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Abstract

The degree to which standard laboratory gait assessments accurately reflect impact loading in an outdoor running environment is currently unknown. Purpose: To compare tibial shock between treadmill and road marathon conditions. Methods: 192 runners (Men/Women: 105/87, Age: 44.9±10.8 yrs) completed a treadmill gait assessment while wearing a tibial-mounted inertial measurement unit, several days before completing a marathon race. Participants ran at 90% of their projected race speed and 30-seconds of tibial shock data were collected. Participants then wore the sensors during the race and tibial shock was averaged over the 12, 23 and 40 km. One-way analysis of covariance and correlation coefficients were used to compare vertical/resultant tibial shock between treadmill and marathon conditions. Analyses were adjusted for differences in running speed between conditions. Results: A significant main effect of condition was found for mean vertical and resultant tibial shock (p<0.001). Early in the marathon (12km point), runners demonstrated higher mean tibial shock adjusted for speed compared with the treadmill data (vertical = +24.3% and resultant = +30.3%). Mean differences decreased across the course of the marathon. Vertical tibial shock at the 40th km of the race was similar to treadmill data, and resultant shock remained higher. Vertical and resultant tibial shock were significantly correlated between treadmill and the 12 km of the race (rs = 0.64-0.65, p<0.001), with only 40-42% of the variance in outdoor tibial shock explained by treadmill measures. Correlations for tibial shock showed minimal changes across stages of the marathon. Conclusions: These results demonstrate that measures of impact loading in an outdoor running environment are not fully captured on a treadmill.

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... The mean axial PTA observed in this study across all speeds was 7.7 g (mean running speed = 2.75 m/s), which is slightly lower than those reported by Johnson et al., who assessed axial PTA in 192 marathon runners during treadmill running at the preferred speed (8.9 g; mean running speed = 3.06 m/s) [34]. Our model prediction remained lower than Johnson et al. [34] even when adjusting for running speed (8.2 g). ...
... The mean axial PTA observed in this study across all speeds was 7.7 g (mean running speed = 2.75 m/s), which is slightly lower than those reported by Johnson et al., who assessed axial PTA in 192 marathon runners during treadmill running at the preferred speed (8.9 g; mean running speed = 3.06 m/s) [34]. Our model prediction remained lower than Johnson et al. [34] even when adjusting for running speed (8.2 g). Our lower axial PTA values may have been related to the different running populations involved. ...
... Our lower axial PTA values may have been related to the different running populations involved. Johnson et al. [34] selectively recruited marathon runners compared to our population, which ranged from recreational to competitive runners. Additionally, Johnson et al. had to interpolate axial PTA data due to exceeding the accelerometer's operating range (±16 g), which may have accounted for some differences. ...
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Measuring lower extremity impact acceleration is a common strategy to identify runners with increased injury risk. However, existing axial peak tibial acceleration (PTA) thresholds for determining high‐impact runners typically rely on small samples or fixed running speeds. This study aimed to describe the distribution of axial PTA among runners at their preferred running speed, determine an appropriate adjustment for investigating impact magnitude at different speeds, and compare biomechanics between runners classified by impact magnitude. A total of 171 runners ran on an instrumented treadmill at their preferred running speed during 3D motion capture. Axial PTA was collected at the distal tibia. The relationship between axial PTA and running speed was investigated using linear regression. Runners were categorized into impact sub‐groups, with high‐ and low‐impact runners identified if their axial PTA was ±1 standard deviation of the model predicted value. Differences in demographics, training, and running biomechanics between impact sub‐groups were compared. Mean axial PTA was 7.8 g across all running speeds. Axial PTA increased with running speed, with a 1.7 g increase for every 1.0 m/s increase. There were no differences in axial PTA between males and females (p = 0.214) and lower limbs (p = 0.312). High‐impact runners had higher vertical loading rates (p < 0.001) and greater ankle dorsiflexion at initial contact (p < 0.001) compared to low‐impact runners. No differences in age, body mass, height, or weekly running distances were observed across impact sub‐groups. This study proposes a method to identify the impact classification of runners based on their axial PTA for screening, monitoring, or gait retraining.
... Yet, they stated some differences among others in knee flexion and vertical loading. Johnson et al. [13] and Milner et al. [14] observed lower tibial shock values when running on a treadmill in contrast to running on surfaces outdoors, which may favor the former during early rehabilitation from an injury. This may be explained by a higher shock absorption of treadmills compared to other surfaces [15]. ...
... Vertical tibial acceleration (vPTA) is an established variable measurable using IMUs to analyze running biomechanics and, thus, lower limb loading for healthy subjects [16][17][18]. There are several studies using IMUs and focusing on the differences in tibial acceleration, comparing movements in the laboratory with movements in field conditions [13,14,19]. However, according to the authors' knowledge, there is only one investigation examining lower limb accelerations with ACLR subjects' IMUs during running, which was conducted in a laboratory [20]. ...
... The results in terms of higher tibial accelerations in the field conditions compared with the lab conditions are supported by the current literature [13,14,19]. As a concrete surface has stiffer material properties than a treadmill's surface, the downward-moving leg will be slowed down after initial contact in a shorter amount of time and will therefore cause a higher reactional momentum [15,41]. ...
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Anterior cruciate ligament reconstruction (ACLR) may affect movement even years after surgery. The purpose of this study was to determine possible interlimb asymmetries due to ACLR when running on a treadmill and in field conditions, with the aim of contributing to the establishment of objective movement assessment in real-world settings; moreover, we aimed to gain knowledge on recovered ACLR as a biomechanical risk factor. Eight subjects with a history of unilateral ACLR 5.4 ± 2.8 years after surgery and eight healthy subjects ran 1 km on a treadmill and 1 km on a concrete track. The ground contact time and triaxial peak tibial accelerations were recorded using inertial measurement units. Interlimb differences within subjects were tested and compared between conditions. There were no significant differences between limbs in the ACLR subjects or in healthy runners for any of the chosen parameters on both running surfaces. However, peak tibial accelerations were higher during field running (p-values < 0.01; Cohen’s d effect sizes > 0.8), independent of health status. To minimize limb loading due to higher impacts during field running, this should be considered when choosing a running surface, especially in rehabilitation or when running with a minor injury or health issues.
... Overuse injuries are associated with repetitive highforce landing impacts during running. High-impact load is directly related to musculoskeletal damage in animal models Johnson et al., 2020) and to lower-limb overuse injuries Johnson et al., 2020). By contrast, lower impact loads are associated with reduced overuse injuries in runners Milner et al., 2006;Shih et al., 2019;van der Worp et al., 2016). ...
... Overuse injuries are associated with repetitive highforce landing impacts during running. High-impact load is directly related to musculoskeletal damage in animal models Johnson et al., 2020) and to lower-limb overuse injuries Johnson et al., 2020). By contrast, lower impact loads are associated with reduced overuse injuries in runners Milner et al., 2006;Shih et al., 2019;van der Worp et al., 2016). ...
... Impact load has been extensively quantified using ground reaction force (GRF) in the vertical direction. Loading rate is characterized by the rate of increase in vertical GRF between initial contact with the ground and the first transient peak (Johnson et al., 2020). Specific measures include vertical instantaneous and average loading rates, abbreviated VILR and VALR, respectively. ...
... Running-induced fatigue may play a role on the ability to maintain impact loading, as stresses on the tibia have been shown to increase during a prolonged run (10). Findings regarding the effect of running-induced fatigue on impact loading are also inconsistent, with some studies finding increases (11,12), decreases (13), or no changes to PTA during a run (14,15). Factors that may explain the inconsistency in findings of previous studies include variations in running speed or running surface (13). ...
... Findings regarding the effect of running-induced fatigue on impact loading are also inconsistent, with some studies finding increases (11,12), decreases (13), or no changes to PTA during a run (14,15). Factors that may explain the inconsistency in findings of previous studies include variations in running speed or running surface (13). PTA is highly influenced by speed (16), and a reduction in speed throughout a prolonged run may explain these changes, which would be expected to decrease with slower speeds if all other factors are held constant. ...
... Despite this, the current protocol design allows the isolation of the effect of fatigue on PTA. Although treadmill and overground running is comparable (48), PTA is lower when measured in a laboratory rather than outdoor or in-field setting (13). Although this is unlikely to impact the change scores as the surface was held constant, the absolute values for PTA will be different to overground or in-field-based testing, and as such, comparisons between this field-based literature should be done with caution. ...
Article
Background: High impact loads have been linked with running injuries. Fatigue has been proposed to increase impact loads, but this relationship has not been rigorously examined, including the associated role of muscle strength, power, and endurance. Purpose: To investigate the effect of fatigue on impact loading in runners, and the role of muscle function in mediating changes in impact loading with fatigue. Methods: Twenty-eight trained endurance runners performed a fixed-intensity time to exhaustion test at 85% of V̇O2max. Tibial accelerations were measured using leg-mounted inertial measurement units (IMUs) and sampled every minute until volitional exhaustion. Tests of lower-limb muscle strength, power, and endurance included maximal isometric strength (soleus, knee extensors, knee flexors), single leg hop for distance, and the one leg rise test. Changes in peak axial tibial acceleration (PTA, g) were compared between time-points throughout the run (0, 25, 50, 75 and 100%). Associations between the change in PTA and lower limb muscle function tests were assessed (Spearman's rho [rs]). Results: Peak tibial acceleration increased over the duration of the fatiguing run. Compared to baseline (0%) (9.1 g SD 1.6), there was a significant increase at 75% (9.9 g SD 1.7., p = 0.001) and 100% (10.1 g SD 1.8, p < 0.001), with no change at 25% (9.6 g SD 1.6, p = 0.142) or 50% (9.7 g SD 1.7, p = 0.053). Relationships between change in peak tibial acceleration and muscle function tests were weak and not statistically significant (rs = -0.153 to 0.142, all p > 0.05). Conclusions: Peak axial tibial acceleration increased throughout a fixed-intensity run to exhaustion. The change in PTA was not related to performance in lower limb muscle function tests.
... A large majority (75%) of the articles studied fewer than 30 participants (median for the grand total: 17 healthy and 8 athletes post-injury), and as few as 22 studies with a sample size from 46 to 432 (median of these 22 studies: 80 athletes) accounted for half of the overall number of participants assessed ( Figure 6b). Eight of these 22 investigations tallied up a total of 770 runners of both genders [47,103,124,182,195,209,214,230], whilst 13 studies analysed 1639 male and 70 female players practicing team sports (i.e., basketball [71], American football [104,118,213,234], soccer [185,191], Australian football [160,202], baseball [94,178], and rugby [81,179]) (Figure 6c). These articles on team sports primarily generated the larger prevalence of male athletes in the overall sample analysed in our review. ...
... The comparison of outcomes of known importance for injury research between lab-and field-based conditions highlighted the importance of a research setting specific to the application, suggesting that certain lab constraints may not be appropriate to investigate field-based injuries (e.g., higher intensity of cutting tasks in real games compared to lab-based tests [218]; higher accelerations peaks in field-compared to lab-based running [87]). Findings support measuring tibial impact acceleration in a natural, outdoor environment [124] and, since fatigue may contribute to altering behaviour and variables with time, call for the development of thresholds associated with an increased likelihood of injuries that are specific to field-based conditions [87]. Other specificity concerns have been raised for the interpretation of research results; sex-specific running injuries require sex-specific monitoring to reduce injury risk [47], and differences in sports collisions require sport-specific tackling detection systems [142]. ...
... Many IrRL3 articles contributed to guideline finalisation, providing specific indications of how to assess and use data for monitoring and personalising feedback to prevent injuries or to guide rehabilitation. Running studies at the deployment level have typically focused on crucial factors for the assessment of loading capacity and joint stability, including the type of running (treadmill vs. real-word running [124]), running surface [192], and level of fatigue [74]. Baseline values have been obtained for ankle-specific biomechanical measures in runners, in relation to their chronic ankle instability history [157]. ...
Article
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Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features—such as research design, scope, experimental settings, and applied context—were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.
... Several of the included studies compared running quality between surfaces, and the findings underscore the need to observe runners in their actual running environment. More unstable surfaces lead to less regularity and greater variability during running [5,142], and the variance in outdoor data cannot be explained by indoor measures [31,95]. Moreover, it is likely that not all metrics differ between the running conditions [245]. ...
... For example, there was no difference in running power on a track compared to a treadmill [166]. Among the four studies that compared tibial acceleration between treadmill and outdoor running, the acceleration magnitude was either lower [241], greater [31,95], or not different [84,241] in outdoor conditions compared to on the treadmill, but in only one case did the outdoor conditions represent an uncontrolled running environment [95]. We suggest that rather than estimating what it is like to run outdoors, it would be helpful to use IMUs during actual training runs, over longer distances and on surfaces that represent real-world running. ...
... For example, there was no difference in running power on a track compared to a treadmill [166]. Among the four studies that compared tibial acceleration between treadmill and outdoor running, the acceleration magnitude was either lower [241], greater [31,95], or not different [84,241] in outdoor conditions compared to on the treadmill, but in only one case did the outdoor conditions represent an uncontrolled running environment [95]. We suggest that rather than estimating what it is like to run outdoors, it would be helpful to use IMUs during actual training runs, over longer distances and on surfaces that represent real-world running. ...
Article
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Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.
... This integrated approach, combining biomechanical data with physiological metrics like heart rate and session RPE, could improve injury risk stratification by accounting for the complex interplay between external and internal loads. With advancements in the development of wearables such as GPS smartwatches and shoe-mounted activity monitors (10), gait mechanics and training load can now be tracked in the field (21,44,47,51). While these have not been validated to measure all biomechanical variables, some variables can be accurately and reliably measured with wearables, such as cadence (1,29), ground contact time (29), stride length (29), and tibial acceleration (29). ...
... The rapid development of consumer-based wearables has provided the flexibility to assess gait mechanics in real-world conditions (21,44). As previously mentioned, while there may be limited biomechanical variables that have been validated in wearables (26), the same principles of faded feedback can be applied but the mode of application may vary. ...
Article
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The purpose of this clinical review is to provide an overview of gait retraining to be used by clinicians as part of a comprehensive treatment plan for managing injured runners. Running-related injuries (RRIs) are multifactorial and it is important to consider all contributors to RRIs, including biomechanics, before determining if gait retraining is appropriate for a patient. Wearable devices may enhance aspects of gait retraining by providing external feedback to modify running biomechanics in or outside the clinic.
... Sihyun Ryu [14] highlighted the significant influence of distal tibial accelerometers on predicting peak ground reaction force (GRF) and loading rate. Caleb D. Johnson [15] positioned an IMU device on the anteromedial aspect of the distal right tibia to monitor vertical and resultant tibial impacts, comparing the impacts during treadmill and overground running. When combined with machine learning approaches, these methods enable more accurate force estimation. ...
... A 15 Hz Butterworth low-pass filter was applied to the normalized biomechanical forces, and a 20 Hz Butterworth low-pass filter was applied to the insole sensor signals to reduce high-frequency noise and more accurately capture the main trends and features in the signals during movement. Each channel of the insole sensor signals was then normalized between 0 and 1 based on the maximum and minimum values, where x n represents the signal from the n-th channel, as shown in Equation (15). ...
Article
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Musculoskeletal injuries induced by high-intensity and repetitive physical activities represent one of the primary health concerns in the fields of public fitness and sports. Musculoskeletal injuries, often resulting from unscientific training practices, are particularly prevalent, with the tibia being especially vulnerable to fatigue-related damage. Current tibial load monitoring methods rely mainly on laboratory equipment and wearable devices, but datasets combining both sources are limited due to experimental complexities and signal synchronization challenges. Moreover, wearable-based algorithms often fail to capture deep signal features, hindering early detection and prevention of tibial fatigue injuries. In this study, we simultaneously collected data from laboratory equipment and wearable insole sensors during in-place running by volunteers, creating a dataset named WearLab-Leg. Based on this dataset, we developed a machine learning model integrating Temporal Convolutional Network (TCN) and Transformer modules to estimate vertical ground reaction force (vGRF) and tibia bone force (TBF) using insole pressure signals. Our model’s architecture effectively combines the advantages of local deep feature extraction and global modeling, and further introduces the Weight-MSELoss function to improve peak prediction performance. As a result, the model achieved a normalized root mean square error (NRMSE) of 7.33% for vGRF prediction and 10.64% for TBF prediction. Our dataset and proposed model offer a convenient solution for biomechanical monitoring in athletes and patients, providing reliable data and technical support for early warnings of fatigue-induced injuries.
... Additionally, there are a number of intrinsic (e.g. fatigue, muscle activation) and extrinsic (e.g., surface, footwear) factors that are known to affect measures of external forces, including TAs (Johnson et al., 2020a;Milner et al., 2020). Establishing whether peak TAs are related to early stance GRF metrics during walking with load carriage would provide an accessible measure of external loads acting on the lower extremities during operational activities. ...
... A data check ensured proper sensor orientation, with the positive direction pointing proximally, using a static trial. Resultant TAs were calculated as the root sum of squares of triaxial accelerations, with 1g subtracted from the resulting signal (Johnson et al., 2020a). Peak vertical and resultant TAs (VTA/RTA) were identified for each stride (Fig. 2C) (Johnson et al., 2020b;Ruder et al., 2019). ...
Article
Peak tibial accelerations (TAs) during running are strongly related to early stance vertical ground reaction forces (GRFs), which are associated with musculoskeletal injury. However, few studies have examined these correlations during walking, and none have evaluated them during walking with loads, a relevant activity for military personnel. Our purpose was to determine the relationships between GRFs and TAs in US Army trainees (n = 649) walking with loads. An inertial measurement unit was attached over their distal antero-medial tibia. Participants walked on an instrumented treadmill at 1.21-1.34 m/s, with a pack loaded with 18.1 kg, for a 3-min warm-up followed by a minimum of 14 strides of data collection. Simple linear regression models were calculated for peak vertical and resultant TAs with vertical and posterior GRF loading rates and peak forces. The strongest relationships were between vertical loading rates and peak vertical TA (R = 0.43-0.50), however the relationships were weaker than has been reported for unloaded walking and running (R > 0.7). All other relationships were trivial to small (R = 0.06-0.27). The weaker relationships for vertical GRFs and TAs may be due to methodological differences between studies, or differences in gait mechanics, such as a longer double-limb support phase in loaded vs. unloaded walking.
... A restoration algorithm has been proposed by Ruder et al. for clipped tibial acceleration signals [14] based on spline interpolation to reconstruct the missing peaks. This algorithm has been applied to another study which compared PTA between treadmill and real-world running [15]. While Ruder et al. [14] concluded that the algorithm was sufficient to reconstruct peaks accurately, the validation was limited to a narrow range of peaks from 15.0 to 15.9 g; the accuracy of the algorithm beyond 15.9 g is unknown. ...
... Compared to previous studies, the axial and resultant PTA values in the current study were on the high side for overground running [16]. Johnson et al. reported average axial and resultant PTA of 11.71 ± 3.66 g and 15.72 ± 4.99 g at the 12 km checkpoint of a marathon [15], while we found 14.30 ± 6.06 g and 20.13 ± 8.97 g, respectively. The higher values could be attributed to the running conditions set for this study. ...
Article
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Wireless accelerometers with various operating ranges have been used to measure tibial acceleration. Accelerometers with a low operating range output distorted signals and have been found to result in inaccurate measurements of peaks. A restoration algorithm using spline interpolation has been proposed to restore the distorted signal. This algorithm has been validated for axial peaks within the range of 15.0–15.9 g. However, the accuracy of peaks of higher magnitude and the resultant peaks have not been reported. The purpose of the present study is to evaluate the measurement agreement of the restored peaks using a low-range accelerometer (±16 g) against peaks sampled using a high-range accelerometer (±200 g). The measurement agreement of both the axial and resultant peaks were examined. In total, 24 runners were equipped with 2 tri-axial accelerometers at their tibia and completed an outdoor running assessment. The accelerometer with an operating range of ±200 g was used as reference. The results of this study showed an average difference of −1.40 ± 4.52 g and −1.23 ± 5.48 g for axial and resultant peaks. Based on our findings, the restoration algorithm could skew data and potentially lead to incorrect conclusions if used without caution.
... Tibial shock was determined from Inertial Measurement Unit accelerometer data using a custom Python processing script (Python Language Reference, Version 2.7; Python Software Foundation, Fredericksburg, VA, USA) that identified each stance phase during running. 35,40 The peak positive vertical acceleration measured at the distal medial tibia was then extracted from the raw accelerometer data during each stance phase. Data for each variable were extracted for 10-foot strikes and averaged. ...
... 36 As such, it can be used as a surrogate for load rates that normally require force plates or force treadmills for measurement. Therefore, accelerometers can provide a way to measure changes in impacts in a runner's natural environment, 40 perhaps allowing for a more ecologically valid measure of changes related to exertion in real world conditions. ...
Article
Purpose : Bone stress injuries (BSIs) are common in female runners, and recurrent BSI rates are high. Previous work suggests an association between higher impact loading during running and tibial BSI. However, it is unknown whether impact loading and fatigue related loading changes discriminate women with a history of multiple BSIs. This study compared impact variables at the beginning of a treadmill run to exertion and the changes in those variables with exertion among female runners with no history of BSI as well as among those with a history of 1 or multiple BSIs. Methods : We enrolled 45 female runners (aged 18–40 years) for this cross-sectional study: having no history of diagnosed lower extremity BSI (N-BSI, n = 14), a history of 1 lower extremity BSI (1-BSI, n = 16), diagnosed by imaging, or a history of multiple (≥3) lower extremity BSIs (M-BSI, n = 15). Participants completed a 5 km race speed run on an instrumented treadmill while wearing an Inertial Measurement Unit (IMU). Vertical average loading rate (VALR), vertical instantaneous loading rate (VILR), vertical stiffness during impact via instrumented treadmill, and tibial shock determined as the peak positive tibial acceleration via IMU were measured at the beginning and end of the run. Results : There were no differences between groups in VALR, VILR, vertical stiffness, or tibial shock in a fresh or exerted condition. However, compared to N-BSI, women with M-BSI had greater increase with exertion in VALR (–1.8% vs. 6.1%, p = 0.01 and VILR (1.5% vs. 4.8%, p = 0.03). Similarly, compared to N-BSI, vertical stiffness increased more with exertion among women with M-BSI (–0.9% vs. 7.3%, p = 0.006) and 1-BSI (–0.9% vs. 1.8%, p = 0.05). Finally, compared to N-BSI, the increase in tibial shock from fresh to exerted condition was greater among women with M-BSI (0.9% vs. 5.5%, p = 0.03) and 1-BSI (0.9% vs. 11.2%, p = 0.02). Conclusion : Women with 1-BSI or M-BSIs experience greater exertion-related increases in impact loading than women with N-BSI. These observations imply that exertion-related changes in gait biomechanics may contribute to risk of BSI.
... Accelerometers are often light-weight and wireless, offering the ability to capture loading parameters outside of the laboratory. This is especially important, given recent findings that TAs differ significantly when moving from a laboratory to outdoor environment (Johnson et al., 2020a;Milner et al., 2020). Additionally, peak TAs in the vertical direction have shown strong correlations to vertical loading rates (Tenforde et al., 2020;Van den Berghe et al., 2019), and associations with running injuries (Kiernan et al., 2018;Milner et al., 2006). ...
... The interquartile ranges for all variables were close to or greater than median values. Inter-participant variability is much lower in the vertical direction for both TA and LRs, where standard deviations closer to 33% of the mean have been reported (Johnson et al., 2020a(Johnson et al., , 2020b As hypothesized, we found significant correlations between medial-lateral TAs and LRs. The correlations were strong (R > 0.5) and the amount of variance in MILR/LILR explained by TAs was high (74-83%). ...
Article
Peak vertical tibial accelerations during running have shown strong correlations with vertical ground reaction force loading rates and some associations with injury. However, little attention has been given to tibial accelerations along the medial-lateral and anterior-posterior axes. Therefore, our purpose was to examine the correlation between peak tibial accelerations and ground reaction force loading rates in the medial-lateral and posterior directions. Eighteen recreational runners were recruited who ran with a rearfoot strike pattern (10 men/ 8 women, mean age (yrs)= 33 ±11). Tibial accelerations and ground reaction forces were collected while participants ran on an instrumented treadmill at a self-selected speed. Correlations were developed for: a) peak medial and lateral accelerations with lateral and medial loading rates, respectively, b) peak anterior tibial accelerations and posterior loading rates. Significant correlations were found between tibial accelerations and loading rates in all planes. Peak medial tibial accelerations were correlated with lateral loading rates (Rs= 0.86, p< 0.001) and peak lateral tibial accelerations were correlated with peak medial loading rates (Rs= 0.91, p< 0.001). A lower correlation was found between anterior accelerations and posterior loading rates (Rs= 0.51, p= 0.030). Tibial accelerations in the medial-lateral plane seem to be a valid surrogate for the respective ground reaction force measures during running on a treadmill, explaining 74-83% of the variance in loading rates. However, with only 26% of the variance explained, the same may not be true for anterior tibial accelerations and posterior loading rates.
... While cumulative loads at the knee per 1 km have been estimated to be lower when increasing cadence (Baggaley et al., 2017), cumulative loads at the hip may increase due to larger hip kinetics and more steps when running with a higher cadence. Third, labbased investigations provide experimental control, accuracy, and feasibility often necessary to address research questions, but differences in running biomechanics have been observed between running in the lab and in the field (i.e., natural running environment) (Johnson et al., 2020;Milner et al., 2020). Fourth, we selected increases in cadence of +5% and +10% since these were commonly used for previous studies in adults (Anderson et al., 2022). ...
Article
Increasing cadence is an intervention to reduce injury risk for adolescent long-distance runners. It is unknown how adolescents respond biomechanically when running with a higher than preferred cadence. We examined the influence of increasing cadence on peak joint angles, moments and powers, and ground reaction forces in long-distance runners. We collected three-dimensional kinematics and kinetics for 31 high school cross-country runners during overground running at their preferred cadence (baseline), +5%, and +10% baseline cadence. We performed repeated-measures ANOVAs to compare peak joint angles, moments and powers, and ground reactions forces among cadence conditions. Increasing cadence reduced peak pelvis, hip, knee, and ankle joint angles (p ≤ .01), peak knee moment and powers (p < .001), peak ankle power (p ≤ .01), and peak ground reaction forces (p ≤ .01) but increased peak hip moment and powers (p < .001). Increasing cadence by 10% elicited greater magnitude changes compared to increasing cadence by 5%. Increasing cadence may be a beneficial intervention to reduce lower extremity peak joint angles and knee kinetics for adolescent long-distance runners. The increase in hip kinetics when running at a higher than preferred cadence indicates this intervention increases the loads applied to the hip for adolescent long-distance runners.
... Biomechanical studies on the effect of fatigue on running gait have primarily used optical marker-based motion capture, undertaken in laboratory settings. However, running is commonly performed outdoors [9], and there are significant differences in biomechanical outcomes between treadmill and overground running [10][11][12][13]. With the concurrent collection of physiological data often absent [14], and inconsistent trends in the outcome measures assessed [8], a holistic understanding of running fatigue in real-world conditions is limited. ...
Article
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Background: Fatigue manifests as a decline in performance during high-intensity and prolonged exercise. With technological advancements and the increasing adoption of inertial measurement units (IMUs) in sports biomechanics, there is an opportunity to enhance our understanding of running-related fatigue beyond controlled laboratory environments. Research question: How have IMUs have been used to assess running biomechanics under fatiguing conditions? Methods: Following the PRISMA-ScR guidelines, our literature search covered six databases without date restrictions until September 2024. The Population, Concept, and Context criteria were used: Population (distance runners ranging from novice to competitive), Concept (fatigue induced by running a distance over 400 m), Context (assessment of fatigue using accelerometer, gyroscope, and/or magnetometer wearable devices). Biomechanical outcomes were extracted and synthesised, and interpreted in the context of three main study characteristics (cohort ability, testing environment, and the inclusion of physiological outcomes) to explore their potential role in influencing outcomes. Results: A total of 88 articles were included in the review. There was a high prevalence of treadmill-based studies (n=46, 52%), utilising only 1-2 sensors (n=69, 78%), and cohorts ranged in experience, from sedentary to elite-level runners, and were largely comprised of males (69% of all participants). The majority of biomechanical outcomes assessed showed varying responses to fatigue across studies, likely attributable to individual variability, exercise intensity, and differences in fatigue protocol settings and prescriptions. Spatiotemporal outcomes such as stride time and frequency (n=37, 42 %) and impact accelerations (n=55, 62%) were more widely assessed, with a fatigue response that appeared population and environment specific. Significance: There was notable heterogeneity in the IMU-based biomechanical outcomes and methods evaluated in this review. The review findings emphasise the need for standardisation of IMU-based outcomes and fatigue protocols to promote Interpretable metrics and facilitate inter-study comparisons
... Research on the biomechanics of long-duration outdoor movements has primarily focused on running athletes (e.g., [39,40]). It wasn't until recently that a study by Bloch et al., (2024) measured changes to gait kinematics during an extended ruck hike. ...
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The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5–20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running.
... For this condition, participants were also asked to perform a modified-Stroop test, a visual processing cognitive task [32]. As described previously [33], this was used as a distraction method, to keep participants from consciously focusing on their running form. For the Shod-Quiet condition, participants also wore their normal footwear and were provided instructions to land as softly and quietly as possible. ...
... These factors limit the general population's access to captive systems and the biomechanical analyses they can provide [3]. Further, even when accessible, captive systems may cause participants to alter their gait (e.g., the Hawthorne effect, running on a treadmill or short track, targeting force plates during over-ground running in lab), can limit the volume of data collected to a few 'representative' gait cycles [4], cannot be used to provide real-time feedback in the field, and cannot capture biomechanics that may only occur under certain real-world conditions (e.g., weather, running surfaces, races and training) [5][6][7][8]. These limitations have led to most biomechanics studies capturing relatively brief 'snapshots' of running that may not accurately represent the millions of gait cycles that occur over many long bouts in the field [9], creating a gap in our understanding of running behavior [10]. ...
Article
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Inertial measurement units (IMUs) provide exciting opportunities to collect large volumes of running biomechanics data in the real world. IMU signals may, however, be affected by variation in the initial IMU placement or movement of the IMU during use. To quantify the effect that changing an IMU’s location has on running data, a reference IMU was ‘correctly’ placed on the shank, pelvis, or sacrum of 74 participants. A second IMU was ‘misplaced’ 0.05 m away, simulating a ‘worst-case’ misplacement or movement. Participants ran over-ground while data were simultaneously recorded from the reference and misplaced IMUs. Differences were captured as root mean square errors (RMSEs) and differences in the absolute peak magnitudes and timings. RMSEs were ≤1 g and ~1 rad/s for all axes and misplacement conditions while mean differences in the peak magnitude and timing reached up to 2.45 g, 2.48 rad/s, and 9.68 ms (depending on the axis and direction of misplacement). To quantify the downstream effects of these differences, initial and terminal contact times and vertical ground reaction forces were derived from both the reference and misplaced IMU. Mean differences reached up to −10.08 ms for contact times and 95.06 N for forces. Finally, the behavior in the frequency domain revealed high coherence between the reference and misplaced IMUs (particularly at frequencies ≤~10 Hz). All differences tended to be exaggerated when data were analyzed using a wearable coordinate system instead of a segment coordinate system. Overall, these results highlight the potential errors that IMU placement and movement can introduce to running biomechanics data.
... However, they require extensive setup and data processing procedures to overcome errors associated with longitudinal analysis, such as sensor misalignment [6]. As a result, measuring the acceleration profile of a single segment and inferring changes in kinematics has often been a methodology employed in running-related studies that have analyzed a participant's running style over longer periods [7][8][9][10][11]. ...
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The overall aim of this study was to determine the effects of running kinematics on the peak upper trunk segmental accelerations captured with an accelerometer embedded in a commonly used GPS device. Thirteen male participants (age: 27 ± 3.7 years, height: 1.81 ± 0.06 m, mass: 82.7 ± 6.2 kg) with extensive running experience completed a single trial of treadmill running (1 degree inclination) for 40 s at nine different speeds ranging from 10 to 18 km/h at 1 km/h increments. Three-dimensional peak upper trunk acceleration values were captured via a GPS device containing a tri-axial accelerometer. Participants’ running kinematics were calculated from the coordinate data captured by an 18-camera motion capture system. A series of generalized linear mixed models were employed to determine the effects of the kinematic variables on the accelerometer acceleration peaks across the key gait phases of foot contact. Results showed that running kinematics had significant effects on peak accelerometer-measured accelerations in all axes (p < 0.05). Overall, peak segment velocities had a larger effect than joint/segment kinematics on resultant (F values = 720.9/54.2), vertical (F values = 149.8/48.1) and medial–lateral (F values = 55.4/33.4) peak accelerometer accelerations. The largest effect on peak accelerometer accelerations were observed during the impact subphase of foot contact at the adduction/abduction velocity of the shank (F value = 129.2, coefficient = −0.03) and anterior/posterior velocity of the pelvis (F value = 58.9, coefficient = 0.01). Axis-dependent effects of running kinematics were also observed, specifically at the trunk segment in the vertical and anterior–posterior peak accelerometer accelerations. This study showed the intersegmental relationship between joint/segment kinematics, segment velocities and the resulting peak accelerations of the upper trunk during running over several speeds. These findings provide insights into the lower body’s GRF attenuation capacity and its contribution to trunk stability whilst running.
... Via the customised Python code, accelerometry signals underwent a post-collection calibration process during which any signal offset and drift was removed prior to movement trials (Winslow & Shorten, 1989). Initial contacts from accelerometry data were identified at 1 ms prior to a maximum of the vertical accelerometer signal (Johnson et al., 2020). Primary outcomes from the accelerometer signal were the mean step-by-step vertical, anteroposterior, and resultant peak accelerations over the 30 steps. ...
... To increase ecological validity, previous research has attempted to replicate field conditions within the lab [15][16][17][18][19]. Even with such attempts, however, spatial constraints may cause participants to alter their gait on a treadmill or short running track [20], and temporal constraints still limit the duration and volume of data collection. Thus, lab measured GRFs may not accurately represent Table 1. ...
Article
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Twenty-seven methods of estimating vertical ground reaction force first peak, loading rate, second peak, average, and/or time series from a single wearable accelerometer worn on the shank or approximate center of mass during running were compared. Force estimation errors were quantified for 74 participants across different running surfaces, speeds, and foot strike angles and biases, repeatability coefficients, and limits of agreement were modeled with linear mixed effects to quantify the accuracy, reliability, and precision. Several methods accurately and reliably estimated the first peak and loading rate, however, none could do so precisely (the limits of agreement exceeded ±65% of target values). Thus, we do not recommend first peak or loading rate estimation from accelerometers with the methods currently available. In contrast, the second peak, average, and time series could all be estimated accurately, reliably, and precisely with several different methods. Of these, we recommend the ‘Pogson’ methods due to their accuracy, reliability, and precision as well as their stability across surfaces, speeds, and foot strike angles.
... This may be possible by utilizing data from the gyroscope; however, it is worth considering the effects on onboard storage space and battery life that would be required to accommodate sampling from an additional sensor. This is especially important when considering clinic or field applications, where recording sessions may last for over an hour [16,17]. ...
Article
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While some studies have found strong correlations between peak tibial accelerations (TAs) and early stance ground reaction forces (GRFs) during running, others have reported inconsistent results. One potential explanation for this is the lack of a standard orientation for the sensors used to collect TAs. Therefore, our aim was to test the effects of an established sensor reorientation method on peak Tas and their correlations with GRFs. Twenty-eight runners had TA and GRF data collected while they ran at a self-selected speed on an instrumented treadmill. Tibial accelerations were reoriented to a body-fixed frame using a simple calibration trial involving quiet standing and kicking. The results showed significant differences between raw and reoriented peak TAs (p < 0.01) for all directions except for the posterior (p = 0.48). The medial and lateral peaks were higher (+0.9–1.3 g), while the vertical and anterior were lower (−0.5–1.6 g) for reoriented vs. raw accelerations. Correlations with GRF measures were generally higher for reoriented TAs, although these differences were fairly small (Δr² = 0.04–0.07) except for lateral peaks (Δr² = 0.18). While contingent on the position of the IMU on the tibia used in our study, our results first showed systematic differences between reoriented and raw peak accelerations. However, we did not find major improvements in correlations with GRF measures for the reorientation method. This method may still hold promise for further investigation and development, given that consistent increases in correlations were found.
... In addition to the sensor placed on L5 (500 Hz), one sensor is placed antero-medial on the distal tibia (1000 Hz), 5 cm above the malleolus, one in each leg. This application has been successfully used in previous investigations, due to the flat bone structure of the tibia at this spot [40,41]. The reference run includes (1) a standardized warm-up of 800 m at a self-selected speed, (2) followed by three sprinting conditions (one submaximal, two maximal) of 60 m, and (3) an incremental run until the athlete is completely exhausted. ...
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Background Running is a very popular sport among both recreational and competitive athletes. However, participating in running is associated with a comparably high risk of sustaining an exercise-related injury. Due to the often multifactorial and individual reasons for running injuries, a shift in thinking is required to account for the dynamic process of the various risk factors. Therefore, a machine learning approach will be used to comprehensively analyze biomechanical, biological, and loading parameters in order to identify risk factors and to detect risk patterns in runners. Methods The prospective longitudinal cohort study will include competitive adult athletes, running at least 20 km per week and being free of injuries three months before the start of the study. At baseline and the end of the study period, subjective questionnaires (demographics, injury history, sports participation, menstruation, medication, psychology), biomechanical measures (e.g., stride length, cadence, kinematics, kinetics, tibial shock, and tibial acceleration) and a medical examination (BMI, laboratory: blood count, creatinine, calcium, phosphate, parathyroid hormone, vitamin D, osteocalcin, bone-specific alkaline phosphatase, DPD cross-links) will be performed. During the study period (one season), continuous data collection will be performed for biomechanical parameters, injuries, internal and external load. Statistical analysis of the data is performed using machine learning (ML) methods. For this purpose, the correlation of the collected data to possible injuries is automatically learned by an ML model and from this, a ranking of the risk factors can be determined with the help of sensitivity analysis methods. Discussion To achieve a comprehensive risk reduction of injuries in runners, a multifactorial and individual approach and analysis is necessary. Recently, the use of ML processes for the analysis of risk factors in sports was discussed and positive results have been published. This study will be the first prospective longitudinal cohort study in runners to investigate the association of biomechanical, bone health, and loading parameters as well as injuries via ML models. The results may help to predict the risk of sustaining an injury and give way for new analysis methods that may also be transferred to other sports. Trial registration : DRKS00026904 (German Clinical Trial Register DKRS), date of registration 18.10.2021.
... During foot strike, ground reaction forces are generated with consecutive deceleration and acceleration of the body. A variety of mechanisms modify the impact shock, and measuring of accelerations at the tibia or other anatomical sites could offer opportunities for performance enhancement, injury prevention and gait retraining [45,48,49]. Due to advances in technology, IMUs nowadays allow for much more than acceleration measures. ...
Chapter
The purpose of this chapter is to describe the interdisciplinary field of biomechanics and its importance in the evaluation of running. We will shortly describe the basic principles and origins of this scientific field and go into further details of new technical innovations. Then, a comprehensive overview of laboratory and field-based biomechanical analyses will be discussed in the light of implication for injury aetiology and prevention. Finally, we will end with a discussion on new research areas and implications for future research.
... Accelerometer data from the IMU were filtered via a low-pass, fourth-order Butterworth recursive filter at a cutoff frequency of 75 Hz. Initial contact from accelerometry data was identified at 1 ms before a maximum of the vertical accelerometer signal (Figure 2) (Johnson et al., 2020). Primary outcomes from the accelerometer signal were peak vertical, posterior, and resultant accelerations. ...
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Introduction Running-related injuries (RRIs) occur from a combination of training load errors and aberrant biomechanics. Impact loading, measured by peak acceleration, is an important measure of running biomechanics that is related to RRI. Foot strike patterns may moderate the magnitude of impact load in runners. The effect of foot strike pattern on peak acceleration has been measured using tibia-mounted inertial measurement units (IMUs), but not commercially available insole-embedded IMUs. The aim of this study was to compare the peak acceleration signal associated with rearfoot (RFS), midfoot (MFS), and forefoot (FFS) strike patterns when measured with an insole-embedded IMU. Materials and Methods Healthy runners ran on a treadmill for 1 min at three different speeds with their habitual foot strike pattern. An insole-embedded IMU was placed inside standardized neutral cushioned shoes to measure the peak resultant, vertical, and anteroposterior accelerations at impact. The Foot strike pattern was determined by two experienced observers and evaluated using high-speed video. Linear effect mixed-effect models were used to quantify the relationship between foot strike pattern and peak resultant, vertical, and anteroposterior acceleration. Results A total of 81% of the 187 participants exhibited an RFS pattern. An RFS pattern was associated with a higher peak resultant (0.29 SDs; p = 0.029) and vertical (1.19 SD; p < 0.001) acceleration when compared with an FFS running pattern, when controlling for speed and limb, respectively. However, an MFS was associated with the highest peak accelerations in the resultant direction (0.91 SD vs. FFS; p = 0.002 and 0.17 SD vs. RFS; p = 0.091). An FFS pattern was associated with the lowest peak accelerations in both the resultant and vertical directions. An RFS was also associated with a significantly greater peak acceleration in the anteroposterior direction (0.28 SD; p = 0.033) than an FFS pattern, while there was no difference between MFS and FFS patterns. Conclusion Our findings indicate that runners should be grouped by RFS, MFS, and FFS when comparing peak acceleration, rather than the common practice of grouping MFS and FFS together as non-RFS runners. Future studies should aim to determine the risk of RRI associated with peak accelerations from an insole-embedded IMU to understand whether the small observed differences in this study are clinically meaningful.
... In the included studies, the dominant main outcome measure is derived from acceleration. There seems to be consensus that peak tibial acceleration (also referred to as tibial shock) can be used as a proxy for the impact forces experienced at the tibia and thus the vertical impact loading in running [85], as it has been shown to correlate strongly with vertical loading rates [86]. Comparably, for head impacts, peak linear acceleration is interpreted as detected head impacts. ...
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Shock impacts during activity may cause damage to the joints, muscles, bones, or inner organs. To define thresholds for tolerable impacts, there is a need for methods that can accurately monitor shock impacts in real-life settings. Therefore, the main aim of this scoping review was to present an overview of existing methods for assessments of shock impacts using wearable sensor technology within two domains: sports and occupational settings. Online databases were used to identify papers published in 2010–2020, from which we selected 34 papers that used wearable sensor technology to measure shock impacts. No studies were found on occupational settings. For the sports domain, accelerometry was the dominant type of wearable sensor technology utilized, interpreting peak acceleration as a proxy for impact. Of the included studies, 28 assessed foot strike in running, head impacts in invasion and team sports, or different forms of jump landings or plyometric movements. The included studies revealed a lack of consensus regarding sensor placement and interpretation of the results. Furthermore, the identified high proportion of validation studies support previous concerns that wearable sensors at present are inadequate as a stand-alone method for valid and accurate data on shock impacts in the field.
... Via the customized LabView software, accelerometry signals underwent a postcollection calibration process during which any signal offset and drift was removed prior to movement trials (Winslow and Shorten, 1989). Footstrikes from accelerometry data from the IMeasureU and Plantiga devices were identified at 0.1 ms prior to a maximum of the vertical accelerometer signal (Johnson et al., 2020). Primary IMU outcome variables were PPA from the IMeasureU-Tibia and IMeasureU-Shoe; PPA from the Plantiga IMU ( Figure 2); and proprietary algorithms for "Impact" and "Shock" from the RunScribe device. ...
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Introduction: Most running-related injuries are believed to be caused by abrupt changes in training load, compounded by biomechanical movement patterns. Wearable technology has made it possible for runners to quantify biomechanical loads (e.g., peak positive acceleration; PPA) using commercially available inertial measurement units (IMUs). However, few devices have established criterion validity. The aim of this study was to assess the validity of two commercially available IMUs during running. Secondary aims were to determine the effect of footwear, running speed, and IMU location on PPA. Materials and Methods: Healthy runners underwent a biomechanical running analysis on an instrumented treadmill. Participants ran at their preferred speed in three footwear conditions (neutral, minimalist, and maximalist), and at three speeds (preferred, +10%, −10%) in the neutral running shoes. Four IMUs were affixed at the distal tibia (IMeasureU-Tibia), shoelaces (RunScribe and IMeasureU-Shoe), and insole (Plantiga) of the right shoe. Pearson correlations were calculated for average vertical loading rate (AVLR) and PPA at each IMU location. Results: The AVLR had a high positive association with PPA (IMeasureU-Tibia) in the neutral and maximalist (r = 0.70–0.72; p ≤ 0.001) shoes and in all running speed conditions (r = 0.71–0.83; p ≤ 0.001), but low positive association in the minimalist (r = 0.47; p < 0.05) footwear condition. Conversely, the relationship between AVLR and PPA (Plantiga) was high in the minimalist (r = 0.75; p ≤ 0.001) condition and moderate in the neutral (r = 0.50; p < 0.05) and maximalist (r = 0.57; p < 0.01) footwear. The RunScribe metrics demonstrated low to moderate positive associations (r = 0.40–0.62; p < 0.05) with AVLR across most footwear and speed conditions. Discussion: Our findings indicate that the commercially available Plantiga IMU is comparable to a tibia-mounted IMU when acting as a surrogate for AVLR. However, these results vary between different levels of footwear and running speeds. The shoe-mounted RunScribe IMU exhibited slightly lower positive associations with AVLR. In general, the relationship with AVLR improved for the RunScribe sensor at slower speeds and improved for the Plantiga and tibia-mounted IMeasureU sensors at faster speeds.
... Most previous work investigating the influence of surface type on running parameters were conducted in laboratory settings [15][16][17][18] . Recent studies have reported that tibial accelerations measured in a laboratory setting do not capture tibial accelerations that occur in the field 22,23 . To our knowledge, only one study investigated tibial accelerations on a trail surface in an outdoor setting, comparing concrete, synthetic running track, and woodchip trail surfaces; they reported no differences in tibial accelerations when running at a self-selected speed 10 . ...
Article
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Objectives Increased tibial axial acceleration and reduced shock attenuation are associated with running injuries and are believed to be influenced by surface type. Trail running has increased in popularity and is thought to have softer surface properties than paved surface, but it is unclear if trail surfaces influence tibial acceleration and shock attenuation. The purpose of this study was to investigate peak triaxial and resultant tibial acceleration as well as axial and resultant shock attenuation among dirt, gravel, and paved surfaces. Design Fifteen recreational runners (12 females, 3 males, age = 27.7 ± 9.1 years) ran over dirt, gravel, and paved surfaces in a trail environment while instrumented with triaxial tibial and head accelerometers. Methods Differences between tri-planar peak tibial accelerations (braking, propulsion, axial, medial, lateral, and resultant) and shock attenuations (axial and resultant) among surface types were assessed with one-way ANOVAs with Bonferroni post-hoc tests. Results No significant differences were found for tibial accelerations or shock attenuations among surface types (p > 0.05). Conclusions Dirt and gravel trail running surfaces do not have lower tibial accelerations or greater shock attenuation than paved surfaces. While runners are encouraged to enjoy the psychological benefits of trail running, trail surfaces do not appear to reduce loading forces associated with RRIs.
... Possible intervention strategies are still at an early stage of development. However, considering the wide availability of IMUs that can be worn on the body or in textiles as 'wearables' [57][58][59] , the concept of running stability might be a promising field for future research. ...
Article
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Local dynamic running stability is the ability of a dynamic system to compensate for small perturbations during running. While the immediate effects of footwear on running biomechanics are frequently investigated, no research has studied the long-term effects of barefoot vs. shod running on local dynamic running stability. In this randomized single-blinded controlled trial, young adults novice to barefoot running were randomly allocated to a barefoot or a cushioned footwear running group. Over an 8-week-period, both groups performed a weekly 15-min treadmill running intervention in the allocated condition at 70% of their VO 2 max velocity. During each session, an inertial measurement unit on the tibia recorded kinematic data (angular velocity) which was used to determine the short-time largest Lyapunov exponents as a measure of local dynamic running stability. One hundred running gait cycles at the beginning, middle, and end of each running session were analysed using one mixed linear multilevel random intercept model. Of the 41 included participants (48.8% females), 37 completed the study (drop-out = 9.7%). Participants in the barefoot running group exhibited lower running stability than in the shod running group ( p = 0.037) with no changes during the intervention period ( p = 0.997). Within a single session, running stability decreased over the course of the 15-min run ( p = 0.012) without differences between both groups ( p = 0.060). Changing from shod to barefoot running reduces running stability not only in the acute phase but also in the longer term. While running stability is a relatively new concept, it enables further insight into the biomechanical influence of footwear.
... Due to these advantages and less complexity compared to laboratory systems, such as marker and camera-based 3D motion capture systems, IMUs have become a more frequently used sports technology (12,18,28). This provides running gait analysis under real-life conditions in the athletes natural training court and habitual environment (16,19,25,29). An IMU system for in-field use is the Humotion SmarTracks Integrated System (HSTI). ...
Article
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Problem: The technology of inertial measurement units (IMU) enables the collection of running biomechanical data under in-field conditions. This paper presents a validation study of an increasingly used IMU system using a corresponding below-ground magnetic timing gate system. Methods: Thirty active healthy participants ran with an IMU located at the lumbar spine on a 60 m-section of a 400 m tartan track. The IMUs were connected with magnetic timing gates installed below the tartan track. A photoelectric cell reference system was used for comparative analysis. Outcome measures were running speed, step length and cadence during running at slow and fast velocity. Intra-Class-Correlation (ICC), Bland-Altman analysis and regression-based Bland-Altman analysis were used to determine measurement agreement. Results: The analysis showed high measurement agreement for running speed, step length and cadence for both velocities (ICCs 0.745-0.996). Bland-Altman analysis showed high random errors and increased systematic and random errors for step length and cadence at fast running velocities. Regression-based Bland-Altman analysis indicated a systematic increase of bias (systematic error) with higher step length values. Discussion: Despite a high measurement agreement expressed by ICCs, study results also showed high error values for absolute measurements expressed by systematic and random errors for all parameters. Therefore, attention should be given to the comparability of both measurement systems. Further research should focus on details of step length calculations as well as reliability and validity under longer running conditions.
... Hierbei können mit Hilfe von "Inertial Measurement Units (IMUs)", die Beschleunigungs-, Drehraten-und magnetische Sensoren enthalten, beispielsweise kontinuierlich kinematische Daten während einer Trainingseinheit oder eines Wettkampfs gemessen werden (7, 8, 14). Außerdem können indirekt über die Beschleunigung der Tibia auch auftretende Kräfte abgeschätzt werden (14,22). Die Forschung in diesem Bereich wird voraussichtlich in den kommenden Jahren deutlich zunehmen und muss sich aktuell noch einer ausreichender Validierung für die unterschiedlichen zu messende Parameter und Forschungsfragestellungen unterziehen (18). ...
Article
OBJECTIVE: to compare step rate and tibial acceleration during an 8-km run performed outdoors versus on a treadmill. DESIGN: Repeated measures observational study. METHODS: Healthy adult runners (females: 9, males: 19) ran 8 km at a self-selected speed outdoors and on a treadmill. A chest mounted inertial measurement unit (IMU) was used to measure step rate while a tibial mounted IMU collected tibial acceleration. Linear mixed-effects models adjusted for speed were used to assess step rate, as well as peak vertical (PV) and peak resultant (PRES) tibial accelerations between conditions and across the 8 km, as well as their interaction. RESULTS: There was a significant interaction between distance and location (est [95% CI] = 0.71 [0.38 to 1.05], p < 0.001) for step rate, with an increase in step rate observed over distance outdoors. There was also a significant interaction between distance and location for PV (-0.13 [-0.25 to -0.00], p = 0.047) and PRES (-0.16 [-0.31 to -0.00], p = 0.047), with both increasing over distance during treadmill running. Overall, PV (3.34 [2.85 to 3.83], p < 0.001) and PRES (5.05 [4.45 to 5.65], p < 0.001) were significantly greater when running outdoors compared to treadmill running. CONCLUSION: Treadmill and overground assessment of step rate were relatively comparable. Tibial acceleration may not be interchangeable with gait analysis in the field.
Article
The knee meniscus plays a key role in shock absorption, joint stability, and congruity at the knee joint. However, due to several reasons, meniscal tears are increasing that in turn causes osteoarthritis. The objective of the current study was to evaluate the stresses on the meniscus during kinematic activities and correlate them with the potential tears observed clinically. From the MRI data of a healthy volunteer, 3D models of the menisci were segmented in Mimics®, post-processed in 3-matics®, meshed in HyperMesh® and were analyzed in Abaqus® for stresses arising due to compressive loads from both femoral and tibial ends; under various angles of flexion. The critical regions with higher stress distribution were correlated with the potential meniscal tears. It was observed that the stresses were higher when loads were applied from the tibial end than femoral end. Though the loads were applied proportional to the area, higher stresses were observed in the lateral meniscus. Results of the study show that at higher knee flexion angles, loading from tibial end leads to longitudinal tear in region E1–E2 (as per Cooper’s Classification) on the lateral meniscus and horizontal tear in A-1 region of the medial meniscus. Longitudinal, horizontal, and root detachment tears reported in the literature, coincide with our predictions. The novelty of the study is the estimation of stresses due to forces from the tibial end and the correlation of the stresses to the type of meniscal tears observed clinically.
Article
This study investigated the relationships between inertial measurement unit (IMU) acceleration at multiple body locations and 3D motion capture impact landing measures in runners. Thirty healthy runners ran on an instrumented treadmill at five running speeds (9–17 km/h) during 3D motion capture. Axial and resultant acceleration were collected from IMUs at the distal and proximal tibia, distal femur and sacrum. Relationships between peak acceleration from each IMU location and patellofemoral joint (PFJ) peak force and loading rate, impact peak and instantaneous vertical loading rate (IVLR) were investigated using linear mixed models. Acceleration was positively related to IVLR at all lower limb locations (p < 0.01). Models predicted a 1.9–3.2 g peak acceleration change at the tibia and distal femur, corresponding with a 10% IVLR change. Impact peak was positively related to acceleration at the distal femur only (p < 0.01). PFJ peak force was positively related to acceleration at the distal (p = 0.03) and proximal tibia (p = 0.03). PFJ loading rate was positively related to the tibia and femur acceleration in males only (p < 0.01). These findings suggest multiple IMU lower limb locations are viable for measuring peak acceleration during running as a meaningful indicator of IVLR.
Article
Inertial measurement units (IMUs) attached to the distal tibia are a validated method of measuring lower-extremity impact accelerations, called tibial accelerations (TAs), in runners. However, no studies have investigated the effects of small errors in IMU placement, which would be expected in real-world, autonomous use of IMUs. The purpose of this study was to evaluate the effect of a small proximal shift in IMU location on mean TAs and relationships between TAs and ground reaction force loading rates. IMUs were strapped to 18 injury-free runners at a specified standard location (∼1 cm proximal to medial malleolus) and 2 cm proximal to the standard location. TAs and ground reaction forces were measured while participants ran at self-selected and 10% slower/faster speeds. Mean TA was lower at the standard versus proximal IMU location in the faster running condition ( P = .026), but similar in the slower ( P = .643) and self-selected conditions ( P = .654). Mean TAs measured at the standard IMU explained more variation in ground reaction force loading rates ( r ² = .79−.90; P < .001) compared with those measured at the proximal IMU ( r ² = .65−.72; P < .001). These results suggest that careful attention should be given to IMU placement when measuring TAs during running.
Article
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Background Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as 3D motion capture or force plates. However, recent developments in wearable devices allow for continuous monitoring and analysis of running mechanics in any environment. Objective measurement of running gait is an important (clinical) tool for injury assessment and provides measures that can be used to enhance performance. Objectives To systematically review available literature investigating how wearable technology is being used for running gait analysis in adults. Methods A systematic search of literature was conducted in the following scientific databases: PubMed, Scopus, WebofScience, and SportDiscus. Information was extracted from each included article regarding the type of study, participants, protocol, wearable device(s), main outcomes/measures, analysis, and key findings. Results A total of 131 articles were reviewed: 56 investigated the validity of wearable technology, 22 examined the reliability and 77 focused on applied use. Most studies used inertial measurement units (IMU) (n=62) (i.e., a combination of accelerometers, gyroscopes, and magnetometers in a single unit) or solely accelerometers (n=40), with one using gyroscopes alone and 31 using pressure sensors. On average, studies used one wearable device to examine running gait. Wearable locations were distributed among the shank, shoe and waist. The mean number of participants was 26 (± 27), with an average age of 28.3 (± 7.0) years. Most studies took place indoors (n =93), using a treadmill (n =62), with the main aims seeking to identify running gait outcomes or investigate the effects of injury, fatigue, intrinsic factors (e.g., age, sex, morphology) or footwear on running gait outcomes. Generally, wearables were found to be valid and reliable tools for assessing running gait compared to reference standards. Conclusions This comprehensive review highlighted that most studies that have examined running gait using wearable sensors have done so with young adult recreational runners, using one IMU sensor, with participants running on a treadmill and reporting outcomes of ground contact time, stride length, stride frequency and tibial acceleration. Future studies are required to obtain consensus regarding terminology, protocols for testing validity and reliability of devices and suitability of gait outcomes.
Article
Peak tibial accelerations during running are of interest because of their correlation with vertical ground reaction force load rates and association with running injury. Previous work has demonstrated systematically lower accelerations measured with a bone- compared to skin-mounted accelerometer. However, no studies have assessed the effects of more or less secure attachment methods for skin mounted sensors. Our purpose was to compare two methods of attaching a skin mounted sensor on mean tibial accelerations, stride-to-stride variability, and correlations with vertical load rates. 18 injury-free runners were recruited as participants. An inertial measurement unit, containing a tri-axial accelerometer, was used to record tibial accelerations while participants ran at a self-selected speed on an instrumented treadmill to collect ground reaction forces. The two attachment methods for securing the sensor to the skin were a manufacturer-provided strap (strap condition) and a combination of tape and elastic wraps (wrap condition). Mean vertical accelerations were significantly lower in the wrap condition (p = 0.02, d = 0.57). No differences were detected in resultant accelerations, vertical loading rates, or stride-to-stride variability. Correlations between tibial accelerations and vertical loading rates were strong (r = 0.79–0.91) and similar between conditions. These results provide two key findings of evidence. Evidenced by systematically lower vertical accelerations, a more secure attachment method may be necessary for capturing the most representative measure of tibial accelerations during running. However, a less secure method (i.e. the strap) is sufficient for capturing tibial accelerations as a surrogate for impact loading forces.
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Background: Impact loading in runners, assessed by the measurement of tibial acceleration, has attracted substantial research attention. Due to potential injury links, particularly tibial fatigue fractures, tibial acceleration is also used as a clinical monitoring metric. There are contributing factors and potential limitations that must be considered before widespread implementation. Aim: The objective of this review is to update current knowledge of the measurement of tibial acceleration in runners and to provide recommendations for those intending on using this measurement device in research or clinical practice. Methods: Literature relating to the measurement of tibial acceleration in steady-state running was searched. A narrative approach synthesised the information from papers written in English. A range of literature was identified documenting the selection and placement of accelerometers, the analysis of data, and the effects of intrinsic and extrinsic factors. Results and discussion: Tibial acceleration is a proxy measurement for the impact forces experienced at the tibia commonly used by clinicians and researchers. There is an assumption that this measure is related to bone stress and strain, however this is yet to be proven. Multi-axis devices should be secured firmly to the tibia to limit movement relative to the underlying bone and enable quantification of all components of acceleration. Additional frequency analyses could be useful to provide a more thorough characterisation of the signal. Conclusions: Tibial accelerations are clearly affected by running technique, running velocity, lower extremity stiffness, as well as surface and footwear compliance. The interrelationships between muscle pre-activation and fatigue, stiffness, effective mass and tibial acceleration still require further investigation, as well as how changes in these variables impact on injury risk.
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OBJECTIVES: To examine mechanical alterations during interval-training treadmill runs in high-level team-sport players. DESIGN: Within-participants repeated measures. METHODS: Twenty high-level male field-hockey players performed six 30-s runs at 5.53+/-0.19ms-1 corresponding to 115% of their velocity associated with maximal oxygen uptake (vVO2max) with 30-s passive recovery on an instrumented treadmill. Continuous measurement of running kinetics/kinematics and spring-mass characteristics were performed and values were subsequently averaged over 20s (8th-28ths) for comparison. RESULTS: Contact time (+1.1+/-4.3%; p=0.044), aerial time (+4.1+/-5.3%; p=0.001), step length (+2.4+/-2.2%; p<0.001) along with mean loading rates (+7.1+/-10.6%; p=0.026) increased from the first to the last interval, whereas step frequency (-2.3+/-2.1%; p<0.001) decreased. Both centre of mass vertical displacement (+3.0+/-6.0%; p<0.001) and leg compression (+2.8+/-9.7%; p=0.036), but not peak vertical forces (0.0+/-4.1%; p=0.761), increased with fatigue. Vertical stiffness decreased (-2.8+/-6.9%; p=0.012), whereas leg stiffness did not change across intervals (p=0.149). CONCLUSIONS: During interval-training treadmill runs, high-level team-sport players modified their mechanical behaviour towards lower vertical stiffness while preserving a constant leg stiffness. Maintenance of running velocity induced longer step lengths and decreased step frequencies that were also accompanied by increased impact loading rates. These mechanical alterations occurred early during the set.
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Ultramarathon runners are exposed to a high number of impact shocks and to severe neuromuscular fatigue. Runners may manage mechanical stress and muscle fatigue by changing their running kinematics. Our purposes were to study (i) the effects of a 110-km mountain ultramarathon (MUM) on tibial shock acceleration and lower limb kinematics, and (ii) whether kinematic changes are modulated according to the severity of neuromuscular fatigue. Twenty-three runners participated in the study. Pre- and post-MUM, neuromuscular tests were performed to assess knee extensor (KE) and plantar flexor (PF) central and peripheral fatigue, and a treadmill running bouts was completed during which step frequency, peak acceleration, median frequency and impact frequency content were measured from tibial acceleration, as well as foot-to-treadmill, tibia-to-treadmill, and ankle flexion angles at initial contact, and ankle range of motion using video analysis. Large neuromuscular fatigue, including peripheral changes and deficits in voluntary activation, was observed in KE and PF. MVC decrements of ~35% for KE and of ~28% for PF were noted. Among biomechanical variables, step frequency increased by ~2.7% and the ankle range of motion decreased by ~4.1% post-MUM. Runners adopting a non rearfoot strike pre-MUM adopted a less plantarflexed foot strike pattern post-MUM while those adopting a rearfoot strike pre-MUM tended to adopt a less dorsiflexed foot strike pattern post-MUM. Positive correlations were observed between percent changes in peripheral PF fatigue and the ankle range of motion. Peripheral PF fatigue was also significantly correlated to both percent changes in step frequency and the ankle angle at contact. This study suggests that in a fatigued state, ultratrail runners use compensatory/protective adjustments leading to a flatter foot landing and this is done in a fatigue dose-dependent manner. This strategy may aim at minimizing the overall load applied to the musculoskeletal system, including impact shock and muscle stretch.
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Objective To determine the distribution of the foot strike patterns among recreational shod runners and to compare the personal and training characteristics between runners with different foot strike patterns. Design Cross-sectional study Setting Areas of running practice in São Paulo, Brazil. Participants 514 recreational shod runners older than 18 years and free of injury. Outcomes measures Foot strike patterns were evaluated with a high-speed camera (250 Hz) and photocells to assess the running speed of participants. Personal and training characteristics were collected through a questionnaire. Results The inter-rater reliability of the visual foot strike pattern classification method was 96.7% and intra-rater reliability was 98.9%. 95.1% (n= 489) of the participants were rearfoot strikers, 4.1% (n= 21) were midfoot strikers, and four runners (0.8%) were forefoot strikers. There were no significant differences between strike patterns for personal and training characteristics. Conclusion This is the first study to demonstrate that almost all recreational shod runners were rearfoot strikers. The visual method of evaluation seems to be a reliable and feasible option to classify foot strike pattern.
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To assess the reliability of triaxial accelerometers as a measure of physical activity in team sports. Eight accelerometers (MinimaxX 2.0, Catapult, Australia) were attached to a hydraulic universal testing machine (Instron 8501) and oscillated over two protocols (0.5 g and 3.0 g) to assess within- and between device reliability. A static assessment was also conducted. Secondly, 10 players were instrumented with two accelerometers during Australian football matches. The vector magnitude was calculated, expressed as Player load and assessed for reliability using typical error (TE) ± 90% confidence intervals (CI), and expressed as a coefficient of variation (CV%). The smallest worthwhile difference (SWD) in Player load was calculated to determine if the device was capable of detecting differences in physical activity. Laboratory: Within- (Dynamic: CV 0.91 to 1.05%; Static: CV 1.01%) and between-device (Dynamic: CV 1.02 to 1.04%; Static: CV 1.10%) reliability was acceptable across each test. Field: The between-device reliability of accelerometers during Australian football matches was also acceptable (CV 1.9%). The SWD was 5.88%. The reliability of the MinimaxX accelerometer is acceptable both within and between devices under controlled laboratory conditions, and between devices during field testing. MinimaxX accelerometers can be confidently utilized as a reliable tool to measure physical activity in team sports across multiple players and repeated bouts of activity. The noise (CV%) of Player load was lower than the signal (SWD), suggesting that accelerometers can detect changes or differences in physical activity during Australian football.
Article
Purpose: Foot strike patterns (FSP) influence landing mechanics, with rearfoot strike (RFS) runners exhibiting higher impact loading than forefoot strike (FFS) runners. The few studies that included midfoot strike (MFS) runners have typically grouped them together with FFS. In addition, most running studies have been conducted in laboratories. Advances in wearable technology now allow the measurement of runners' mechanics in their natural environment. The purpose of this study was to examine the relationship between FSP and impacts across a marathon race. Methods: A total of 222 healthy runners (119 males, 103 females; age, 44.1 ± 10.8 yr) running a marathon race were included. A treadmill assessment was undertaken to determine FSP. An ankle-mounted accelerometer recorded tibial shock (TS) over the course of the marathon. TS was compared between RFS, MFS, and FFS. Correlations between speed and impacts were examined between FSP. TS was also compared at the 10- and 40-km race points. Results: RFS and MFS runners exhibited similar TS (12.24g ± 3.59g vs 11.82g ± 2.68g, P = 0.46) that was significantly higher (P < 0.001 and P < 0.01, respectively) than FFS runners (9.88g ± 2.51g). In addition, TS increased with speed for both RFS (r = 0.54, P = 0.01) and MFS (r = 0.42, P = 0.02) runners, but not FFS (r = 0.05, P = 0.83). Finally, both speed (P < 0.001) and TS (P < 0.001) were reduced between the 10- and the 40-km race points. However, when normalized for speed, TS was not different (P = 0.84). Conclusions: RFS and MFS exhibit higher TS than FFS. In addition, RFS and MFS increase TS with speed, whereas FFS do not. These results suggest that the impact loading of MFS is more like RFS than FFS. Finally, TS, when normalized for speed, is similar between the beginning and the end of the race.
Article
Studies seeking to determine the effects of gait retraining through biofeedback on peak tibial acceleration (PTA) assume that this biometric trait is a valid measure of impact loading that is reliable both within and between sessions. However, reliability and validity data were lacking for axial and resultant PTAs along the speed range of over-ground endurance running. A wearable system was developed to continuously measure 3D tibial accelerations and to detect PTAs in real-time. Thirteen rearfoot runners ran at 2.55, 3.20 and 5.10 m*s-1 over an instrumented runway in two sessions with re-attachment of the system. Intraclass correlation coefficients (ICCs) were used to determine within-session reliability. Repeatability was evaluated by paired T-tests and ICCs. Concerning validity, axial and resultant PTAs were correlated to the peak vertical impact loading rate (LR) of the ground reaction force. Additionally, speed should affect impact loading magnitude. Hence, magnitudes were compared across speeds by RM-ANOVA. Within a session, ICCs were over 0.90 and reasonable for clinical measurements. Between sessions, the magnitudes remained statistically similar with ICCs ranging from 0.50 to 0.59 for axial PTA and from 0.53 to 0.81 for resultant PTA. Peak accelerations of the lower leg segment correlated to LR with larger coefficients for axial PTA (r range: 0.64–0.84) than for the resultant PTA per speed condition. The magnitude of each impact measure increased with speed. These data suggest that PTAs registered per stand-alone system can be useful during level, over-ground rearfoot running to evaluate impact loading in the time domain when force platforms are unavailable in studies with repeated measurements.
Article
Purpose: Recent observations demonstrate that a sizeable proportion of the recreational running population runs at rather slow speeds and does not always show a clear flight phase. This study determined the key biomechanical and physiological characteristics of this running pattern, i.e. grounded running (GR), and compared these characteristics with slow aerial running (SAR) and reference data on walking at the same slow running speed. Methods: Thirty male subjects performed instructed GR and SAR at 2.10 m·s on a treadmill. Ground reaction forces, tibial accelerations and metabolic rate were measured to estimate general musculoskeletal loading (external power and maximal vertical ground reaction force), impact intensity (vertical instantaneous loading rate and tibial acceleration) and energy expenditure. More explicit measures of muscular loading (muscle stresses and peak eccentric power) were calculated based on a representative subsample, in which detailed kinematics and kinetics were recorded. We hypothesized that all measures would be lower for the GR condition. Results: Subjects successfully altered their running pattern upon a simple instruction towards a GR pattern by increasing their duty factor from 41.5% to 51.2%. As hypothesized, impact intensity, general measures for musculoskeletal and the more explicit measures for muscular loading decreased by up to 35.0%, 20.3% and 34.0% respectively compared to SAR. Contrary to our hypothesis, metabolic rate showed an increase of 4.8%. Conclusion: Changing running style from SAR to GR reduces musculoskeletal loading without lowering the metabolic energy requirements. As such, GR might be beneficial for most runners as it has the potential to reduce the risk of running related injuries while remaining a moderate-to-vigorous form of physical activity, contributing to fulfillment of the recommendations concerning physical activity and public health.
Article
A stable gaze is necessary to optimize visual conditions during running. Head accelerations generally remain stable when looking in front, however it is unclear if this response is similar when the head is turned sideways, and whether other adaptive strategies are present to maintain this stability. The purpose of this study, therefore, was to examine whether runners maintained stable head accelerations while gazing at fixed targets in front and to their sides. We collected biomechanical data from thirteen runners as they directed their gaze to visual targets located in front, 45-degree and 90-degree to the sides at a random sequence. Vertical head and tibial accelerations were the primary outcome measures, while vertical loading rate, footstrike angle, contact time, stride length, and stride rate were the secondary measures. A reduction in vertical head accelerations was found in the rightmost direction (p = .040), while an increase in vertical tibial accelerations was found on the same direction (p = .016). No other significant differences were observed for the other variables. The results of this study suggest that the tibia accommodated the increased shock to maintain head stability.
Article
The characteristics of a treadmill and the environment where it is based could influence the user’s gaze and have an effect on their running kinematics and lower limb impacts. The aim of this study was to identify the effect of visual focus on spatio-temporal parameters and lower limb kinematics during treadmill running. Twenty six experienced runners ran at 3.33 m s⁻¹ on a treadmill under two visual conditions, either looking ahead at a wall or looking down at the treadmill visual display. Spatio-temporal parameters, impact accelerations of the head and tibia, and knee and ankle kinematics were measured for the final 15 seconds of a 90 second bout of running under each condition. At the end of the test, participants reported their preference for the visual conditions assessed. Participants’ stride angle, flight time, knee flexion during the flight phase, and ankle eversion during contact time were increased when runners directed visual focus toward the wall compared to the treadmill display (p < 0.05). Whilst head acceleration was also increased in the wall condition (p < 0.05), the other acceleration parameters were unaffected (p > 0.05). However, the effect size of all biomechanical alterations was small. The Treadmill condition was the preferred condition by the participants (p < 0.001; ESw = 1.0). The results of the current study indicate that runners had a greater mass centre vertical displacement when they ran looking ahead, probably with the aim of compensating for reduced visual feedback, which resulted in larger head accelerations. Greater knee flexion during the flight phase and ankle eversion during the contact time were suggested as compensatory mechanisms for lower limb impacts.
Article
Introduction: Running with a forefoot strike (FFS) pattern has been suggested to reduce the risk of overuse running injuries, due to a reduced vertical loadrate compared with rearfoot strike (RFS) running. However, resultant loadrate has been reported to be similar between foot strikes when running in traditional shoes, leading to questions regarding the value of running with a FFS. The influence of minimal footwear on the resultant loadrate has not been considered. This study aimed to compare component and resultant instantaneous loadrate (ILR) between runners with different foot strike patterns in their habitual footwear conditions. Methods: 29 injury-free participants (22 males, 7 females) ran at 3.13m.s along a 30m runway, with their habitual foot strike and footwear condition. Ground reaction force data were collected. Peak ILR values were compared between three conditions; those who habitually run with a RFS in standard shoes, with a FFS in standard shoes, and with a FFS in minimal shoes. Results: Peak resultant, vertical, lateral and medial ILR were lower (P < 0.001) when running in minimal shoes with a FFS than in standard shoes with either foot strike. When running with a FFS, peak posterior ILR were lower (P < 0.001) in minimal than standard shoes. Conclusions: When running in a standard shoe, peak resultant and component instantaneous loadrates were similar between footstrike patterns. However, loadrates were lower when running in minimal shoes with a FFS, compared with running in standard shoes with either foot strike. Therefore, it appears that footwear alters the loadrates during running, even with similar foot strike patterns.
Article
Background Vertical ground reaction force (VGRF) parameters have been implicated as a cause of several running-related injuries. However, no systematic review has examined this relationship. Aim We systematically reviewed evidence for a relation between VGRF parameters and specific running-related injuries. Methods MEDLINE, Web of Science and EMBASE databases were searched. Two independent assessors screened the articles and rated the methodological quality. The 3 key VGRF parameters we measured were vertical loading rate, impact/passive peak (Fz1) and propulsive/active peak (Fz2). Standardised mean differences of these parameters were calculated using a random-effects model. Meta-regression was performed using injury type, study type and methodological quality as factors. Results The search yielded 2016 citations and 18 met the inclusion criteria for the systematic review. The loading rate was higher in studies that included patients with a history of stress fractures and patients with all injury types, both compared with controls. Only studies that included patients with a history of symptoms at the time of kinetic data collection showed higher loading rates overall in cases than in controls. There were no differences between injured subjects and controls for the active and passive peaks of the VGRF. Summary The loading rate is higher in respondents with a history of stress fractures than in respondents without running injuries. Owing to the absence of prospective studies on other injury types, it is not possible to draw definite conclusions regarding their relation with loading rate.
Article
Background Running has been critical to human survival. Therefore, the high rate of injuries experienced by modern day runners is puzzling. Landing on the heel, as most modern day shod runners do, results in a distinct vertical impact force that has been shown to be associated with running-related injuries. However, these injury studies were retrospective in nature and do not establish cause and effect. Objective To determine whether runners with high impacts are at greater risk for developing medically diagnosed injuries. Methods 249 female runners underwent a gait analysis to measure vertical instantaneous loading rate, vertical average loading rate (VALR), vertical impact peak (VIP) and peak vertical force. Participants then recorded their mileage and any running-related injuries monthly in a web-based, database programme. Variables were first compared between the entire injured (INJ; n=144) and uninjured (n=105) groups. However, the focus of this study was on those injured runners seeking medical attention (n=103) and those who had never injured (n=21). Results There were no differences between the entire group of injured and uninjured groups. However, all impact-related variables were higher in those with medically diagnosed injuries compared with those who had never been injured. (effect size (ES) 0.4–0.59). When VALR was >66.0 body weight (BW)/s, the odds of being DX_INJ were 2.72 (95% CI 1.0 to 7.4). Impact loading was associated with bony and soft-tissue injuries. Conclusions Vertical average loading rate was lower in female runners classified as ‘never injured’ compared with those who had been injured and sought medical attention.
Article
Using data from six male subjects, this study compared ground reaction force and tibial acceleration parameters for running. A bone-mounted triaxial accelerometer and a force platform were employed for data collection. Low peak values were found for the axial acceleration, and a time shift toward the occurrence of the first peak in the vertical force data was present. The time to peak axial acceleration differed significantly from the time to the first force peak, and the peak values of force and acceleration demonstrated only a moderate correlation. However, a high negative correlation was found for the comparison of the peak axial acceleration with the time to peak vertical force. Employing a multiple regression analysis, the peak tibial acceleration could be well estimated using vertical force loading rate and peak horizontal ground reaction force as predictors.
Article
The purpose of this study was to investigate the acute effects of progressive fatigue on the parameters of running mechanics previously associated with tibial stress fracture risk. Twenty-one trained male distance runners performed three sets (Pre, Mid, and Post) of six overground running trials at 4.5 m·s (±5%). Kinematic and kinetic data were collected during each trial using a 12-camera motion capture system, force platform, and head and leg accelerometers. Between tests, each runner ran on a treadmill for 20 min at their corresponding lactate threshold (LT) speed. Perceived exertion levels (RPE) were recorded at the third and last minute of each treadmill run. RPE scores increased from 11.8 ± 1.3 to 14.4 ± 1.5 at the end of the first LT run and then further to 17.4 ± 1.6 by the end of the second LT run. Peak rearfoot eversion, peak axial head acceleration, peak free moment and vertical force loading rates were shown to increase (P < 0.05) with moderate-large effect sizes during the progression from Pre to Post tests, although vertical impact peak and peak axial tibial acceleration were not significantly affected by the high-intensity running bouts. Previously identified risk factors for impact-related injuries (such as tibial stress fracture) are modified with fatigue. Because fatigue is associated with a reduced tolerance for impact, these findings lend support to the importance of those measures to identify individuals at risk of injury from lower limb impact loading during running.
Article
Knowledge of the kinetic changes that occur during sloped running is important in understanding the adaptive gait-control mechanisms at work and can provide additional information about the poorly understood relationship between injury and changes in kinetic forces in the lower extremity. A study of these potential kinetic changes merits consideration, because training and return-to-activity programs are potentially modifiable factors for tissue stress and injury risk. To contribute further to the understanding of hill running by quantifying the 3-dimensional alterations in joint kinetics during moderately sloped decline, level, and incline running in a group of healthy runners. Crossover study. Three-dimensional motion analysis laboratory. Nineteen healthy young runners/joggers (age = 25.3 +/- 2.5 years). Participants ran at 3.13 m/s on a treadmill under the following 3 different running-surface slope conditions: 4 degrees decline, level, and 4 degrees incline. Lower extremity joint moments and powers and the 3 components of the ground reaction force. Moderate changes in running-surface slope had a minimal effect on ankle, knee, and hip joint kinetics when velocity was held constant. Only changes in knee power absorption (increased with decline-slope running) and hip power (increased generation on incline-slope running and increased absorption on decline-slope running in early stance) were noted. We observed an increase only in the impact peak of the vertical ground reaction force component during decline-slope running, whereas the nonvertical components displayed no differences. Running style modifications associated with running on moderate slopes did not manifest as changes in 3-dimensional joint moments or in the active peaks of the ground reaction force. Our data indicate that running on level and moderately inclined slopes appears to be a safe component of training regimens and return-to-run protocols after injury.
Article
To compare selected structural and biomechanical factors between female runners with a history of plantar fasciitis and healthy control subjects. Cross-sectional. University of Delaware Motion Analysis Laboratory, Newark, Delaware; and University of Massachusetts Biomechanics Laboratory, Amherst, Massachusetts. Twenty-five female runners with a history of plantar fasciitis were recruited for this study. A group of 25 age- and mileage-matched runners with no history of plantar fasciitis served as control subjects. The independent variable was whether or not subjects had a history of plantar fasciitis. Subjects ran overground while kinematic and kinetic data were recorded using a motion capture system and force plate. Rearfoot kinematic variables of interest included peak dorsiflexion, peak eversion, time to peak eversion along with eversion excursion. Vertical ground reaction force variables included impact peak and the maximum instantaneous load rate. Structural measures were taken for calcaneal valgus and arch index during standing and passive ankle dorsiflexion range of motion. A significantly greater maximum instantaneous load rate was found in the plantar fasciitis group along with an increased ankle dorsiflexion range of motion compared with the control group. The plantar fasciitis group had a lower arch index compared with control subjects, but calcaneal valgus was similar between groups. No differences in rearfoot kinematics were found between groups. These data indicate that a history of plantar fasciitis in runners may be associated with greater vertical ground reaction force load rates and a lower medial longitudinal arch of the foot.
Article
Measurements of tibial acceleration during walking and running were obtained by means of a triaxial accelerometer. The accelerometer was fixed to the free end of a Steinmann pin inserted into the right tibia of one volunteer subject. The patterns of tibial acceleration showed little step-to-step variation within each experimental condition. Following foot strike and depending upon footwear, the resultant tibial acceleration reached between 2.7 and 3.7 g during walking. The tibia experienced maximal accelerations of 10.6 g during running. The high values of tibial acceleration recorded in the antero-posterior (AP) and medio-lateral (ML) directions clearly revealed the importance of measuring all three components of acceleration to quantify the magnitude of the shock experienced by the lower limbs during locomotor activities.
Article
Although running surface stiffness has been associated with overuse injuries, all evidence to support this suggestion has been circumstantial. In the present study, the biomechanical response of heel-toe runners to changes in running surface has been investigated. Six heel-toe runners performed shod running trials over three surfaces: a conventional asphalt surface, a new rubber-modified asphalt surface, and an acrylic sports surface. The surfaces were categorised according to impact absorbing ability using standard impact test procedures (BS 7044). The rubber-modified asphalt was found to exhibit the greatest amount of mechanical impact absorption, and the conventional asphalt the least. The comparison of peak impact force values across surfaces for the group of subjects demonstrated no significant differences in magnitude of force. However, a significant reduction in loading rate of peak impact force was detected for the rubber-modified surface compared with conventional asphalt (P < 0.1). Although analysis of group data revealed no significant differences in kinematic variables when running on the different surfaces, a varied response to surface manipulation among runners was demonstrated, with marked differences in initial joint angles, peak joint angles, and peak joint angular velocities being observed. For some subjects, the maintenance of similar peak impact forces for different running surfaces was explained by observed kinematic adjustments. For example, when running on the surface providing the least impact absorption, an increased initial knee flexion was observed for some subjects, suggesting an increased lower extremity compliance. However, for some subjects, sagittal plane kinematic data were not sufficient for the explanation of peak impact force results. It appears that the mechanism of adaptation varies among runners, highlighting the requirement of individual subject analyses.
Article
OBJECTIVE: To obtain descriptive information between vertical ground reaction force (GRF)-time histories and gait speed, running style, and gender. DESIGN: GRF-time history measurements were obtained from male and female subjects during walking, slow jogging, jogging and running on an indoor platform. BACKGROUND: Previous studies have established GRF descriptor variables for male subjects running at speeds from 3 to 6 m s(-1), but very little descriptive data exists for slower or faster running, nor have previous studies reported GRF descriptors separately for female subjects. METHODS: GRF-time histories were recorded for 13 male and 10 female recreational athletes during walking and slow jogging at speeds between 1.5 and 3.0 m s(-1), and running at speeds between 3.5 and 6.0 m s(-1). Vertical GRF-time data for trials with speeds within 0.2 m s(-1) of the prescribed speed were analysed to determine thrust maximum GRF (F(z)) and loading rate (G(z)). RESULTS: In both male and female subjects, F(z) increased linearly during walking and running from 1.2 BW to approximately 2.5 BW at 6.0 m s(-1), remaining constant during forward lean sprinting at higher speeds. F(z) was linearly correlated to G(z), the latter ranging from 8 to 30 BW s(-1) over this speed range. Slow jogging was associated with a > 50% higher F(z) and G(z) in comparison to walking or fast running. CONCLUSIONS: Similar GRF descriptor data and velocity relationships were obtained for male and female subjects. Impact forces were greatest when the subjects adopted a higher, less fixed centre of gravity during slow jogging. RELEVANCE: These results suggest that vertical GRF norms can be established for male and female subjects alike, and that slow or fast running with a lower, fixed centre of gravity decreases impact forces.
Article
Tibial stress fractures (TSF) are among the most serious running injuries, typically requiring 6-8 wk for recovery. This cross-sectional study was conducted to determine whether differences in structure and running mechanics exist between trained distance runners with a history of prior TSF and those who have never sustained a fracture. Female runners with a rearfoot strike pattern, aged between 18 and 45 yr and running at least 32 km.wk(-1), were recruited for this study. Participants in the study were 20 subjects with a history of TSF and 20 age- and mileage-matched control subjects with no previous lower extremity bony injuries. Kinematic and kinetic data were collected during overground running at 3.7 m.s(-1) using a six-camera motion capture system, force platform, and accelerometer. Variables of interest were vertical impact peak, instantaneous and average vertical loading rates, instantaneous and average loading rates during braking, knee flexion excursion, ankle and knee stiffness, and peak tibial shock. Tibial varum was measured in standing. Tibial area moment of inertia was calculated from tibial x-ray studies for a subset of runners. The TSF group had significantly greater instantaneous and average vertical loading rates and tibial shock than the control group. The magnitude of tibial shock predicted group membership successfully in 70% of cases. These data indicate that a history of TSF in runners is associated with increases in dynamic loading-related variables.