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Shoe midsole hardness, sex and age effects on lower extremity kinematics during running
... Various studies have investigated differences in midsole hardness and its effects on rearfoot strike running biomechanics with limited information reported on its effects on lower limb kinematics. It has been found that softer midsoles can increase the maximal ankle pronation angle (Milani et al., 1997), and reduce the range of motion in the sagittal plane at the hip and knee, while increasing it at the ankle joint (Nigg et al., 2012). In terms of ground reaction forces investigations have produced counterintuitive results. ...
... Hennig et al. (1996) provided only the stiffness values of the midsoles tested. Some studies solely provided the shoe material hardness measured using a durometer (Baltich et al., 2015;Heidenfelder et al., 2010;Nigg et al., 1987Nigg et al., , 2012, with only Heidenfelder et al. (2010) providing the location the measurements were taken. Other researchers only provided peak impact acceleration values of the test shoes (Milani et al., 1997), while some studies provided both the durometer hardness of the test midsoles and peak rearfoot impact acceleration values (Sterzing, Custoza, et al., 2015;TenBroek et al., 2014). ...
... In contrast to our first hypothesis, mechanical differences due to midsole hardness did not induce changes in lower limb kinematics during ground contact of running. This is not in line with previous research which found that mechanically altered midsole hardness and peak impact acceleration can influence lower limb kinematics (Milani et al., 1997;Nigg et al., 2012). However, this might be due to the larger range of differences in midsole hardness of at least 12 Asker C between shoe conditions used by Nigg et al. (2012). ...
Mechanical shoe properties impact running biomechanics, triggering subjective shoe perception. Regarding midsole hardness little is known about the minimal mechanical alteration needed to change running biomechanics and perception. Three ethylene-vinyl acetate midsoles differing in rearfoot hardness (47, 53, 57 Asker C), and peak rearfoot impact acceleration (11.65, 12.40, 12.96 g), were used to create experimental shoe conditions (softer, medium, harder), featuring differing peak rearfoot impact accelerations (12.83, 13.49, 13.95 g) when measured with insoles. Twenty-five male rearfoot runners ran on a concrete loop, while capturing ground reaction forces and lower extremity kinematics of eight valid right foot ground contacts in each shoe. Perception of shoe cushioning and shoe rebound was also assessed during these runs using a 15 cm visual analogue scale. Variable magnitude means were compared for main effects (p < 0.05) by repeated measures analysis of variance, Bonferroni post-hoc tests, and effect size estimation (ηp²). No lower limb kinematic effects were induced by the shoes. Kinetically the softer shoe significantly reduced maximal vertical loading rate 1 compared to the medium and harder shoe (131.28 to 138.40 and 139.54 bw/s). Runners significantly perceived the difference in shoe cushioning between the softer and harder shoe (6.32 to 8.06 cm). For the running shoe model in this research a difference in mechanical peak impact acceleration of 0.66 g was sufficient to elicit different biomechanical loading. To elicit different cushioning perception a mechanical difference of 1.12 g was sufficient, resulting in a maximal vertical loading rate 1 difference of 8.26 bw/s. Knowing a shoe model’s biomechanical and perceptual sensitivity to mechanical alteration allows better informed design, development, and manufacturing decisions.
... This approach can lead to potentially relevant information being discarded (Chau, 2001). Previous studies used principal component analysis to analyze the intensity of the GRF over time (Muniz and Bini, 2017;Nigg et al., 2012). However, this technique does not allow statistical comparison between groups. ...
... SPM is a statistical technique that allows the assessment of the entire range of gait signals. Such approaches avoid missing important information from discrete variable selection (Nigg et al., 2012). SPM, in particular, is ideal for the region of interest-related hypothesis testing because it is valid for the whole waveform (Pataky et al., 2016). ...
... The boots analyzed in the present study have not elicited any changes in sagittal lower limb kinematics. It was expected that the SBR boot should have limited dorsiflexion at the terminal stance and preswing phase because of its reduced energy absorption (Cikajlo and Matjačić, 2007;Nigg et al., 2012). However, similar sagittal ankle motion during gait while wearing both boots, in the current study, suggest equitable shaft stiffness. ...
This study compared ground reaction forces (GRF) and lower limb two-dimensional (2D) kinematic waveforms, with and without load carriage, in military personnel walking in two different types of boots. Data were measured in 24-soldiers walking on a 10-m walkway under four randomized crossover trials: wearing two military boots (styrene-butadiene rubber midsole – SBR – 63 Shore A; and polyurethane midsole – PU – 48 Shore A); with and without a 15-kg backpack. GRF traditional parameters were evaluated by two-way ANOVAs. GRF and kinematic waveforms were assessed using a statistical parametric mapping (SPM) method (two-way ANOVA). No interaction effects were observed between footwear and load. GRF at the beginning of stance was lower while wearing the SBR boot condition compared to the PU boot condition. Load carriage increased trunk, hip, and knee flexion. The analyzed military boots did not affect movement patterns during loaded walking and the military boot with SBR midsole material reduced impact to a greater extent. The study demonstrated that the design and materials (e.g., midsole material and thickness) used in boot manufacturing can influence military boot performance.
... Previous studies have shown that the material and the shape of orthoses are effective factors in the kinematic and kinetic variables during various dynamic movements such as walking and running [7,8]. For instance, Nigg et al. (2012) reported that the insole's stiffness is an influential factor of lower extremity kinematics (spatial parameters) during walking [9]. Since any material produces a different level of vibration, therefore, the mechanical properties of soft tissues should be regulated and adjusted through proper muscles contraction before or during movement. ...
... Previous studies have shown that the material and the shape of orthoses are effective factors in the kinematic and kinetic variables during various dynamic movements such as walking and running [7,8]. For instance, Nigg et al. (2012) reported that the insole's stiffness is an influential factor of lower extremity kinematics (spatial parameters) during walking [9]. Since any material produces a different level of vibration, therefore, the mechanical properties of soft tissues should be regulated and adjusted through proper muscles contraction before or during movement. ...
... However, the effect of different types of foot orthoses (based on the stiffness) was not evaluated in their study. Furthermore, material and shape of insoles affect kinematic and kinetic variables during different tasks such as walking and running [7,8,9]. In this regard, Nigg and colleagues (2012) reported that the stiffness of foot orthoses is an effective factor in kinematics of lower extremity (spatial location of thighs, legs and feet) during walking [9]. ...
The purpose of the present study was to determine the immediate effect of various foot orthoses on muscle co-contraction around the ankle and knee joint of the dominant leg during single-leg drop jump task. Thirteen healthy males participated in this quasi-experimental study. The electromyography activity of vastus medialis (VM), rectus femoris (RF), vastus lateralis (VL), biceps femoris (BF), semi tendinus (ST), tibialis anterior (TA), peroneus longus (PL), and gastrocnemius medialis (GM) muscles was recorded during single-leg drop jump movement. The relevant variables in pre-activation, eccentric, and concentric phases of single-leg drop jump task were calculated for each subject in four conditions: wearing shoe only, soft, semi-rigid, and rigid orthoses. There was no significant difference among four condition for the overall lower extremity muscle activity values during pre-activation, eccentric and concentric phases (P>0.05).No significant differences were also observed among the conditions in co-contraction values in the concentric phase. A significant difference was observed for the ankle joint muscles co-contraction between soft/semi-rigid and soft/rigid conditions in the pre-activation phase. There was also difference in medial muscles co-contraction of the knee joint between shoe only/semi-rigid conditions in the eccentric phase (P<0.05). We concluded that during single-leg drop jump in the competition or rehabilitation situations, awareness of changes caused by different types of foot orthoses can be beneficial and improve performance.
... Midsole hardness (MH) is the key parameter with regard to the quality of running shoes. Excessively low or high MH causes abnormal changes in the biomechanical characteristics of the foot during running, causing footrelated injuries [13][14][15]. Peak plantar pressure increases with increasing MH [16]. Although running shoes with low hardness provide better cushioning and comfort, the stability control ability of the foot is poor [16][17][18][19]. ...
... Research on the influence of running shoes on the biomechanical characteristics of the foot has mainly adopted an experimental biomechanical method to analyze the external mechanical situation, overall motion, ground support reaction force, and planar pressure distribution of the foot and the shoe (insole) [14,15]. There are also new experimental methods such as new sensors [25] and algorithms [26] to explore the relationship between the foot and the shoe under different working conditions. ...
High long-term stress on the plantar fascia (PF) is the main cause of plantar fasciitis. Changes in the midsole hardness (MH) of running shoes are an important factor leading to the alteration of the PF. This study aims to establish a finite-element (FE) model of the foot–shoe, and investigates the effects of midsole hardness on PF stress and strain. The FE foot–shoe model was built in ANSYS using computed-tomography imaging data. Static structural analysis was used to simulate the moment of running push and stretch. Plantar stress and strain under different MH levels were quantitatively analyzed. A complete and valid 3D FE model was established. With an increase in MH from 10 to 50 Shore A, the overall stress and strain of the PF were decreased by approximately 1.62%, and the metatarsophalangeal (MTP) joint flexion angle was decreased by approximately 26.2%. The height of the arch descent decreased by approximately 24.7%, but the peak pressure of the outsole increased by approximately 26.6%. The established model in this study was effective. For running shoes, increasing the MH reduces the stress and strain of PF, but also imposes a higher load on the foot.
... The multitude of variables studied and the diversity of the methods of running kinematics analysis make comparisons between studies quite challenging. However, a shared observation across studies is that sex differences mostly existed at the hip and knee level [40][41][42][43][44][45][46][47][48][49][50][51]. ...
... Despite moderate correlations between hip, pelvis and trunk kinematics and hip abductors or external rotator strength in both males or females, hip strength parameters remain a substantial portion of the explained variance in running kinematics for both sexes [45]. Females have also been shown to present greater knee abduction during the stance phase of running compared to males [43,44,[47][48][49][50]. Greater knee abduction has been associated with smaller rearfoot Relative speed: ...
In recent years, there has been a significant expansion in female participation in endurance (road and trail) running. The often reported sex differences in maximal oxygen uptake (VO2max) are not the only differences between sexes during prolonged running. The aim of this narrative review was thus to discuss sex differences in running biomechanics, economy (both in fatigue and non-fatigue conditions), substrate utilization, muscle tissue characteristics (including ultrastructural muscle damage), neuromuscular fatigue, thermoregulation and pacing strategies. Although males and females do not differ in terms of running economy or endurance (i.e. percentage VO2max sustained), sex-specificities exist in running biomechanics (e.g. females have greater non-sagittal hip and knee joint motion compared to males) that can be partly explained by anatomical (e.g. wider pelvis, larger femur-tibia angle, shorter lower limb length relative to total height in females) differences. Compared to males, females also show greater proportional area of type I fibres, are more able to use fatty acids and preserve carbohydrates during prolonged exercise, demonstrate a more even pacing strategy and less fatigue following endurance running exercise. These differences confer an advantage to females in ultra-endurance performance, but other factors (e.g. lower O2 carrying capacity, greater body fat percentage) counterbalance these potential advantages, making females outperforming males a rare exception. The present literature review also highlights the lack of sex comparison in studies investigating running biomechanics in fatigue conditions and during the recovery process.
... An advantage of traditional biomechanical analysis methods (e.g., analysis of several discrete variables, such as peak angles, together with statistical hypothesis tests, such as t-tests or analysis of variance) is that they allow for detailed comparisons of selected variables between different groups, and investigation of relevant factors. However, the disadvantage of these methods is that they may not be able to detect crucial information in large portions of unanalyzed data 32 . In this regard, principal component analysis has recently attracted increasing interest in biomechanical studies because of its usefulness in identifying the movement characteristics of various groups under a range of conditions using waveforms of the entire time series data set in a comprehensive manner [32][33][34][35][36][37][38][39][40][41][42] . ...
... However, the disadvantage of these methods is that they may not be able to detect crucial information in large portions of unanalyzed data 32 . In this regard, principal component analysis has recently attracted increasing interest in biomechanical studies because of its usefulness in identifying the movement characteristics of various groups under a range of conditions using waveforms of the entire time series data set in a comprehensive manner [32][33][34][35][36][37][38][39][40][41][42] . Principal component analysis is a multivariate statistical technique that summarizes the information conveyed by a large number of correlated variables using a smaller number of uncorrelated variables (principal components). ...
Frailty is associated with gait variability in several quantitative parameters, including high stride time variability. However, the associations between joint kinematics during walking and increased gait variability with frailty remain unclear. In the current study, principal component analysis was used to identify the key joint kinematics characteristics of gait related to frailty. We analyzed whole kinematic waveforms during the entire gait cycle obtained from the pelvis and lower limb joint angle in 30 older women (frail/prefrail: 15 participants; non-frail: 15 participants). Principal component analysis was conducted using a 60 × 1224 input matrix constructed from participants’ time-normalized pelvic and lower-limb-joint angles along three axes (each leg of 30 participants, 51 time points, four angles, three axes, and two variables). Statistical analyses revealed that only principal component vectors 6 and 9 were related to frailty. Recombining the joint kinematics corresponding to these principal component vectors revealed that frail older women tended to exhibit greater variability of knee- and ankle-joint angles in the sagittal plane while walking compared with non-frail older women. We concluded that greater variability of knee- and ankle-joint angles in the sagittal plane are joint kinematic characteristics of gait related to frailty.
... Meanwhile, the cushioned footwear worn by individuals with ankle arthropathy has a significant effect on the amount of force acting at the joint [15]. However, understanding the shoe construction and materials used cannot completely explain the cushioning performance efficacy of sport shoes because the neuromuscular system can play a role in reducing the impacts by changing its movement characteristics [16] and joint compliance [17] in response to various shoe conditions. These studies have shown no causal relationship found between impact forces and running injuries regardless of midsole hardness [16] and insert designs [18]. ...
... However, understanding the shoe construction and materials used cannot completely explain the cushioning performance efficacy of sport shoes because the neuromuscular system can play a role in reducing the impacts by changing its movement characteristics [16] and joint compliance [17] in response to various shoe conditions. These studies have shown no causal relationship found between impact forces and running injuries regardless of midsole hardness [16] and insert designs [18]. To date, whether footwear cushioning has detrimental or beneficial effects could be related to test parameters, movement tasks and physical conditions of participants across various studies [1,19,20]. ...
Purpose:
this study aimed to investigate the footwear cushioning effects on impact forces and joint kinematics of the lower extremity during bipedal drop landings before and after acute exercise-induced fatigue protocol.
Methods:
in this case, 15 male collegiate basketball athletes performed drop landings from a 60 cm platform wearing highly-cushioned shoes (HS) and less cushioned shoes (control shoes, CS) before and after acute fatigue-inducing exercises (i.e., shuttle run combined with multiple vertical jumps). Force plates and motion capturing systems were synchronised to measure ground reaction forces and kinematic data during drop landings. Maximum jump height was analysed with one-way ANOVA. Two-way repeated measure ANOVAs were performed on each of the tested variables to examine if there was significant main effects of shoe and fatigue as well as the interaction. The significance level was set to 0.05.
Results:
rearfoot peak impact forces and loading rates significantly reduced when the participants wore HS in pre- and post-fatigue conditions. The peak loading rates in forefoot significantly reduced when HS were worn in post-fatigue. Compared with pre-fatigue, wearing HS contributed to with 24% and 13% reduction in forefoot and rearfoot peak loading rates, respectively, and the occurrence times of first and second peak impact forces and loading rates were much later. In the post-fatigue, a significant increase in the initial contact and minimum angles of the ankle were observed in HS compared with CS.
Conclusion:
these findings suggest that footwear cushioning can reduce landing-related rearfoot impact forces regardless of fatigue conditions. In a situation where the neuromuscular activity is reduced or absent such as post-fatigue wearing better cushioning shoes show superior attenuation, as indicated by lower forefoot and rearfoot impacts.
... The advantages of applying a PCA directly to marker trajectories rather than the more traditional 3D joint angles are (1) that the former does not require assumptions on the orientation of joint axes thus avoiding a potential source of error (Della Croce et al., 2005) and (2) that the movement components dominating each PM can be easily visualized in intuitive stick figure animations (Troje, 2002). Two previous studies successfully applied a kinematic PCA to resolve sexspecific running kinematics but did not use a full-body marker set-up and/or did not report on upper body movement Nigg et al., 2012). ...
... Our solution to this issue was to compare men and women at their preferred running speed and include speed as a covariate in the analysis. This approach allowed us to differentiate between the effects of speed, which are generally present in the basic movement components of running (e.g., PM 2 ) Nigg et al., 2012), and the effects of sex, which we identified in PM 6 and PM 8 . Our findings of more knee flexion during stance in women as well as sex-specific ankle angles at ground contact (see Figures 3F,H) suggest that women may use a modified foot strike pattern from men. ...
There is a sex bias for common overuse running injuries that are associated with sex-specific hip kinematics. Gait retraining programs aimed at altering hip kinematics may be more efficient if they incorporated an understanding of how hip kinematics are correlated with the movement of the remaining body segments. We applied a principal component analysis to structure the whole-body running kinematics of 23 runners (12 ♀) into k = 12 principal movements (PMk), describing correlated patterns of upper and lower body movements. We compared the time-dependent movement amplitudes with respect to each PMk between males and females using a waveform analysis and interpreted our findings according to stick figure animations. The movement amplitudes of two PMs (PM6 and PM8) showed statistically significant effects of “sex,” which were independent of running speed. According to PM8, females showed more hip adduction, which correlated with increased transverse rotation of the pelvis and upper body compared to men. We propose that increased hip adduction and upper body rotation in female runners may be a strategy to compensate for a less efficient arm and upper body swing compared to men. Gait interventions aimed at reducing hip adduction and running-related injuries in female runners should consider instructions for both upper and lower body to maximize training efficacy.
... Results showed a high level of accuracy in classifying strides when comparing different stack heights ranging from 82.9% to 94.4%. This underscores distinct differences in kSYNs linked to varying stack heights, aligning with prior research for example on midsole hardness, i.e. 86.0% to 99.5% for hard, medium, and soft midsoles (Nigg et al., 2012). Observations revealed a significant contribution to distinguishing between stack heights across the entire spectrum of kSYNs, from low-order to high-order ( Figure 2). ...
Understanding how shoe features affect motor control processes is crucial for designing targeted running shoes. The purpose of this study was to investigate adaptations of coupled movement components, i.e. kinematic synergies (kSYNs), when running with different shoe stack heights (19 mm, 35 mm, and 50 mm). The applied analysis combined a principal component analysis, support vector machine classifiers, and stride-to-stride variability (SSV) calculations. The results showed classification rates ranging from 82.9% to 94.4% across different stack heights. Notably, only the 50 mm stack height demonstrated increased SSV for the kSYNs that highly contribute to separating the two stack heights when compared to the 19 mm condition. The findings suggest that the motor control system adjusts to variations in stack height within certain limits by regulating task-relevant kSYNs.
... We allowed participants to use their preferred footwear to capture their habitual running pattern. However, footwear can affect lower limb biomechanics (Nigg et al., 2012) and running economy (Hoogkamer et al., 2018), potentially acting as a confounding factor in the clustering process and running economy comparison. Information about the shoe-type used by the runners could have added to the discussion. ...
... The optimal stride frequency (Cavanagh & Kram, 1989) of an elite long distance runner is around 4800 strides per hour (Musgjerd et al., 2021;Oeveren et al., 2017). During strides, the foot-ground reaction forces exhibit repeated compressive loadings (Nigg et al., 2012). Figure 1(a) shows the heel landing (first peak) and the forefoot propulsion (second peak) during the first 200 ms for a 75 kg man running at 12 km h −1 (Clarke et al., 1983). ...
... While increasing stack height may adversely affect safety (e.g., prolongs eversion, which increases the risk of injury (Hannigan and Pollard, 2020)), modifying midsole hardness is a safer way to attenuate impact. Midsole hardness values range from Asker scale C-40 to C-70 in running footwear (Baltich et al., 2015;Ly et al., 2010;Meardon et al., 2018;Nigg et al., 2012;Nigg and Gérin-Lajoie, 2011;Sun et al., 2020). In vitro impact testing has shown that softer midsoles commonly have better cushioning (Aerts and De, 1993;Cook et al., 1985;Frederick, 1986;Shorten and Mientjes, 2011), but the effects have been mixed in human studies (Baltich et al., 2015;Logan et al., 2010;Malisoux et al., 2021a;Nigg et al., 1987). ...
... To identify the single weights of each joint, each plane, kinematics, and kinetics in landing pattern recognition, the current study divides the input signal of the classification task into 9 algorithmic situations. 1) Both kinematics and kinetics signals: M1 before fatigue = 280(56 subjects × 5 trials ) × 202(101 kinematics + 101 kinetics ) × 9(3 joint × 3 plane ), M1 after fatigue = 280(56 subjects × 5 trials ) × 202(101 kinematics + 101 kinetics ) × 9(3 joint × 3 plane ); 2) Only kinematics signal: M2 before fatigue = 280(56 subjects × 5 trials ) × 101 kinematics × 9(3 joint × 3 plane ), M2 after fatigue = 280(56 subjects × 5 trials ) × 101 kinematics × 9(3 joint × 3 plane ); 3) Only kinetics signal: M3 before fatigue = 280(56 subjects × 5 trials ) × 101 kinetics × 9(3 joint × 3 plane ), M3 after fatigue = 280(56 subjects × 5 trials ) × At the same time, to ensure that the results of the LRP interpretation method employed after classification can be directly mapped to the original signal, the input signal was directly inputted into the classification model in this study. This was also done to better interpret the LRP results, thus not using techniques such as principal component analysis (PCA), which is commonly used in feature extraction and automatic pattern classification [12,33,47,48]. ...
As one of many fundamental sports techniques, the landing maneuver is also frequently used in clinical injury screening and diagnosis. However, the landing patterns are different under different constraints, which will cause great difficulties for clinical experts in clinical diagnosis. Machine learning (ML) have been very successful in solving a variety of clinical diagnosis tasks, but they all have the disadvantage of being black boxes and rarely provide and explain useful information about the reasons for making a particular decision. The current work validates the feasibility of applying an explainable ML (XML) model constructed by Layer-wise Relevance Propagation (LRP) for landing pattern recognition in clinical biomechanics. This study collected 560 groups landing data. By incorporating these landing data into the XML model as input signals, the prediction results were interpreted based on the relevance score (RS) derived from LRP. The interpretation obtained from XML was evaluated comprehensively from the statistical perspective based on Statistical Parametric Mapping (SPM) and Effect Size. The RS has excellent statistical characteristics in the interpretation of landing patterns between classes, and also conforms to the clinical characteristics of landing pattern recognition. The current work highlights the applicability of XML methods that can not only satisfy the traditional decision problem between classes, but also largely solve the lack of transparency in landing pattern recognition. We provide a feasible framework for realizing interpretability of ML decision results in landing analysis, providing a methodological reference and solid foundation for future clinical diagnosis and biomechanical analysis.
... Thus, studying the whole-body kinematics of running and uncovering signal beyond the comparison of single aspects requires combined datasets of many runners. It is well-known that recognizing particular features in gait requires large amounts of data 31,32 . ...
Collecting large datasets for investigations into human locomotion is an expensive and labor-intensive process. Methods for 3D human pose estimation in the wild are becoming increasingly accurate and could soon be sufficient to assist with the collection of datasets for analysis into running kinematics from TV broadcast data. In the domain of biomechanical research, small differences in 3D angles play an important role. More precisely, the error margins of the data collection process need to be smaller than the expected variation between athletes. In this work, we propose a method to infer the global geometry of track and field stadium recordings using lane demarcations. By projecting estimated 3D skeletons back into the image using this global geometry, we show that current state-of-the-art 3D human pose estimation methods are not (yet) accurate enough to be used in kinematics research.
... Prior research shows that the different hardness of shoe soles has a great influence on the ankle joint and the first metatarsophalangeal joint. Increasing the mid-sole hardness of shoes can reduce the maximum ankle dorsiflexion angle [9,10], increase stability and reduce fatigue [11]. When fatigue is produced, the maximum distance that COP moves in the x and y axes increases, and the average or maximum velocity in the x and y axes increases [12]. ...
The purpose of this study was to compare the differences in shooting performance, physical stability, and lower extremity muscle fatigue in high-level shooters wearing shooting shoes and sports shoes, and to determine the causes. Eight high-level 10 m air pistol shooters wore shooting shoes and sports shoes in a simulated shooting qualification experiment (60 rounds in 75 min) and we recorded shooting scores, pressure centers (COP), and median frequency of muscle fatigue index (MDF). All the data are expressed as mean ± standard deviation and are compared using a paired t-test. Athletes in shooting shoes scored higher than those in sports shoes (p < 0.05); COP moved less in the front-to-back and left-to-right directions for athletes wearing shooting shoes rather than sports shoes; and fewer muscles experienced fatigue, with fatigue also occurring later, for athletes wearing shooting shoes rather than sports shoes. Shooting shoes may reduce the sway of athletes’ center of pressure in the anterior–posterior and left–right directions, enhance postural stability, and result in higher shooting scores. In addition, they may make shooters feel more comfortable and relaxed during long training sessions and competitions.
... Recently, machine learning and multivariate analysis have been shown to be useful methods for discovering mechanical trends in running performance [40]. For example, PCA and SVM have been used to recognize the gait patterns differences [35], [42], [50], [61]. Thus, by using machine learning and multivariate analysis, there could be differences identified in gait muscle forces generated while wearing the NS and BS. ...
Purpose: The aim of this study was to investigate the differences in ankle joint parameters of biomechanics changes between the normal shoes (NS) and the bionic shoes (BS) during the running stance phases. Methods: A total of 40 Chinese male runners from Ningbo University were recruited for this study (age: 22.3 ± 3.01 years; height: 174.67 ± 7.11 cm; body weight (BW): 66.83 ± 9.91 kg). The participants were asked to perform a running task. Statistical parametric mapping (SPM) analysis was used to investigate any differences between NS and BS during the running stance phases. The principal component analysis (PCA) and support vector machine (SVM) were used to further explore the differences of the muscle force between the BS and NS. Results: Significant differences (p < 0.05) were found in the first metatarsophalangeal joint (MPJ1), ground reaction force (GRF), ankle joint and around muscle forces. Furthermore, the accuracy of SVM model in identifying the gait muscle force between BS and NS reached 100%, which proved that the BS had a very large impact on the gait muscle force compared with NS. Conclusions: We found that BS may be better suited to the human condition than other unstable shoes, or even NS. In addition, our results suggest that BS play an important role in reducing ankle injuries during running by increasing muscle participation in unstable conditions while better restoring the most primitive instability of foot condition that humans have.
... 74 Understanding the underlying knee biomechanics during simple tasks is imperative. Previous work in this area has evaluated the sex-and/or age-based differences in knee kinematics/kinetics of running, [75][76][77][78][79] jumping tasks, [80][81][82][83][84][85] and cutting maneuvers 80,86,87 in children, adolescents, and young adults. Multiple other tasks have been evaluated biomechanically in adolescents using 3DMA including tasks involved in movement screening 88 ; directional changes/run-and-cut tasks [89][90][91][92][93] ; drop-landing or vertical jump tasks 88,89,[94][95][96][97][98][99] ; and sport-specific tasks including soccer kicks, 100 baseball/softball, 101-105 gymnastics, 106 tennis, 107,108 volleyball, 99 and cricket. ...
Three-dimensional motion capture systems may improve evaluation, treatment, and rehabilitation of knee injuries, because quantitative assessment of the knee improves understanding of biomechanical mechanisms. The benefit of using motion analysis in pediatric sports medicine is that it allows closer and more focused evaluation of sports injuries using kinematics, kinetics, and electromyogram with physical and imaging to determine what is happening dynamically during sports. Future research investigating knee injuries should focus on identifying risk factors, assessing the effectiveness of surgical and nonsurgical interventions, and developing return to sport/rehabilitation protocols. The literature is focused on motion capture in adults with knee injuries.
... Principal component analysis has been used to identify dominant movements of running biomechanics in order to classify differences between participant subgroups. 23,24 This approach allows for complete data set analysis while reducing a large number of variables into principal components and minimizing type I error. Phinyomark et al 8 utilized principal component analysis in conjunction with a support vector machine to explore running kinematics, and their results support both sex-and age-specific analyses. ...
Sex-based analyses are important when studying running kinematics. Females experience a unique aging process and demonstrate differences in running biomechanics from males. The purpose was to determine the relationship between age and running kinematics in female runners. Forty-six female runners (18–65 y) ran at self-selected jogging and maximal speed on a treadmill. Lower-extremity joint kinematics were calculated, and 2 principal component analyses (jogging speed and maximal speed) were performed from kinematic variables. Regression was used to examine the relationship between age and identified components, and between age and the variables with the highest loadings within these components. For jogging speed, there was a positive relationship between age and ankle varus at initial contact and a negative relationship between age and peak eversion, hip adduction, knee flexion, dorsiflexion, and hip adduction at initial contact ( P s < .05). For maximal speed, initial contact ankle frontal plane angle became more positive with age, and there was a negative relationship with age and peak eversion, dorsiflexion and knee flexion, and knee flexion and hip adduction at initial contact ( P s < .05). Primarily distal joint angles decreased with increasing age in female recreational runners at self-selected running speeds.
... When comparing biological sex, it has been shown that there are significant differences found in lower limb kinematics while running, which have been attributed to anatomical and morphological differences found between the sexes. These differences in morphology have been seen to influence frontal and sagittal plane joint angles of biological females when compared to biological males while running which can have an impact on runningrelated injuries [16][17][18][19]. One sex-related anatomical difference in the lower limb, which has been studied extensively, is found in the feet showing a difference between overall length, anatomical ball width, heel width, toe height, and instep height [20][21][22][23]. ...
Alterations in running shoe design have been studied and used in the prevention of injury and enhancement of performance allowing running shoe companies to market to a variety of runners based on skill level, foot-strike pattern, and even sex. These alterations have been shown to affect biomechanical and physiological variables associated with running. Some shoe companies have designed shoes specifically for biological female runners due to the morphological differences found between male and female feet. The purpose of this study is to determine if sex-specific running shoes can alter female runner biomechanics or physiology. Female runners were asked to run in the male and female models of the Altra Torin 4 Plush shoe to determine if there were differences in ground reaction forces (GRFs), sagittal plane joint angles and moments, oxygen consumption (VO2), respiratory exchange ratio (RER), and perceived level of comfort while running; There were no significant differences in GRFs, sagittal joint angles and moments, VO2, RER, or perceived comfort; There were no differences in measured biomechanical or physiological variables between the female and male version of the shoes suggesting that the alterations made to the female-specific shoe do not provide any additional benefit to female recreational runners.
... Footwear was the final sub-theme of trainingrelated metrics identified, with perceptions that older shoe age increased injury risk. This perception may be associated with the theory that shoe cushioning decreases loading on the body [75,76], and a decrease in cushioning capacity with extended use increases the risk of RRI's [77,78]. However, a recent systematic review concluded that no evidence-based recommendations could be made for shoe age and preventing RRI's [79]. ...
Purpose
Understanding the perceived efficacy and ease of use of technologies will influence initial adoption and sustained utilization. The objectives of this study were to determine the metrics deemed important by runners for monitoring running-related injury (RRI) risk, and identify the facilitators and barriers to their use of injury focused wearable technologies.
Methods
A qualitative focus group study was undertaken. Nine semi-structured focus groups with male (n = 13) and female (n = 14) recreational runners took place. Focus groups were audio and video recorded, and transcribed verbatim. Transcripts were thematically analysed. A critical friend approach was taken to data coding, and multiple methods of trustworthiness were executed.
Results
Excessive loading and inadequate recovery were deemed the most important risk factors to monitor for RRI risk. Other important factors included training activities, injury status and history, and running technique. The location and method of attachment of a wearable device, the design of a smartphone application, and receiving useful injury-related information will affect recreational runners’ adoption of injury focused technologies.
Conclusions
Overtraining, training-related and individual-related risk factors are essential metrics that need to be monitored for RRI risk. RRI apps should include the metrics deemed important by runners, once there is supporting evidence-based research. The difficulty and/or ease of use of a device, and receiving useful feedback will influence the adoption of injury focused running technologies. There is a clear willingness from recreational runners to adopt injury focused wearable technologies whilst running.
... Landing from jumping smash could exert a huge load on the body since it is a single-leg landing technique (Rambely & Abas, 2007). Many studies have been conducted on the jumping movements in various sports and activities such as basketball, walking and running (Hong et al., 2013;Hu et al., 2015;Kersting & Brüggemann, 2006;Nigg et al., 2012;Webster et al., 2021;Zhang et al., 2005). However, finite element studies focus on jumping movements in badminton are still scarce (Hong et al., 2013;Hu et al., 2015). ...
Previous research has reported that up to 92% of injuries amongst badminton players consist of lower limb, whereby 35% of foot fractures occurred at the metatarsal bone. In sports, insoles are widely used to increase athletes' performance and prevent many injuries. However, there is still a lack of badminton insole analysis and improvements. Therefore, this study aimed to biomechanically analyse three different insole designs. A validated and converged three-dimensional (3D) finite element model of ankle-foot complex was developed, which consisted of the skin, talus, calcaneus, navicular, three cuneiform, cuboid, five metatarsals and five phalanges. Three existing insoles from the market, (1) Yonex Active Pro Truactive, (2) Victor VT-XD 8 and (3) Li-Ning L6200LA, were scanned using a 3D scanner. For the analysis, single-leg landing was simulated. On the superior surface of the skin, 2.57 times of the bodyweight was axially applied, and the inferior surface of the outsole was fixed. The results showed that Insole 3 was the most optimum design to reduce peak stress on the metatarsals (3.807 MPa). In conclusion, the optimum design of Insole 3, based on the finite element analysis, could be a justification of athletes' choices to prevent injury and other complications.
... Principal component analysis (PCA) is more sensitive than traditional parameter-based analysis techniques in detecting differences in kinematic and kinetic waveforms (20,21). More and more studies are using PCA in time series datasets such as motion posture, gait, and ground reaction force (GRF), because PCA allows the detection of time-varying coordinated correlation patterns (22)(23)(24)(25). Therefore, PCA can be used to extract the main characteristics of the GRF and motion posture of cats during landing, which can not only determine the potential relationship between variables but also reveal the main findings within the data set. ...
Felines have significant advantages in terms of sports energy efficiency and flexibility compared with other animals, especially in terms of jumping and landing. The biomechanical characteristics of a feline (cat) landing from different heights can provide new insights into bionic robot design based on research results and the needs of bionic engineering. The purpose of this work was to investigate the adaptive motion adjustment strategy of the cat landing using a machine learning algorithm and finite element analysis (FEA). In a bionic robot, there are considerations in the design of the mechanical legs. (1) The coordination mechanism of each joint should be adjusted intelligently according to the force at the bottom of each mechanical leg. Specifically, with the increase in force at the bottom of the mechanical leg, the main joint bearing the impact load gradually shifts from the distal joint to the proximal joint; (2) the hardness of the materials located around the center of each joint of the bionic mechanical leg should be strengthened to increase service life; (3) the center of gravity of the robot should be lowered and the robot posture should be kept forward as far as possible to reduce machine wear and improve robot operational accuracy.
... However, the reported changes in running kinematics remains inconsistent among different studies, particularly at the ankle joint (Agresta et al., 2018;Sinclair, 2017;Willy & Davis, 2014). Such great variability in the running kinematics has been explained by footwear adaptation (Au et al., 2018;Nigg et al., 2012). Interestingly, not all previous studies have considered the time allowed for participants to familiarise themselves with the treadmill prior to data collection. ...
This study investigated treadmill familiarisation time in different shoe conditions by comparing lower limb consecutive kinematics waveforms using a trend symmetry method to calculate trend symmetry index, range amplitude ratio and range offset. Eighteen young adults (26.6 ± 3.3 years, 7 females) completed three 10-minute running trials at their preferred running speed (2.30 ± 0.17 m/s) on a treadmill with three shoe conditions (i.e., usual, minimalist and maximalist shoes) in a random order. Sagittal lower limb kinematic data were recorded using inertial measurement units. The results showed that sagittal-plane kinematic waveforms in the hip, knee and ankle remained consistent (trend symmetry > 0.95) without extreme excursions (range amplitude ratio ≈ 1) over 10 minutes within each testing shoe condition. Significant time × shoe interaction effect was observed in range offset (i.e., absolute differences in the average degree of kinematic waveforms between consecutive minutes) at ankle (p = 0.029, ŋp2 = 0.096) and knee (p = 0.002, ŋp2 = 0.126). Post-hoc analysis suggested that running with novel shoes required a shorter time to achieve stable lower limb kinematics (2 to 3 minutes) compared with usual shoes (7 minutes). In conclusion, young healthy adults need up to 3 and 7 minutes to familiarise to the treadmill when running at their preferred speed with their novel and usual running shoes.
... In the research of gait pattern recognition, it is often necessary to record a large amount of data in order to better recognize gait patterns 36 , which makes it difficult to complete an accurate interpretation of gait pattern recognition results with few variables as possible. In this study, the variables were imported into the DNN model for training, and then the relevance score of each variable's contribution to the gait pattern recognition results was obtained through LRP. ...
Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mileages. In recent years, machine learning algorithms have been used for pattern recognition and classification of gait features to emphasize the uniqueness of gait patterns. However, they all have a representative problem of being a black box that often lacks the interpretability of the predicted results of the classifier. Therefore, this study was conducted using a Deep Neural Network (DNN) model and Layer-wise Relevance Propagation (LRP) technology to investigate the differences in running gait patterns between higher-mileage runners and low-mileage runners. It was found that the ankle and knee provide considerable information to recognize gait features, especially in the sagittal and transverse planes. This may be the reason why high-mileage and low-mileage runners have different injury patterns due to their different gait patterns. The early stages of stance are very important in gait pattern recognition because the pattern contains effective information related to gait. The findings of the study noted that LRP completes a feasible interpretation of the predicted results of the model, thus providing more interesting insights and more effective information for analyzing gait patterns.
... Nonetheless, the predominance of sagittal plane movements within unique and generic movement characteristics remains striking. A potential explanation might be that postural control and running movements are mostly confined to the sagittal plane [34][35][36]. In this plane, a joint's range of motion tends to be larger [37]; thus, similarities and dissimilarities in flexion/extension movements between individuals might simply be more common. ...
Human movement patterns were shown to be as unique to individuals as their fingerprints. However, some movement characteristics are more important than other characteristics for machine learning algorithms to distinguish between individuals. Here, we explored the idea that movement patterns contain unique characteristics that differentiate between individuals and generic characteristics that do not differentiate between individuals. Layer-wise relevance propagation was applied to an artificial neural network that was trained to recognize 20 male triathletes based on their respective movement patterns to derive characteristics of high/low importance for human recognition. The similarity between movement patterns that were defined exclusively through characteristics of high/low importance was then evaluated for all participants in a pairwise fashion. We found that movement patterns of triathletes overlapped minimally when they were defined by variables that were very important for a neural network to distinguish between individuals. The movement patterns overlapped substantially when defined through less important characteristics. We concluded that the unique movement characteristics of elite runners were predominantly sagittal plane movements of the spine and lower extremities during mid-stance and mid-swing, while the generic movement characteristics were sagittal plane movements of the spine during early and late stance.
... In any case, results on adults might be less generalizable to men compared to women. Evidence from the literature shows opposing results on the influence of gender on PCAdriven locomotion pattern analysis during walking (Kobayashi, Hobara, Heldoorn, Kouchi, & Mochimaru, 2016;Rowe, Beauchamp, & Astephen Wilson, 2021;Saito & Kobayashi, 2021;Troje, 2002) and running (Maurer, Federolf, von Tscharner, Stirling, & Nigg, 2012;Nigg, Baltich, Maurer, & Federolf, 2012;Phinyomark, Hettinga, Osis, & Ferber, 2014). Kobayashi et al. demonstrated a significant age-gender interaction in pelvic and hip joint motions in healthy adults aged 20 to 75 (Kobayashi et al., 2016). ...
The relative displacements of body segments during walking can be reduced to a small number of multi-joint kinematic patterns, pmk, through Principal Component Analysis (PCA). These patterns were extracted from two groups of children (n = 8, aged 6–9 years, 4 males, and n = 8, aged 10–13 years, 4 males) and 7 adults (21–29 years, 1 male), walking on a treadmill at various velocities, normalized to body stature (adimensional Froude number, Fr). The three-dimensional coordinates of body markers were captured by an optoelectronic system.
Five components (pm1 to pm5) explained 99.1% of the original dataset variance. The relationship between the variance explained (“size”) of each pmk and the Fr velocity varied across movement components and age groups. Only pm1 and pm2, which described kinematic patterns in the sagittal plane, showed significant differences (at p < 0.05) across pairs of age groups. The time course of the size of all the five components matched various mechanical events of the step cycle at the level of both body system and lower limb joints. Such movement components appeared clinically interpretable and lend themselves as potential markers of neural development of walking.
... Principal component analysis has been used to identify dominant movements of running biomechanics in order to classify differences between participant subgroups. 23,24 This approach allows for complete data set analysis while reducing a large number of variables into principal components and minimizing type I error. Phinyomark et al 8 utilized principal component analysis in conjunction with a support vector machine to explore running kinematics, and their results support both sex-and age-specific analyses. ...
... Moreover, it has been described that sex and age are differentiating factors in children's motor competence. 20, 21 Boyer et al. 22 and Nigg et al. 23 observed that there is a significant impact of sex on runners' mechanics. In addition, several studies with young runners have reported that sex is a differentiating parameter, as they found that boys performed better than girls in sprint ability, 21 CODA 21,24 and jump capacity 20 during late childhood and youth. ...
The aim of the present research was to describe the changes in the locomotor competence [i.e. sprint, change of direction ability (CODA) and jump capacity] of young runners from an athletic training school after one season, according to runners’ sex and age. Two hundred and forty-one young runners from an athletic training school were divided by sex (boys, n = 107, and girls, n = 134) and age [under 8 years old (U8, n = 70), under 10 years old (U10, n = 68), under 12 years old (U12, n = 45), under 14 years old (U14, n = 39) and under 16 years old (U16, n = 19)]. At the start of the training season (PRE) and at the end of the season (POST), the runners performed different tests in order to assess their locomotor competence. The results showed that boys and girls improved their performance during the season in the 5 m sprint (p = 0.000, ES = -0.58 to -0.74) and horizontal countermovement jump (HCMJ) (p = 0.000, ES = 0.51 to 1.02), and decreased it in the 15 m sprint test (p = 0.011 or p = 0.006, ES = 0.27 to 0.31), and only girls improved in change of direction ability (CODA) (p = 0.000, ES = -0.22 to -0.27). In addition, with respect to age categories, all groups improved their performance in the HCMJ (p = 0.000 - 0.005, ES > 0.40) and the 5 m sprint tests (p = 0.000 - 0.002, ES = -0.68 to -1.24). Although in the 505 test no group improved its result (p = 0.184 - 0.314, ES = -0.25 to 0.01), the U8 and U10 groups improved in the modified agility test (MAT) (p = 0.000 or p = 0.003, ES = -0.38 to -0.41). In conclusion, there are differences in the changes in the locomotor competence according to runners’ sex and age, so perhaps age- and sex-dependent specialization in training is necessary.
... Cinsiyetin koşu mekaniğine olan etkisini araştıran çalışmalar, kadınların koşu sırasında daha büyük kalça addüksiyon ve diz abdüksiyon açısı, artmış pelvik tilt, artmış kalça addüksiyon açısal hızı, topuk vuruşu sırasında artmış kalça internal rotasyonu ve diz eksternal rotasyonu olduğunu kaydetmiştir. [24][25][26] Ferber ve ark. koşu sırasında alt ekstremite mekaniğini cinsiyetler arası detaylı bir şekilde araştırmış, kadın koşucuların frontal düzlemde büyük kalça addüksiyon açısı ve kalça negatif işi yaptığını bulmuştur. ...
portif aktiviteler sırasında sıçrama sonrası yere inme alt ekstremitede en çok görülen yaralama tiplerinden biridir. 1 Sıçrama sonrası yere inme mekaniğinin bozuk olması, yetersiz alt ekstremite dinamik kontrolü ile ilişkilendirilir. 1-3 Yere inme mekanizmasındaki cinsiyetler arası farklılıklar çoklu hareket düzlemle-rinde ve farklı eklemlerde görülmektedir. Kadınlar tipik olarak erkeklere kıyasla sıçrama sonrası daha dik bir gövde pos-türü ile yere iner. 3,4 Bu nedenle, kadınlar sıçrama sonrası yere inmede büyük bir vertikal yer reaksiyon kuvveti, büyük zirve posterior yer reaksiyon kuvveti, prok-simal anterior tibial parçalama stresi ve artmış kalça internal rotasyonu, azalmış diz fleksiyonu ve artmış diz valgus açısı sergilemektedir (Resim 1). 1-3 SAGİTAL DÜZLEM Blackburn ve Padua, kadın sporcularda gövde, kalça ve diz biyomekaniğini gövde fleksiyonuna odaklanarak sıçrama sonrası yere inme ve sporcuların tercih ettikleri Kadın ve Erkek Sporcularda Biyomekaniksel Farklılıklar Ö ÖZ ZE ET T Kadınların spora katılımının artmasıyla birlikte spor yaralanmalarının kadınlarda görülme oranı artmıştır. Aynı sporu yapan kadın ve erkek sporcular birbirleriyle kıyaslandığında, kadınla-rın daha fazla yaralanmalara maruz kaldığı görülmüştür. Kadınların erkeklere göre farklı anato-miye, hormonal cevaba ve biyomekaniğe sahip olması, sportif aktivitelerde kadınların farklı cevaplar ortaya koyduklarını düşündürmektedir. Sıçrama sonrası düşüş ve yana kesme manevralarında, koşu ve fırlatma aktivitelerinde cinsiyetler arası biyomekaniksel farklılıklar bulunmuştur. Vücut biyo-mekaniğinin analiz edilerek gerekli nöromüsküler eğitimlerle spor yaralanmalarının azaltılabileceği gösterilmiştir. A An na ah h t ta ar r K Ke e l li i m me e l le er r: : Alt ekstremite; biyomekanikal fenomen; hızbilim; cinsiyet kimliği A AB BS S T TR RA AC CT T With the increase of women's participation in sports, the incidence of sports injuries has increased in women athletes. When women and men athletes in the same sport were compared with each other, women were exposed to more sports injuries. The fact that women have different anatomy, hormonal response and biomechanics compared to men suggests that women show different respoenses in sports activities. Biomechanical differences between genders were found in the landing from a jump and cutting maneuvers, running and throwing activities. It has been shown that body biomechanics can be analyzed and sports injuries can be reduced by required neuro-muscular training.
... A number of applications were presented throughout this paper. Additional interest has been noted in osteoarthritis [88,89], patellofemoral pain [90], military training [91,92], shoe design [93], and multiple sclerosis [94], to name just a few. ...
Sex differences in human locomotion are of interest in a broad variety of interdisciplinary applications. Although kinematic sex differences have been studied for many years, the underlying reasons behind several noted differences, such as pelvis and torso range of motion, are still not well understood. Walking speed and body size in particular represent confounding influences that hinder our ability to determine causal factors. The purpose of this study was to investigate sex differences in whole body gait kinematics across a range of controlled, non-dimensional walking and running speeds. We hypothesized that as task demand (i.e. gait speed) increased, the influences of modifiable factors would decrease, leading to a kinematic motion pattern convergence between sexes. Motion capture data from forty-eight healthy young adults (24 M, 24 F) wearing controlled footwear was captured at three walking and three running Froude speeds. Spatiotemporal metrics, center of mass displacement, and joint/segment ranges of motion were compared between sexes using 2x6 mixed-model ANOVAs. Three dimensional time-series waveforms were also used to describe the time-varying behavior of select joint angles. When controlling for size, sex differences in spatiotemporal metrics and center of mass displacement disappeared. However, contrary to our hypothesis, sagittal plane ankle, frontal plane pelvis, and transverse plane pelvis and torso range of motion all displayed sex differences that persisted or increased with gait speed. Overall, most spatiotemporal sex differences appear to be related to size and self-selection of gait speeds, while in contrast, sex differences in joint motion may be more inherent and ubiquitous than previously thought. Discussion on potential causal factors is presented.
... Gender differences in kinematics have been shown in many sports. Young runners have been found to have a significant gender effect on running mechanics [12][13][14]. McLean et al. found differences in the kinematics of the knees, hips, and ankles between men and women who play basketball [15]. Due to these differences, the authors also stressed upon the higher risk of anterior cruciate ligament injury (ACL) while playing in women. ...
Background: The identification of gender differences in kinematics and coordination of movement in different body segments in sports may improve the training process by emphasizing the necessity of its differentiation, and consequently individualization, developing, and improving the technique in women and men. Indicating differences can also help in determining the risk of injury in order to prevent from them by diversifying training programs. However, there is no information regarding this problem in the existing literature pertaining to table tennis. Therefore, the aim of the study was to evaluate the differences in the values of selected angular and kinematic parameters during topspin forehand and topspin backhand shots between male and female table tennis players. Methods: Six male and six female advanced table tennis players performed topspin forehand and topspin backhand shots, both receiving a backspin ball. The angular parameters in four events (ready position, backswing, maximum acceleration, and forward) at chosen joints as well as the maximal acceleration of the playing hand were measured, using the myoMotion system, and were compared between male and female players. Results: Significant differences (p ≤ 0.05) were found in the magnitude of angular parameters and maximum hand acceleration between men and women. The movement pattern of topspin strokes performed by men takes into account, more than that in the case of women, movements that use large muscle groups and large joints (hip joints, trunk joints, shoulder joints in extension, and flexion). The difference in the values of maximal acceleration reached almost 50 m/s 2 in topspin forehand (p < 0.01) and 20 m/s 2 in backhand (p < 0.01). Conclusions: Differentiation of movement patterns can be a manifestation of movement optimization due to anthropological differences and limitations. The differences in the values of maximal acceleration suggest that women could use both sides to perform a topspin attack against the backspin ball, while men should seek opportunities to make a stronger shot with a forehand topspin.
... Gender differences in kinematics have been shown in many sports. Young runners have been found to have a significant gender effect on running mechanics [12][13][14]. McLean et al. found differences in the kinematics of the knees, hips, and ankles between men and women who play basketball [15]. Due to these differences, the authors also stressed upon the higher risk of anterior cruciate ligament injury (ACL) while playing in women. ...
Previous studies on gender differences in running biomechanics have predominantly been limited to joint angles and have not investigated a potential influence of footwear condition. This study shall contribute to closing this gap. Lower body biomechanics of 37 recreational runners (19 f, 18 m) were analysed for eight footwear and two running speed conditions. Presenting the effect size Cliff’s Delta enabled the interpretation of gender differences across a variety of variables and conditions. Known gender differences such as a larger range of hip movement in female runners were confirmed. Further previously undiscovered gender differences in running biomechanics were identified. In women, the knee extensors are less involved in joint work. Instead, compared to men, the supinators contribute more to deceleration and the hip abductors to acceleration. In addition to differences in extent, women also show a temporal delay within certain variables. For the foot, ankle and shank, as well as for the distribution of joint work, gender differences were found to be dependent on footwear condition, while sagittal pelvis and non-sagittal hip and thigh kinematics are rather consistent. On average, smaller gender differences were found for an individual compared to a uniform running speed. Future studies on gender differences should consider the influence of footwear and running speed and should provide an accurate description of the footwear condition used. The findings of this study could be used for the development of gender-specific running shoes and sports and medical products and provide a foundation for the application of smart wearable devices in gender-specific training and rehabilitation
Background: Finding the best subset of gait features among biomechanical variables is considered very important because of its ability to identify relevant sports and clinical gait pattern differences to be explored under specific study conditions. This study proposes a new method of metaheuristic optimization-based selection of optimal gait features, and then investigates how much contribution the selected gait features can achieve in gait pattern recognition.
Methods: Firstly, 800 group gait datasets performed feature extraction to initially eliminate redundant variables. Then, the metaheuristic optimization algorithm model was performed to select the optimal gait feature, and four classification algorithm models were used to recognize the selected gait feature. Meanwhile, the accuracy results were compared with two widely used feature selection methods and previous studies to verify the validity of the new method. Finally, the final selected features were used to reconstruct the data waveform to interpret the biomechanical meaning of the gait feature.
Results: The new method finalized 10 optimal gait features (6 ankle-related and 4-related knee features) based on the extracted 36 gait features (85% variable explanation) by feature extraction. The accuracy in gait pattern recognition among the optimal gait features selected by the new method (99.81%±0.53%) was significantly higher than that of the feature-based sorting of effect size (94.69%±2.68%), the sequential forward selection (95.59%±2.38%), and the results of previous study. The interval between reconstructed waveform-high and reconstructed waveform-low curves based on the selected feature was larger during the whole stance phase.
Significance: The selected gait feature based on the proposed new method (metaheuristic optimization-based selection) has a great contribution to gait pattern recognition. Sports and clinical gait pattern recognition can benefit from population-based metaheuristic optimization techniques. The metaheuristic optimization algorithms are expected to provide a practical and elegant solution for sports and clinical biomechanical feature selection with better economy and accuracy.
To understand the nature of aesthetic walking pattern, we conducted two experiments. At first, we compared the kinematic gait characteristics between four ballet dancers and ten age-matched controls. Next, we conducted an experiment to evaluate the visual aesthetic impression of gait kinematics. To evaluate gait characteristics, principal component analyses is applied to kinematic time series. The following kinematic characteristics were commonly found in the ballet dancers and peoples with walking patterns of high aesthetic qualities ; 1) extended torso, 2) increment in the pelvic anteversion, 3) small knee flexion when heel-contacted.
Research is often conducted to investigate footwear mechanical properties and their effects on running biomechanics, but little is known about their influence on runner satisfaction, or how well the shoe is perceived. A tool to predict runner satisfaction in a shoe from its mechanical properties would be advantageous for footwear companies. Data in this study were from a database (n = 615 subject-shoe pairings) of satisfaction ratings (gathered after participants ran on a treadmill), and mechanical testing data for 87 unique subjects across 61 unique shoes. Random forest and elastic net logistic regression models were built to test if footwear mechanical properties and subject characteristics could predict runner satisfaction in 3 ways: degree-of-satisfaction on a 7-point Likert scale, overall satisfaction on a 3-point Likert scale, and willingness-to-purchase the shoe (yes/no response). Data were divided into training and validation sets, using an 80–20 split, to build the models and test their accuracy, respectively. Model accuracies were compared against the no-information rate (i.e. proportion of data belonging to the largest class). The models were not able to predict degree-of-satisfaction or overall satisfaction from footwear mechanical properties but could predict runner’s willingness to purchase with 68–75% accuracy. Midsole Gmax at the heel and forefoot appeared in the top five of variable importance rankings across both willingness-to-purchase models, suggesting its role as a major factor in purchase decisions. The negative regression coefficient for both heel and forefoot Gmax indicated that softer midsoles increase the likelihood of a shoe purchase. Future models to predict satisfaction may improve accuracy with the addition of more subject-specific parameters, such as running goals or foot proportions.
Although foot orthotics with different stiffness is widely used for the treatment of lower
extremity abnormalities and injuries, their effect on foot coordination and variability
is unclear. The purpose of the present study was to investigate the effect of different stiffness
of shoe orthosis on foot inter-joint coordination patterns and variability during the stance
phase of running. Fifteen healthy active men volunteered to participate in this study.
Coordination pattern and variability were calculated from kinematics raw data using a
Continuous Relative Phase method while running with different stiffness insoles inserted
in a sandal. A repeated measure of the ANOVA test was performed to test the hypothesis
(P<0.05). a part of the results showed that running with hard, soft, and semi-hard increased
about %95, %179, and %220 of continued relative phase inversion: eversion of the ankle
and tarsometatarsal joint in first 25% of stance phase compared to no insole condition
(P<0.001). Generally, the findings show that insole stiffness may affect lower extremity
mechanics by changing foot inter-joint coordination and variability. Thus, insole stiffness
should be considered when specialists use orthotic devices for treatment.
(1) Background: The objective of this study was to determine physical and biomechanical changes in age groups upon running. (2) Method: 75 male adults (20–80s) participated in the study. Bone mineral density and lower extremity joint strength were measured according to age-increase targeting. Based on age, correlations among running characteristics, impulse, impact force, maximum vertical ground reaction force, loading rate, lower extremity joint 3D range of motion, joint moment, and power upon running motion were calculated. (3) Result: Older runners tended to show lower bone mineral density, extremity maximum strength, stride time, and stride distance, with smaller RoM and joint power of ankle and knee joints in the sagittal plane, compared with younger subjects. However, there were no significant correlations between age and impact variables (i.e., impulse, impact force, peak GRF, and loading rate) during running. (4) Conclusion: Older runners tend to show weaker physical strength characteristics, such as bone mineral density and muscle strength and lower joint functionality of ankle and knee joints during running, compared with younger runners. Therefore, strengthening the lower extremity muscle and improving dynamic joint function, especially for ankle joints, can be helpful for injury prevention during running.
Purpose
Understanding users’ perceived usefulness and ease of use of technologies will influence their adoption and sustained use. The objectives of this study were to determine the metrics deemed important by runners for monitoring running-related injury (RRI) risk, and identify the barriers and facilitators to their use of injury focused wearable technologies.
Methods
A qualitative focus group study was undertaken. Nine semi-structured focus groups with male (n=13) and female (n=14) recreational runners took place. Focus groups were audio and video recorded, and transcribed verbatim. Transcripts were thematically analysed. A critical friend approach was taken to data coding, and multiple methods of trustworthiness were executed.
Results
Excessive loading and inadequate recovery were deemed the most important risk factors to monitor for RRI risk. Other important factors included training activities, injury status and history, and running technique. The location and attachment method of a wearable device and the design of a smartphone application were identified as important barriers and facilitators, with receiving useful injury-related feedback identified as a further facilitator.
Conclusions
Overtraining, training-related and individual- related risk factors are essential metrics that need to be monitored for RRI risk. RRI apps should include the metrics deemed important by runners, once there is supporting evidence- based research. The difficulty and/or ease of use of a device, and receiving useful feedback will influence the adoption of injury focused running technologies. There is a clear willingness from recreational runners to adopt injury focused wearable technologies whilst running.
To determine the influence of midsole hardness on ground reaction force (GRF) features during badminton scissor jump takeoff and landing and the interactive effect of midsole hardness with playing and nonplaying limbs, data were collected from badminton athletes who performed scissor jumps while wearing shoes with two levels of midsole hardness. Temporal-spatial and GRF variables were calculated. Measurements of the soft and hard midsole conditions for playing versus non-playing sides were compared using two-way repeated measure analyses of variance. The playing and non-playing limbs showed different GRF features while performing scissor jump. During takeoff, no significant differences between the soft and hard midsole conditions were identified for the jump height in any of the GRF variables. During landing, the cushioning capacity might be affected by harder midsole indicated by higher vertical impact peak (p = 0.008). Meanwhile, the longer time-to-vertical impact peak (p = 0.007) and the lower loading rate of the vertical impact peak (p = 0.013) may be plausible indicators for cushioning. Current study indicated the playing-limb consistently showed dominance on both the propulsion and shock attenuation behaviours during scissor jump and that, for the footwear selection between 62C and 68C midsoles, expectation would be more on effects on landing characteristics than on propulsion performance.
Background
Kinesio Taping is frequently used in the management of lower limb injuries, and has been shown to improve pain, function, and running performance. However, little is known about the effects of Kinesio Taping on running biomechanics, muscle activity, and perceived benefits.
Research question
This study aimed to explore the immediate effects of Kinesio Taping on lower limb kinematics, joint moments, and muscle activity, as well as perceived comfort, knee joint stability, and running performance in healthy runners.
Methods
Twenty healthy participants ran at a self-selected pace along a 20-metre runway under three conditions; no tape (NT), Kinesio Tape with tension (KTT), and Kinesio tape without tension (KTNT). Comparisons of peak hip, knee angles and moments, and EMG were analysed during the stance phase of running.
Results
KTT exhibited significant increases in peak hip flexion, peak hip abduction and hip external rotation compared to NT. Moreover, the KTT condition showed a trend towards a decrease in peak hip internal rotation and adduction angle compared to the NT condition. EMG results showed that Tensor Fascia Latae activity decreased with KTT compared with NT, and Gluteus Maximus activity reduced with KTNT when compared with NT. Ten of the 20 participants indicated important improvements in the comfort score, six participants in the knee stability score, and seven participants in the running performance score when using KTT.
Significance
These results suggest that changes in running biomechanics previously associated with ITBS can be improved with the application of kinesio tape, with the greatest effect seen with the application of kinesio tape with tension. Perceived improvements were seen in comfort, stability and running performance, however these benefits were only seen in half the participants. Further work is required to explore the biomechanical effects and perceived benefits in different patient groups.
The purpose of this study was to clarify the characteristics of toe trajectory when stepping over an obstacle in the dark and the effect of light information．In this study, time series data of toe trajectory of leading foot in sagittal plane (antero-posterior direction and vertical direction) were measured from eight young adults while they stepped over an obstacle under two illuminations (Blight and Dark) and three light information by phosphorescence (with the phosphorescence materials applied to the overall and partial and without the phosphorescence materials) conditions．Principal component analysis has been applied on the 240 x 202 input matrix constructed from participant’s time-normalized toe trajectory data． Two-way (illumination conditions by obstacles) multivariate analysis of variance on the principal component scores of extracted principal component vectors (PCV) revealed the effect of significant illumination condition on PCV1(p<0.05), 3(p<0.001) and 6(p<0.05)．There were no effects of light information by phosphorescence and the interaction of illumination and light information．Reconstructed toe trajectory from PCVs indicate that participants tend to take off their toe father away from the obstacle, land their heel closer to the obstacle, and lift their toe higher in the dark condition．We further analyzed these discrete parameters statistically, and found significant differences between blight and dark conditions．Also, we analyzed take off distance, heel contact distance and toe clearance．These results were similar to those of the PCA．In conclusion, the characteristics of toe trajectories when stepping over an obstacle were different in dark and light conditions, and no effect of light information on toe trajectories was found in dark conditions．
This study was aimed to understand the effect of age and sex on kinematic and kinetic features during walking. Gait data of 223 healthy adults aged 20 to 75 were obtained from AIST Gait Database. Principal component analysis was performed on the time-normalized joint angle and moment data of one gait cycle computed from 8 joints of whole body and pelvis-laboratory angle. Two-way (age by sex) analyses of variance were conducted on the principal component scores of principal component vectors, each of which explained more than 1% of the variance. The results showed that the 1st and 5th principal components were affected by sex, while the 3rd, 7th and 19th principal components were affected by age. The results of the post-hoc analyses revealed that 7th principal component represents the characteristic that changes uniformly with age, 3rd principal component represents the characteristic that changes from young to middle, and 19th principal component represents the characteristic that changes from middle to elderly, respectively. Furthermore, the kinematic and kinetic features associated with these principal components were reconstructed, and it was found that the anterior-posterior range of motion of the upper limb decreases and the peak values of the angles and moments of the hip and ankle joints at the 50-60% range of gait cycle decrease from young to middle, the gap between the timing of the upper and lower limb movements increases from middle to elderly.
Many unilateral total knee replacement (TKR) patients will need a contralateral TKR. Differences in knee joint biomechanics between bilateral patients and unilateral patients are not well established. The purpose of this study was to examine knee joint differences in level walking between bilateral and unilateral patients, and asymptomatic controls, using principal component analysis. Knee joints of 1st replaced limbs of 15 bilateral patients (69.40±5.04 years), 15 replaced limbs of unilateral patients (66.47±6.15 years), and 15 asymptomatic controls (63.53±9.50 years) were analyzed during level walking. Principal component analysis examined knee joint sagittal- and frontal-plane kinematics and moments, and vertical GRF. A one-way analysis of variance analyzed differences between principal component scores of each group. TKR patients exhibited more flexed and abducted knees throughout stance, decreased sagittal knee range of motion (ROM), increased early-stance adduction ROM, decreased loading-response knee extension and push-off knee flexion moments, decreased loading-response and push-off peak knee abduction moment (KAbM), increased KAbM at midstance, increased midstance vertical ground reaction force (GRF), and decreased loading-response and push-off vertical GRF. Additionally, bilateral patients exhibited reduced sagittal knee ROM, increased adduction ROM, decreased sagittal knee moments throughout stance, decreased KAbM throughout stance, an earlier loading-response peak vertical GRF, and a decreased push-off vertical GRF, compared to unilateral patients. TKR patients, especially bilateral patients had stiff knee motion in the sagittal-plane, increased frontal-plane joint laxity, and a quadriceps avoidance gait.
Background
Various types of footwear fixation can dramatically alter gait characteristics, and could potentially contribute to an increased risk of falls in the elderly. However, no studies have been conducted to analyze the effects of footwear fixation on joint angle variabilities, particularly during the entire gait cycle.
Research question
Does the fixation of footwear significantly affect the lower limb joint angle variabilities during the gait cycle?
Methods
Principal component analysis (PCA) was conducted on 20 healthy adults using 3D spatio-temporal data of the pelvis and lower limb joint angle that were collected during the entire gait cycle with the footwear in various conditions (well-fixated footwear, less-fixated footwear, slippers, and bare feet). Kinematic waveforms were reconstructed from the PCA data, which were used to determine the distinct differences in joint angle variabilities between footwear conditions.
Results
The results showed large variability in the knee- and ankle-joint angles on the sagittal plane when walking in the loose condition (less-fixated footwear, slippers, and bare feet) compared with those in the well-fixated footwear condition.
Significance
These results demonstrate the effect of footwear fixation on the joint angle variabilities of the elderly while walking. The increase in the knee- and ankle-joint angle variabilities when walking with less-fixated footwear could be a risk factor for falls.
The aim of this study was to investigate gender-specific influences of different symmetric and asymmetric occlusion conditions on postural control during standing and walking.
The study involved 59 healthy adult volunteers (41 f/19 m) aged between 22 and 53 years (30.2 ± 6.3 years). Postural control measurements were carried out using a pressure plate by measuring plantar pressure distribution during standing and walking test conditions. Seven different occlusion conditions were tested. Prior to a MANOVA model analysis, the relationship between the two test conditions were checked using a factor analysis with a varying number of factors (between 2 and 10).
The plantar pressure distributions during walking and standing are independent test conditions. The coefficient of variance across all variables between the conditions and genders was not significant: t(46) = 1.51 (p = 0.13). No statement can be made whether, or not, the influence of gender is greater than the influence of the conditions.
Healthy male and female test subjects did not show any difference between seven occlusion conditions on the plantar pressure distribution while standing or walking. No differences between the genders were found for any of the investigated variables. In contrast to custom-made occlusion splints, simple cotton rolls appear not to influence the neuromuscular system in a systematic manner.
This paper presents an application of functional principal component analysis (FPCA) to describe the inter-subject variability
of multiple waveforms. This technique was applied to the study of sit-to-stand movement in two groups of people, osteoarthritic
patients and healthy subjects. Although STS movement has not been extensively applied to the study of knee osteoarthritis,
it can provide relevant information about the effect of osteoarthritis on knee joint function. Two waveforms, knee flexion
angle and flexion moment, were analysed simultaneously. Instead of using the common multivariate approach we used the functional
one, which allows working with continuous functions with neither discretization nor time-scale normalization. The results
show that time-scale normalization can alter the FPCA solution. Furthermore, FPCA presents better discriminatory power compared
with the classical multivariate approach. This technique can, therefore, be applied as a functional assessment tool, allowing
the identification of relevant variables to discriminate heterogeneous groups such as healthy and pathological subjects.
Recent observations of a bicyclist riding through town and on a treadmill show that the rider uses the upper body very little when performing normal maneuvers and that the bicyclist may, in fact, primarily use steering input for control. The observations also revealed that other motions such as lateral movement of the knees were used in low speed stabilization. In order to validate the hypothesis that there is little upper body motion during casual cycling, an in-depth motion capture analysis was performed on the bicycle and rider system.
We used motion capture technology to record the motion of three similar young adult male riders riding two different city bicycles on a treadmill. Each rider rode each bicycle while performing stability trials at speeds ranging from 2 km/h to 30 km/h: stabilizing while pedaling normally, stabilizing without pedaling, line tracking while pedaling, and stabilizing with no-hands. These tasks were chosen with the intent of examining differences in the kinematics at various speeds, the effects of pedaling on the system, upper body control motions and the differences in tracking and stabilization.
Principal component analysis was used to transform the data into a manageable set organized by the variance associated with the principal components. In this paper, these principal components were used to characterize various distinct kinematic motions that occur during stabilization with and without pedaling. These motions were grouped on the basis of correlation and conclusions were drawn about which motions are candidates for stabilization-related control actions.
There are evidences to suggest that wearing footwear constrains the natural barefoot motion during locomotion. Unlike prior studies that deduced foot motions from shoe sole displacement parameters, the aim of this study was to examine the effect of footwear motion on forefoot to rearfoot relative motion during walking and running. The use of a multi-segment foot model allowed accurate both shoe sole and foot motions (barefoot and shod) to be quantified. Two pairs of identical sandals with different midsole hardness were used. Ten healthy male subjects walked and ran in each of the shod condition. The results showed that for barefoot locomotion there was more eversion of the forefoot and it occurred faster than for shod locomotion. In this later condition, the range of eversion was reduced by 20% and the rate of eversion in late stance by 60% in comparison to the barefoot condition. The sole constrained both the torsional (eversion/inversion) and adduction range of motion of the foot. Interestingly, during the push-off phase of barefoot locomotion the rate and direction of forefoot torsion varied between individuals. However, most subjects displayed a forefoot inversion direction of motion while shod. Therefore, this experiment showed that the shoes not only restricted the natural motion of the barefoot but also appeared to impose a specific foot motion pattern on individuals during the push-off phase. These findings have implications for the matching of footwear design characteristics to individual natural foot function.
Gender differences in kinematics during running have been speculated to be a contributing factor to the lower extremity injury rate disparity between men and women. Specifically, increased non-sagittal motion of the pelvis and hip has been implicated; however it is not known if this difference exists under a variety of locomotion conditions. The purpose of this study was to characterize gender differences in gait kinematics and muscle activities as a function of speed and surface incline and to determine if lower extremity anthropometrics contribute to these differences.
Whole body kinematics of 34 healthy volunteers were recorded along with electromyography of muscles on the right lower limb while each subject walked at 1.2, 1.5, and 1.8m/s and ran at 1.8, 2.7, and 3.6m/s with surface inclinations of 0%, 10%, and 15% grade. Joint angles and muscle activities were compared between genders across each speed-incline condition. Pelvis and lower extremity segment lengths were also measured and compared.
Females displayed greater peak hip internal rotation and adduction, as well as gluteus maximus activity for all conditions. Significant interactions (speed-gender, incline-gender) were present for the gluteus medius and vastus lateralis. Hip adduction during walking was moderately correlated to the ratio of bi-trochanteric width to leg length.
Our findings indicate females display greater non-sagittal motion. Future studies are needed to better define the relationship of these differences to injury risk.
Biological motion contains information about the identity of an agent as well as about his or her actions, intentions, and emotions. The human visual system is highly sensitive to biological motion and capable of extracting socially relevant information from it. Here we investigate the question of how such information is encoded in biological motion patterns and how such information can be retrieved. A framework is developed that transforms biological motion into a representation allowing for analysis using linear methods from statistics and pattern recognition. Using gender classification as an example, simple classifiers are constructed and compared to psychophysical data from human observers. The analysis reveals that the dynamic part of the motion contains more information about gender than motion-mediated structural cues. The proposed framework can be used not only for analysis of biological motion but also to synthesize new motion patterns. A simple motion modeler is presented that can be used to visualize and exaggerate the differences in male and female walking patterns.
Objective:
To explain and underscore the use of principal component analysis in clinical biomechanics as an expedient, unbiased means for reducing high-dimensional data sets to a small number of modes or structures, as well as for teasing apart structural (invariant) and variable components in such data sets.
Design:
The method is explained formally and then applied to both simulated and real (kinematic and electromyographic) data for didactical purposes, thus illustrating possible applications (and pitfalls) in the study of coordinated movement.
Background:
In the sciences at large, principal component analysis is a well-known method to remove redundant information in multidimensional data sets by means of mode reduction. At present, principal component analysis is starting to penetrate the fundamental and clinical study of human movement, which amplifies the need for an accessible explanation of the method and its possibilities and limitations. Besides mode reduction, we discuss principal component analysis in its capacity as a data-driven filter, allowing for a separation of invariant and variant properties of coordination, which, arguably, is essential in studies of motor variability.
Methods:
Principal component analysis is applied to kinematic and electromyographic time series obtained during treadmill walking by healthy humans.
Results:
Common signal structures or modes are identified in the time series that turn out to be readily interpretable. In addition, the identified coherent modes are eliminated from the data, leaving a filtered, residual pattern from which useful information may be gleaned regarding motor variability.
Conclusions:
Principal component analysis allows for the detection of modes (information reduction) in both kinematic and electromyographic data sets, as well as for the separation of invariant structure and variance in those data sets.
Relevance:
Principal component analysis can be successfully applied to movement data, both as feature extractor and as data-driven filter. Its potential for the (clinical) study of human movement sciences (e.g., diagnostics and evaluation of interventions) is evident but still largely untapped.
Running shoes are designed to accommodate various arch types to reduce the risk of lower extremity injuries sustained during running. Yet little is known about the biomechanical changes of running in the recommended footwear that may allow for a reduction in injuries.
To evaluate the effects of motion control and cushion trainer shoes on running mechanics in low- and high-arched runners.
Controlled laboratory study.
Twenty high-arched and 20 low-arched recreational runners (>10 miles per week) were recruited for the study. Three-dimensional kinematic and kinetics were collected as subjects ran at 3.5 ms(-1) +/- 5% along a 25-m runway. The motion control shoe evaluated was the New Balance 1122, and the cushioning shoe evaluated was the New Balance 1022. Repeated-measures analyses of variance were used to determine if low- and high-arched runners responded differently to motion control and cushion trainer shoes.
A significant interaction was observed in the instantaneous loading rate such that the low-arched runners had a lower instantaneous loading rate in the motion control condition, and the high-arched runners had a lower instantaneous loading rate in the cushion trainer condition. Significant main effects for shoe were observed for peak positive tibial acceleration, peak-to-peak tibial acceleration, mean loading rate, peak eversion, and eversion excursion.
These results suggest that motion control shoes control rearfoot motion better than do cushion trainer shoes. In addition, cushion trainer shoes attenuate shock better than motion control shoes do. However, with the exception of instantaneous loading rate, these benefits do not differ between arch type.
Running footwear recommendations should be based on an individual's running mechanics. If a mechanical analysis is not available, footwear recommendations can be based empirically on the individual's arch type.
Introduction. The biomechanical knowledge for developing running shoe cushioning guidelines is scarce. This study tested whether changes in midsole hardness, gender and age affect the lower-extremity pre- and post-heel strike muscle activity during heel-toe running. Methods. Surface electromyography (EMG) of the gastrocnemius medialis (GM), biceps femoris (BF) and vastus medialis (VM) was analysed for 54 male and female runners aged 10–75. Participants ran at 12 ± 0.6 km/h on a 30-m long runway with Soft (Asker C-40), Medium (Asker C-52) and Hard (Asker C-65) midsoles. EMG signals were resolved into time-frequency space using wavelet analysis. EMG intensities were extracted from the wavelet transformed signals to quantify frequency and time domain differences. The total energies for the pre- and post-heel strike EMG signals were calculated. Results. Similar muscle patterns and no frequency or time differences were found between the three midsole conditions. Compared to women, male runners had similar or decreased relative EMG intensity at lower frequencies, but greater intensities at higher frequencies for all three muscles. Male runners exhibited less pre- and more post-heel strike BF activity. Older runners had less GM and BF intensities at low frequencies, but greater intensities for higher frequencies. The differences were smaller for the VM and the trend was reversed. The VM pre-heel strike contribution increased with age. Kids showed less pre- versus post-heel strike BF activation while all other groups showed the opposite. Conclusions. The tested midsole hardness changes did not affect lower extremity muscle activity for the general population of runners, but greater hardness variations and/or other construction manipulations might. Should that be the case, those design modifications should take into account functional differences with gender and age.
Setting of the learning problem consistency of learning processes bounds on the rate of convergence of learning processes controlling the generalization ability of learning processes constructing learning algorithms what is important in learning theory?.
pAnimate motion contains not only information about the actions of a person but also about his or her identity, intentions and emotions. We can recognize a good friend by the way he or she moves and we can attribute age, gender and other characteristics to an unfamiliar person. How is such information encoded in visual motion data and how can it be retrieved by the visual system? We present an algorithm that transforms visual motion data such that they can be successfully approached with linear methods from statistics and pattern recognition. The transformation is based on a linear decomposition of postural data into a few components that change with sinusoidal temporal patterns. The components repeat consistently across subjects such that linear combinations of existing motion data result in smooth, meaningful interpolations. Examples are presented how this model can be used to discriminate between different types of motion (here: walking vs. running) and how it can be used to classify instances of the same type of motion (e.g. walking) in terms of characteristics of the actor (here: gender classification). Since the transformation is reversible the model can also be used for synthesis and modeling of animate motion. Therefore, it serves not only as a model for biological information processing but has also implications for both computer vision and computer graphics./p
Ground reaction forces are often used as a primary descriptive component in the analysis of the support phase of running. The purpose of this study was to investigate the changes in ground reaction force parameters during the support phase of the running stride at different running speeds. Ten skilled distance runners, who ran with a heel-toe football pattern at all running speeds, served as subjects. The experimental set-up consisted of a Kistler force platform interfaced to a Tektronix 4051 Graphics Calculator. Each subject performed 10 successful trials at each of 4 running speeds ranging from a sprint pace (7m/s) to a jogging pace (4m/s). Running speed was monitored by a photoelectric timing system. Data processing consisted of the evaluation of 19 descriptive variables of the relative ground reaction force-time curves for each of the 4 10-trial conditions. Ten vertical, 5 antero-posterior and 4 medio-lateral variables were used in the analysis. The relative force-time curves were generated using a cubic spline technique which transformed the absolute time events into 200 equally spaced data points to assist in making between speed comparisons. Separate multivariate analyses of variance with planned comparisons were carried out on each of the 3 relative data sets. Statistically significant differences were found for the relative ground reaction force parameters at the different running speeds (p < 0.01). While events in the ground reaction force curves occurred at the same relative time, magnitude changes in the forces and relative impulses as a result of the changes in running speed were observed. The results suggested that considerable care must be taken in comparing ground reaction force data unless the data were collected at comparable running speeds.
Changes in gait kinematics have often been analyzed using pattern recognition methods such as principal component analysis (PCA). It is usually just the first few principal components that are analyzed, because they describe the main variability within a dataset and thus represent the main movement patterns. However, while subtle changes in gait pattern (for instance, due to different footwear) may not change main movement patterns, they may affect movements represented by higher principal components. This study was designed to test two hypotheses: (1) speed and gender differences can be observed in the first principal components, and (2) small interventions such as changing footwear change the gait characteristics of higher principal components. Kinematic changes due to different running conditions (speed - 3.1m/s and 4.9 m/s, gender, and footwear - control shoe and adidas MicroBounce shoe) were investigated by applying PCA and support vector machine (SVM) to a full-body reflective marker setup. Differences in speed changed the basic movement pattern, as was reflected by a change in the time-dependent coefficient derived from the first principal. Gender was differentiated by using the time-dependent coefficient derived from intermediate principal components. (Intermediate principal components are characterized by limb rotations of the thigh and shank.) Different shoe conditions were identified in higher principal components. This study showed that different interventions can be analyzed using a full-body kinematic approach. Within the well-defined vector space spanned by the data of all subjects, higher principal components should also be considered because these components show the differences that result from small interventions such as footwear changes.
The effects of current athletic footwear on lower extremity biomechanics are unknown. The aim of this study was to examine the changes, if any, that occur in peak lower extremity net joint moments while walking in industry recommended athletic footwear. Sixty-eight healthy young adults underwent kinetic evaluation of lower extremity extrinsic joint moments while walking barefoot and while walking in current standard athletic footwear matched to the foot mechanics of each subject while controlling for speed. A secondary analysis was performed comparing peak knee joint extrinsic moments during barefoot walking to those while walking in three different standard footwear types: stability, motion control, and cushion. 3-D motion capture data were collected in synchrony with ground reaction force data collected from an instrumented treadmill. The shod condition was associated with a 9.7% increase in the first peak knee varus moment, and increases in the hip flexion and extension moments. These increases may be largely related to a 6.5% increase in stride length with shoes associated with increases in the ground reaction forces in all three axes. The changes from barefoot walking observed in the peak knee joint moments were similar when subjects walked in all three footwear types. It is unclear to what extent these increased joint moments may be clinically relevant, or potentially adverse. Nonetheless, these differences should be considered in the recommendation as well as the design of footwear in the future.
The objective of this study was to compare the three-dimensional lower extremity running kinematics of young adult runners and elderly runners. Seventeen elderly adults (age 67-73 years) and 17 young adults (age 26-36 years) ran at 3.1 m x s(-1) on a treadmill while the movements of the lower extremity during the stance phase were recorded at 120 Hz using three-dimensional video. The three-dimensional kinematics of the lower limb segments and of the ankle and knee joints were determined, and selected variables were calculated to describe the movement. Our results suggest that elderly runners have a different movement pattern of the lower extremity from that of young adults during the stance phase of running. Compared with the young adults, the elderly runners had a substantial decrease in stride length (1.97 vs. 2.23 m; P = 0.01), an increase in stride frequency (1.58 vs. 1.37 Hz; P = 0.002), less knee flexion/extension range of motion (26 vs. 33 degrees ; P = 0.002), less tibial internal/external rotation range of motion (9 vs. 12 degrees ; P < 0.001), larger external rotation angle of the foot segment (toe-out angle) at the heel strike (-5.8 vs. -1.0 degrees ; P = 0.009), and greater asynchronies between the ankle and knee movements during running. These results may help to explain why elderly individuals could be more susceptible to running-related injuries.
One prominent pattern emerging from a review of the literature on sport shoes and biomechanics is the observation that many effects are the indirect result of shoe-induced adjustments in movement, i.e. a particular shoe characteristic elicits a kinematic adaptation which in turn has secondary consequences on kinetics and on injury and performance. For example, in addition to its variable effects on peak forces, cushioning system design has been shown to alter electromyographic patterns and to affect knee flexion during foot strike and affect indirectly the economy of running. Mediolateral stability as measured by rearfoot kinematics is strongly influenced by shoe design features such as heel lift, and sole hardness and geometry. The frictional properties of the shoe and surface interface have also been shown to affect kinematics in a way that in turn affects the recorded frictional forces themselves. Such kinematically mediated responses are the most provocative result of studies of the biomechanical effects of footwear. It is becoming apparent that the shoe can be a powerful tool for manipulating human movement. The abundance of shoe design possibilities coupled with the body's tendency to adjust in predictable ways to shoe mechanical characteristics have given us a new way to manipulate human kinematics and kinetics, as well as a convenient model for studying biomechanical adaptation.
It is not known whether changes in the biomechanics of elderly gait are related to aging per se, or to reduced walking speed in this population. The goals of the present study were to identify specific biomechanical changes, independent of speed, that might impair gait performance in healthy older people by identifying age-associated changes in the biomechanics of gait, and to determine which of these changes persist at increased walking speed.
Stereophotogrammetric and force platform data were collected. Differences in peak joint motion (kinematic) and joint moment and power (kinetic) values between healthy young and elderly subjects at comfortable and increased walking speed were measured.
A gait laboratory.
Thirty-one healthy elderly (age 65 to 84 years) and 31 healthy young adult subjects (age 18 to 36 years), all without known neurologic, musculoskeletal, cardiac, or pulmonary problems.
All major peak kinematic and kinetic variables during the gait cycle.
Several kinematic and kinetic differences between young and elderly adults were found that did not persist when walking speed was increased. Differences that persisted at both comfortable and fast walking speeds were reduced peak hip extension, increased anterior pelvic tilt, and reduced ankle plantarflexion and ankle power generation.
Gait performance in the elderly may be limited by both subtle hip flexion contracture and ankle plantarflexor concentric weakness. Results of the current study should motivate future experimental trials of specific hip flexor stretching and ankle plantarflexor concentric strengthening exercises to preserve and potentially improve walking performance in the elderly.
Little is known about the effects of severe repetitive loading on articular cartilage chondrocytes, even though epidemiological studies associate this type of loading with osteoarthritis. We hypothesize that repetitive loading can kill cartilage chondrocytes in a dose-related manner.
Large cartilage-on-bone specimens were cut from the patella groove of bovine knees obtained directly from a slaughterhouse. Cartilage was loaded using a flat impermeable indenter in such a manner that the loaded region was supported naturally by surrounding cartilage and subchondral bone. Specimens received 3600 cycles of compressive loading at 1 Hz, with the peak load lying in the range 1-70% of the force required to damage cartilage in a single loading cycle (35 MPa). Cell viability was assessed in thick sections of loaded and control cartilage using a paravital staining method: fluorescein diacetate stained live cells green, and propidium iodide stained dead cells red. The assay was validated on cartilage which had been subjected to repeated freeze-thaw cycles to kill the chondrocytes.
Paravital staining revealed 100% cell death after one freeze-thaw cycle at -196 degrees C and three cycles at -20 degrees C. Baseline chondrocyte viability was 80% in unloaded cartilage, and viability decreased when applied compressive loading exceeded 6 MPa. Above this threshold, cell viability was inversely proportional to applied stress. When gross damage to the cartilage surface first became evident, above 14 MPa, 40% of cells remained viable. Load-induced chondrocyte death was greatest in the surface zone, and extended beyond the loaded area. Electron micrographs indicated that some cells were dying by apoptosis.
Some chondrocytes are much more vulnerable to repetitive mechanical loading than others, suggesting that vigorous activity may lead to cell death in articular cartilage.
Repetitive impacts encountered during locomotion may be modified by footwear and/or surface. Changes in kinematics may occur either as a direct response to altered mechanical conditions or over time as active adaptations.
: To investigate how midsole hardness, surface stiffness, and running duration influence running kinematics.
In the first of two experiments, 12 males ran at metabolic steady state under six conditions; combinations of midsole hardness (40 Shore A, 70 Shore A), and surface stiffness (100 kN x m, 200 kN x m, and 350 kN x m). In the second experiment, 10 males ran for 30 min on a 12% downhill grade. In both experiments, subjects ran at 3.4 m x s on a treadmill while 2-D hip, knee, and ankle kinematics were determined using high-speed videography (200 Hz). Oxygen cost and heart rate data were also collected. Kinematic adaptations to midsole, surface, and running time were studied.
Stance time, stride cycle time, and maximal knee flexion were invariant across conditions in each experiment. Increased midsole hardness resulted in greater peak ankle dorsiflexion velocity (P = 0.0005). Increased surface stiffness resulted in decreased hip and knee flexion at contact, reduced maximal hip flexion, and increased peak angular velocities of the hip, knee, and ankle. Over time, hip flexion at contact decreased, plantarflexion at toe-off increased, and peak dorsiflexion and plantarflexion velocity increased.
Lower-extremity kinematics adapted to increased midsole hardness, surface stiffness, and running duration. Changes in limb posture at impact were interpreted as active adaptations that compensate for passive mechanical effects. The adaptations appeared to have the goal of minimizing metabolic cost at the expense of increased exposure to impact shock.
This paper investigated application of a machine learning approach (Support vector machine, SVM) for the automatic recognition of gait changes due to ageing using three types of gait measures: basic temporal/spatial, kinetic and kinematic. The gaits of 12 young and 12 elderly participants were recorded and analysed using a synchronized PEAK motion analysis system and a force platform during normal walking. Altogether, 24 gait features describing the three types of gait characteristics were extracted for developing gait recognition models and later testing of generalization performance. Test results indicated an overall accuracy of 91.7% by the SVM in its capacity to distinguish the two gait patterns. The classification ability of the SVM was found to be unaffected across six kernel functions (linear, polynomial, radial basis, exponential radial basis, multi-layer perceptron and spline). Gait recognition rate improved when features were selected from different gait data type. A feature selection algorithm demonstrated that as little as three gait features, one selected from each data type, could effectively distinguish the age groups with 100% accuracy. These results demonstrate considerable potential in applying SVMs in gait classification for many applications.
To compare differences in hip and knee kinematics and kinetics in male and female recreational runners.
Gait analysis of 20 men and 20 women recreational runners.
Female runners are reported to be more likely to sustain certain lower extremity injuries compared to their male counterparts. This has been attributed, in part, to differences in their structure and it has been postulated that these structural differences may lead to differences in running mechanics. It was hypothesized that females would exhibit greater peak hip adduction, hip internal rotation, knee abduction and decreased knee internal rotation compared to their male counterparts. It was also hypothesized that females would exhibit greater hip and knee negative work in the frontal and transverse planes compared to males.
Comparisons of hip and knee three-dimentional joint angles and negative work during the stance phase of running gait were made between genders.
Female recreational runners demonstrated a significantly greater peak hip adduction, hip internal rotation and knee abduction angle compared to men. Female recreational runners also demonstrated significantly greater hip frontal and transverse plane negative work compared to male recreational runners.
Female recreational runners exhibit significantly different lower extremity mechanics in the frontal and transverse planes at the hip and knee during running compared to male recreational runners.
Understanding the differences in running mechanics between male and female runners may lend insight into the etiology of different injury patterns seen between genders. In addition, these results suggest that care should be taken to account for gender when studying groups of male and female recreational runners.
The aims of this study were to investigate whether older adults modify their walking mechanics to compensate for the degeneration in their muscle-tendon units (MTUs), and to examine whether running has a beneficial effect on walking mechanics in younger and older adults. The investigation was conducted on 30 older and 19 younger adults divided into two subgroups: runners versus non-active. In previous studies we documented that older adults had lower leg-extensor muscle strength and tendon stiffness compared to younger. Runners and non-active subjects had similar MTU capacities. In this study we analysed walking kinematics and kinetics (1.6 m/s) from the same subjects. Older adults showed a lower gear ratio (ratio between moment arm of the ground reaction force and moment arm of muscle) at the triceps surae MTU during the initial and mid part of ground contact, lower average horizontal forces and lower average ankle joint moment during ground contact compared to younger (p<0.05). Compared to non-active subjects, runners had a lower gear ratio at the quadriceps femoris MTU during the initial and final part of ground contact, lower average horizontal forces and lower maximal knee joint moment during ground contact independent of the subject's age (p<0.05). We concluded that the older adults modify the gearing at the ankle joint in order to adjust the task effort to the reduced triceps surae muscle strength. It appears, further, that runners walked more effectively from a mechanical standpoint compared to non-active subjects, which suggests that runners may be able to transfer motor adaptation from running to walking even in old age.
The objectives of this study were to characterize the active and passive contributions to joint kinetics during walking in healthy young and older adults, and assess whether isokinetic ankle strength is associated with ankle power output during walking. Twenty healthy young (18-35 years) and 20 healthy older (65-85 years) adults participated in this study. We measured subject-specific passive-elastic joint moment-angle relationships in the lower extremity and tested maximum isokinetic ankle strength at 30 deg/s. Passive moment-angle relationships were used to estimate active and passive joint moment, power, and work quantities during walking at 80%, 100% and 120% of preferred walking speed. There were no significant differences in walking speed, step length, or cadence between the older and young adults. However, the older adults produced significantly more net positive work at the hip but less net positive work at the ankle at all walking speeds. Passive contributions to hip and ankle work did not significantly differ between groups, inferring that the older adults generated the additional hip work actively. Maximum isokinetic ankle strength was significantly less in the older adults, and correlated with peak positive plantar-flexor power at both the preferred and fast walking speeds. The results of this study suggest that age-related shifts in joint kinetics do not arise as a result of increased passive hip joint stiffness, but seem to be reflected in plantar-flexor weakness.
We present a new learning algorithm for pattern recognition inspired by a recent upper bound on leave--one--out error [ Jaakkola and Haussler, 1999 ] proved for Support Vector Machines (SVMs) [ Vapnik, 1995; 1998 ] . The new approach directly minimizes the expression given by the bound in an attempt to minimize leave--one--out error. This gives a convex optimization problem which constructs a sparse linear classifier in feature space using the kernel technique. As such the algorithm possesses many of the same properties as SVMs. The main novelty of the algorithm is that apart from the choice of kernel, it is parameterless -- the selection of the number of training errors is inherent in the algorithm and not chosen by an extra free parameter as in SVMs. First experiments using the method on benchmark datasets from the UCI repository show results similar to SVMs which have been tuned to have the best choice of parameter. 1 Introduction Support Vector Machines (SVMs), motivated by minim...
The effect of running shoe design on shock attenuation
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Discrimina-tion of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics Rider motion identification during normal bicycling by means of principal component analysis
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The effect of running shoe design on shock attenuation
- Frederick