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Postural reconfiguration and cycle-to-cycle variability in patients with work-related musculoskeletal disorders compared to healthy controls and in relation to pain emerging during a repetitive movement task
Abstract
Background:
Movement variability in sustained repetitive tasks is an important factor in the context of work-related musculoskeletal disorders. While a popular hypothesis suggests that movement variability can prevent overuse injuries, pain evolving during task execution may also cause variability. The aim of the current study was to investigate, first, differences in movement behavior between volunteers with and without work-related pain and, second, the influence of emerging pain on movement variability.
Methods:
Upper-body 3D kinematics were collected as 22 subjects with musculoskeletal disorders and 19 healthy volunteers performed a bimanual repetitive tapping task with a self-chosen and a given rhythm. Three subgroups were formed within the patient group according to the level of pain the participants experienced during the task. Principal component analysis was applied to 30 joint angle coordinates to characterize in a combined analysis the movement variability associated with reconfigurations of the volunteers' postures and the cycle-to-cycle variability that occurred during the execution of the task.
Findings:
Patients with no task-related pain showed lower cycle-to-cycle variability compared to healthy controls. Findings also indicated an increase in movement variability as pain emerged, manifesting both as frequent postural changes and large cycle-to-cycle variability.
Interpretation:
The findings suggested a relationship between work-related musculoskeletal disorders and movement variability but further investigation is needed on this issue. Additionally, the findings provided clear evidence that pain increased motor variability. Postural reconfigurations and cycle-to-cycle variability should be considered jointly when investigating movement variability and musculoskeletal disorders.
... Acceleration data were divided with the first touch screen signal so that each cycle had one profile. After that, the mean of the standard deviation of 40 cycles was calculated and converted into a kinematic variability (KV) value representing one bin (Longo et al., 2018b). And the Euclidean norm of three axis variabilities was calculated for each sensor so that a total of 3 KVs were used (KV LA , KV UA , and KV TR representing the lower, upper arm, and trunk, respectively). ...
... All the measured values are decomposed into several principal components that represent the complete movements, and the LLE can be calculated with those values to evaluate the movement stability (Daffertshofer et al., 2004). Longo et al. (2018b) constructed the state space for local dynamic stability using only the first principal component of the measured values representing motion. However, we wanted to include more principal components and increase the degree to which they represent the entire data. ...
Sustained shoulder abduction, which results from an inappropriate worktable height or tool shape and long task hours, leads to an accumulation of muscle fatigue and subsequent work-related injuries in workers. It can be alleviated by controlling the table height or ergonomic tool design, but workers who are doing some types of work that require a discomfortable posture, such as minimally invasive surgery, cannot avoid these situations. Loads to the shoulder joint or muscles result in several problems, such as muscle fatigue, deterioration of proprioception or changing movement strategies of the central nervous system, and these are critical to work that requires a high accuracy of the upper extremities. Therefore, in this paper, we designed and conducted an experiment with human participants to discuss how an inappropriate height of the work-table affects the task performance of workers who are performing a fine manipulative task that requires high accuracy of the end point. We developed an apparatus that can control the height and has four touch screens to evaluate the end-point accuracy with two different heights. Eighteen adults (9 women and 9 men) participated in the experiments, and the electromyography of their shoulder muscles, their movement stability, and task performance were measured for the analysis. We found that inappropriate height of a table brings about muscle fatigue, and time elapsed for conducting tasks accelerated the phenomenon. Task performance deteriorated according to increased fatigue, and improved movement stability is not enough to compensate for these situations.
... Several studies evaluating movement variability have been reported, which include methods based on approximate or sample entropy (Madeleine and Madsen, 2009), nonlinear dynamics (Stergiou & Decker, 2011), angle-angular velocity phase plots (Wagner, Pfusterschmied, Klous, von Duvillard, & Müller, 2012), and goal equivalent manifolds (Cusumano & Dingwell, 2013;Sedighi & Nussbaum, 2017). Longo, Meulenbroek, Haid, and Federolf (2018) reported that principal component analysis (PCA) is a suitable method for detecting movement variability and identifying changes in postural configuration. However, these methods cannot evaluate the time-varying movement variability. ...
... Thus, the results of the proposed method suggest that the movement of the shoulder joint differs from that of the elbow joint in terms of decreasing the effect of muscle fatigue during repetitive tasks. Longo et al. (2018) suggested that PCA is a suitable method for detecting motor variability and identifying changes in postural configuration. Compared with PCA, SVD can generally be considered as an equivalent method of mathematical processing. ...
This study proposes a new calculation method for the anomaly score of repetitive tasks based on singular spectrum transformation (SST) that accounted for a long‐term history of human motion. To validate the efficacy of the proposed method, the calculated anomaly score was compared with movement variability computed by a traditional method and to its SST‐computed score. Eleven male participants performed repetitive lightweight material handling tasks under different work conditions and an electromagnetic tracking system measured their working posture. Movement variability and anomaly score on the shoulder and elbow joints were calculated based on measured working postures. The movement variability on the elbow flexion angle increased with time. In contrast, the anomaly score of the elbow flexion angle decreased with time, but shoulder flexion and inner rotation angles showed increased scores with the passage of time. These findings are similar to those of previous studies that stated that movement variability increased from redundant degrees of freedom available for performing multi‐joint movements; this occurred due to the development of muscle fatigue on the shoulder joint from performing repetitive tasks. On comparing this to the anomaly scores calculated by conventional SST, it was observed that the score computed by the proposed method reflected the whole trend of human motion in repetitive tasks and did not depend on local problems in working posture. Therefore, it was concluded that the new method of calculating the anomaly score is more suitable to detect changes in movement variability in repetitive tasks.
... The data for the current technical note was taken from a previously reported study (Longo et al., 2018b). In brief, nineteen healthy participants [12 females; age 30y (SD: 10.1y)] performed repetitive tapping movements for 15 min between two pairs of targets displayed on a touchscreen (ProLiteIiyama, Iiyama Corpora-tion, Tokyo, Japan). ...
... In brief, nineteen healthy participants [12 females; age 30y (SD: 10.1y)] performed repetitive tapping movements for 15 min between two pairs of targets displayed on a touchscreen (ProLiteIiyama, Iiyama Corpora-tion, Tokyo, Japan). This earlier study proved that PCA is a useful tool in investigating the relationship between postural reconfigurations and pain emerging during the repetitive task (Longo et al., 2018b). All participants provided written informed consent and the study was approved by an institutionalized ethics review board (ECSW2016-2006. ...
Human movements, recorded through kinematic data, can be described by means of principal component analysis (PCA) through a small set of variables representing correlated segment movements. The PC-eigenvectors then form a basis in the associated vector space of postural changes. Similar to 3D movements, the kinematics in this posture space can be quantified through ‘principal’ positions (PPs), velocities (PVs) and accelerations (PAs). The PAs represent a novel set of variables characterizing neuro-muscular control. The aim of the current technical note was to (i) compare the variance explained by PAs with the variance explained by PPs; (ii) clarify the relationship between PAs and segment accelerations; and (iii) compare variability of the first principal acceleration (PA1) with the local dynamic stability (largest Lyapunov exponent, LyE) of the first principal position (PP1). A PCA was applied on 3D upper-body positions collected by an Xsens inertial sensor system as nineteen volunteers performed a bimanual repetitive tapping task. The main finding revealed that the PP-explained variance considerably differed from the PA-explained variance, indicating that the latter should be considered when reducing the dimensionality in postural movement analysis through a PCA. Further, the current study formally established that the acceleration curves obtained from differentiating segment positions and from linear combinations of PAs are identical. Finally, a strong correlation, r(17)=0.92, p<0.001, was observed between the cycle-to-cycle variability in PA1 and the LyE calculated for PP1, supporting the notion that PA variability and LyE share some of the information they provide about movement control.
... Therefore, it is crucial to understand the motor control of workers who sit for extended periods of time. One potential solution is to use inertial sensors that are embedded in smartphones to monitor these workers [29][30][31][32][33]. The present work is part of the Prevention of Occupational Disorders in Public Administration based on the Artificial Intelligence (PrevOccupAI) project. ...
Chronic spinal pain (CSP) is a prevalent condition, and prolonged sitting at work can contribute to it. Ergonomic factors like this can cause changes in motor variability. Variability analysis is a useful method to measure changes in motor performance over time. When performing the same task multiple times, different performance patterns can be observed. This variability is intrinsic to all biological systems and is noticeable in human movement. This study aims to examine whether changes in movement variability and complexity during real-time office work are influenced by CSP. The hypothesis is that individuals with and without pain will have different responses to office work tasks. Six office workers without pain and ten with CSP participated in this study. Participant's trunk movements were recorded during work for an entire week. Linear and nonlinear measures of trunk kinematic displacement were used to assess movement variability and complexity. A mixed ANOVA was utilized to compare changes in movement variability and complexity between the two groups. The effects indicate that pain-free participants showed more complex and less predictable trunk movements with a lower degree of structure and variability when compared to the participants suffering from CSP. The differences were particularly noticeable in fine movements.
... The number of times that the checks needs to be made varies and is dependent on the visitors of the establishment. This creates the repetitive and monotonous task that needs to be performed for long periods of time [4]. Thermal cameras are a good means of intervention, the drawback is the high investment cost especially if the establishment has several numbers of entrances. ...
Living in the “new-normal” world, the non-contact infrared temperature checks is expected to remain until such time that the
treatment and vaccine against COVID-19 becomes available worldwide. Changing the mindset of the people is also a huge factor toconsider in order to feel comfortable again without wearing a mask or conducting such pre-cautions. This paper aims to identify the relationship of the health and environmental factors to the discomfort that the person conducting the checks experience. The case study was done using the data gathered in the interviews, surveys, Cornell Musculoskeletal Discomfort Questionnaires (CMDQ), conducted Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) analysis. Minitab 18 was used to derived the correlation between the age, height, shifts, number of guests checked, RULA and REBA score to the discomfort experienced by the participants, using statistical analysis. This study will provide simple ideas that should help improve the staff welfare while performing the monotonous task. One of its objectives is to provide information on how to reduce the discomfort. It is also hoped that this study can serve as a reference in resolving similar tasks that promotes Musculoskeletal Disorders (MSDs). It aims to open up ideas on reducing the risks related to other new activities that are being performed in relation to this pandemic.
... Furthermore, such a tool could help to explain the above reported inconsistencies in the role of height in balance control. In this light, we reason that a potentially more useful method for examining postural control strategies is the analysis of 3D kinematic movement data through a principle component analysis (PCA) [32][33][34][35]. Recent studies successfully used PCA-determined variables to provide insight into principal movement strategies during standing balance tasks with a specific focus on the number of interventions that the postural control system deploys in each movement dimension to maintain balance. ...
A phenomenon called adolescent awkwardness is believed to alter motor control, but underlying mechanisms remain largely unclear. Since adolescents undergo neurological and anthropometrical changes during this developmental phase, we hypothesized that adolescents control their movements less tightly and use a different coordinative structure compared to adults. Moreover, we tested if emerging differences were driven by body height alterations between age groups. Using 39 reflective markers, postural movements during tandem stance with eyes open and eyes closed of 12 adolescents (height 168.1 ± 8.8 cm) and 14 adults were measured, in which 9 adults were smaller or equal than 180 cm (177.9 ± 3.0 cm) and 5 taller or equal than 190 cm (192.0 ± 2.5 cm). A principal component analysis (PCA) was used to extract the first nine principal movement components (PMk). The contribution of each PMk to the overall balancing movement was determined according to their relative variance share (rVARk) and tightness of motor control was examined using the number of times that the acceleration of each PMk changed direction (Nk). Results in rVARk did not show significant differences in coordinative structure between adolescents and adults, but Nk revealed that adolescents seem to control their movements less tightly in higher-order PMk, arguably due to slower processing times and missing automatization of postural control or potential increases in exploration. Body height was found to not cause motor control differences between age groups.
... For that purpose, a special suit with integrated IMU sensors was used. This kind of technology was used in sports (Lintmeijer et al., 2018,) and medicine (Held et al., 2018, Longo et al., 2018, Karatsidis et al. 2019. It is assumed that observed values for upper limb angles and kinematics, trunk torsion and body center of mass will significantly differ between two forest cleaning methods. ...
The main tool used in a forest cleaning is a billhook, a hand tool consisting of a hold and a hooked blade sharpened on both sides. Forest cleaning is physically very tiring and takes place under difficult working conditions (high temperature and humidity, dense vegetation, insects). Moreover, working with billhook is exclusively manual work and its effects on health are mostly unknown. A novelty in Croatia, regarding motor-manual forest cleaning, are battery shears, a more ergonomic and humane approach to forest cleaning. For the purpose of the ergonomic comparison of the two types of forest cleaning methods, a top technology was used-Xsens MVN. Xsens technology consists of sophisticated hardware and software for human movement analysis. It is a full-body human measurement system based on inertial sensors, biomechanical models, and sensor fusion algorithms. The aim of this paper is to present a new and modern method of movement analysis in ongoing research of two mentioned forest cleaning methods, to show challenges of field measurements, and to assume possible application in forestry regarding ergonomic measurements.
... MV is now often considered as a regulator of motion 4 to increase flexibility and adaptability 5 ; therefore, Latash 6 termed these variations the "principle of abundance" rather than a "problem of redundancy". There may be an optimal amount of MV 7 -neither too much variability nor movements that are too rigid -and some evidence even suggests that MV has a key role in preventing musculoskeletal disorders [8][9][10][11][12] and improving performance 8,13 . ...
The substantial kinematic degrees-of-freedom available in human movement lead to inherent variations in a repetitive movement, or motor variability (MV). Growing evidence suggests that characterizing MV permits a better understanding of potential injury mechanisms. Several diverse methods, though, have been used to quantify MV, but limited evidence exists regarding the merits of these methods in the occupational context. In this work, we explored different classes of methods for characterizing MV during symmetric and asymmetric box lifting tasks. Kinematic MV of both the whole-body center-of-mass (COM) and the box were quantified, using metrics derived from a linear method (Standard Deviation), a non-linear method (Sample Entropy; an index of movement regularity), and a novel application of an equifinality method (Goal Equivalent Manifold; an index related to the set of effective motor solutions). Our results suggest that individuals manipulate regularity and the set of effective motor solutions to overcome unwanted motor noises related to the COM. These results, together with earlier evidence, imply that individuals may prioritize stability over variability with increasing task difficulty. Task performance also appeared to deteriorate with decreasing variability and regularity of the COM. We conclude that diverse metrics of MV may be complimentary to reveal differences in MV.
... Over the last decade, great advancements have been made in the application of technical devices to measure physical exposure at the workplace [7][8][9][10], and current knowledge about relevant risk factors for SDEs has grown significantly. ...
Background: Work-related musculoskeletal disorders at the elbow are a common health problem, which highly impacts workers’ well-being and performance. Besides existing qualitative information, there is a clear lack of quantitative information of physical risk factors associated with specific disorders at the elbow (SDEs). Objective: To provide evidence-based quantitative measures of physical risk factors associated with SDEs. Methods: Studies were searched from 2007 to 2017 in Medline, EMBASE, and Cochrane Work. The identified risk factors were grouped in main- and sub-categories of exposure using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework for rating evidence. Results: 133 different risk-factor specifications were identified in 10/524 articles and were grouped into 5 main- and 16 sub-categories of exposure. The risk factors were significantly associated with lateral epicondylitis, medial epicondylitis, or ulnar neuropathy. Significant risk factors such as wrist angular velocity (5°/s, with increasing prevalence ratio of 0.10%/(°/s), or forearm supination (≥45° and ≥5% of time combined with forceful lifting) were found. Conclusions: This review delivers a categorization of work-related physical risk-factor specifications for SDEs with a special focus on quantitative measures, ranked for evidence. These results may build the base for developing risk assessment methods and prospective preventive measures.
View Full-Text: https://www.mdpi.com/1660-4601/16/1/130
Background
Scapular kinematics of breast cancer survivors are most often evaluated during arm elevation. However, known compensations exist during functional task performance. The purpose of this study was to determine if scapular kinematics of breast cancer survivors during arm elevation are related to scapular kinematics during functional task performance.
Methods
Scapular kinematics of 25 non-cancer controls and 25 breast cancer survivors (split by presence of impingement pain) during arm elevation in 3 planes and 3 reaching and lifting functional tasks were measured. Scapular upward rotation and scapulohumeral rhythm (SHR) at 30° increments of arm elevation were calculated. Between-group differences of upward rotation during arm elevation were evaluated with one-way ANOVAs (p < 0.05). The association of upward rotation angle and SHR during arm elevation and functional tasks was tested with Pearson correlations (p < 0.05).
Findings
Scapular upward rotation was reduced for the breast cancer survivor with pain at lower levels of arm elevation in each plane by up to 7.1° (p = .014 to 0.049). This is inconsistent with functional task results, in which upward rotation decrements occurred at higher levels of arm elevation. Upward rotation angles and SHR during arm elevation had an overall weak-to-moderate relationship (r = 0.003 to 0.970, p = .001 to 0.048) to values from functional tasks. Arm elevation during sagittal plane elevation demonstrated scapular upward rotation that was most closely associated to upward rotation during functional task performance.
Interpretation
Inconsistent relationships suggests that clinical evaluations should adopt basic functional movements for scapular motion assessment to complement simple arm elevations.
Motion analysis is used to study the functionality or dysfunctionality of the neuromuscular system, as human movements are the direct outcome of neuromuscular control. However, motion analysis often relies on measures that quantify simplified aspects of a motion, such as specific joint angles, despite the well-known complexity of segment interactions. In contrast, analyzing whole-body movement patterns may offer a new understanding of movement coordination and movement performance. Clinical research and sports technique evaluations suggest that principal component analysis (PCA) provides novel and valuable insights into control aspects of the neuromuscular system and how they relate to coordinative patterns. However, the implementation of PCA computations are time consuming, and require mathematical knowledge and programming skills, drastically limiting its application in current research. Therefore, the aim of this study is to present the Matlab software tool “PManalyzer” to facilitate and encourage the application of state-of-the-art PCA concepts in human movement science. The generalized PCA concepts implemented in the PManalyzer allow users to apply a variety of marker set independent PCA-variables on any kinematic data and to visualize the results with customizable plots. In addition, the extracted movement patterns can be explored with video options that may help testing hypotheses related to the interplay of segments. Furthermore, the software can be easily modified and adapted to any specific application.
In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations—the variability related to the volunteer’s postural change—were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.
Movement variability of the upper limb was investigated using a bimanual Fitts' task. Participants tapped rhythmically between target-pairs of different Index of Difficulties (ID) for three intervals of 20 min each. We studied the effects of ID and time-on-task on movement time, end-point variability, approximate entropy and standard deviation of relative phase. Lower ID and time-on-task caused decreasing movement time and increasing end-point variability. Moreover, standard deviation of relative phase and approximate entropy moderately increased. By looking into the long-term effects of a sustained bimanual Fitts' task, this is the first time such movement variability increase is demonstrated in multiple variability indices. The relevance of the findings for future studies on work-related musculoskeletal disorders is being discussed.
Increased movement variability has been suggested to reduce the risk of developing musculoskeletal disorders caused by repetitive work. This study investigated the effects of work pace on arm movement variability in a standardised repetitive pipetting task performed by 35 healthy women. During pipetting at slow and fast paces differing by 15%, movements of arm, hand and pipette were tracked in 3D, and used to derive shoulder and elbow joint angles. The size of cycle-to-cycle motor variability was quantified using standard deviations of several kinematics properties, while the structure of variability was quantified using indices of sample entropy and recurrence quantification analysis. When pace increased, both the size and structure of motor variability in the shoulder and elbow decreased. These results suggest that motor variability drops when repetitive movements are performed at increased paces, which may in the long run lead to undesirable outcomes such as muscle fatigue or overuse.
Marker-based human motion analysis is an important tool in clinical research and in many practical applications. Missing marker information caused by occlusions or a marker falling off is a common problem impairing data quality. The current paper proposes a conceptually new gap filling algorithm and presents results from a proof-of-principle analysis. The underlying idea of the proposed algorithm was that a multitude of internal and external constraints govern human motion and lead to a highly subject-specific movement pattern in which all motion variables are intercorrelated in a specific way. Two principal component analyses were used to determine how the coordinates of a marker with gaps correlated with the coordinates of the other, gap-free markers. Missing marker data could then be reconstructed through a series of coordinate transformations. The proposed algorithm was tested by reconstructing artificially created gaps in a 20-step walking trial and in an 18-s one-leg balance trial. The measurement accuracy's dependence on the marker position, the length of the gap, and other parameters were evaluated. Even if only 2 steps of walking or 1.8 s of postural sway (10% of the whole marker data) were provided as input in the current study, the reconstructed marker trajectory differed on average no more than 11 mm from the originally measured trajectory. The reconstructed result improved further, on average, to distances below 5 mm if the marker trajectory was available more than 50% of the trial. The results of this proof-of-principle analysis supported the assumption that missing marker information can be reconstructed from the intercorrelations between marker coordinates, provided that sufficient data with complete marker information is available. Estimating missing information cannot be avoided entirely in many situations in human motion analysis. For some of these situations, the proposed reconstruction method may provide a better solution than what is currently available.
For a successful completion of a movement task the motor control system has to observe a multitude of internal constraints that govern the coordination of its segments. The purpose of this study was to apply principal component (PC) analysis to detect differences in the segmental coordination between healthy subjects and patients with medial knee osteoarthritis (OA). It was hypothesized that (1) systematic differences in patterns of whole body movement would be identifiable with this method even in small sample sized groups and that (2) these differences will include compensatory movements in the OA patients in both the lower and upper body segments. Marker positions and ground reaction forces of three gait trials of 5 healthy and 5 OA participants with full body marker sets were analyzed using a principal component analysis. Group differences in the PC-scores were determined for the first 10 PC-vectors and a linear combination of those PC-vectors where differences were found defined a discriminant vector. Projecting the original trials onto this discriminant vector yielded significant group differences (t(d=8)=3.011; p=0.017) with greater upper body movement in patients with knee OA that was correlated with the medial-lateral ground reaction force. These results help to characterize the adaptation of whole-body gait patterns to knee OA in a relatively small population and may provide an improved basis for the development of interventions to modify knee load. The PC-based motion analysis offered a highly sensitive approach to identify characteristic whole body patterns of movement associated with pathological gait.
Several recent reviews have reported that 'repetitive movements' constitute a risk factor for occupational musculoskeletal disorders in the neck, shoulder and arm regions. More variation in biomechanical exposure is often suggested as an effective intervention in such settings. Since increasing variation using extrinsic methods like job rotation may not always be possible in an industrial context, the intrinsic variability of the motor system may offer an alternative opportunity to increase variation. Motor variability refers to the natural variation in postures, movements and muscle activity observed to different extents in all tasks. The current review discusses research appearing in motor control, sports sciences and occupational biomechanics literature to answer whether motor variability is important to consider in an occupational context, and if yes, whether it can be manipulated by training the worker or changing the working conditions so as to increase biomechanical variation without jeopardizing production. The review concludes that motor variability is, indeed, a relevant issue in occupational health and performance and suggests a number of key issues for further research.
LATASH, M.L., J.P. SCHOLZ, and G. SCHÖNER. Motor control strategies revealed in the structure of motor variability. Exerc. Sport Sci. Rev., Vol. 30, No. 1, pp 26–31, 2002. We describe an uncontrolled manifold hypothesis, which suggests a particular solution for the notorious problem of motor redundancy. A body of recent experiments supports the uncontrolled manifold hypothesis and shows its ability to discover biological strategies of the coordination of apparently redundant motor systems. The hypothesis and associated computational apparatus have great potential for application in the areas of motor rehabilitation and motor skill acquisition.
Biological motion contains information about the identity of an agent as well as about his or her actions, intentions, and emotions. The human visual system is highly sensitive to biological motion and capable of extracting socially relevant information from it. Here we investigate the question of how such information is encoded in biological motion patterns and how such information can be retrieved. A framework is developed that transforms biological motion into a representation allowing for analysis using linear methods from statistics and pattern recognition. Using gender classification as an example, simple classifiers are constructed and compared to psychophysical data from human observers. The analysis reveals that the dynamic part of the motion contains more information about gender than motion-mediated structural cues. The proposed framework can be used not only for analysis of biological motion but also to synthesize new motion patterns. A simple motion modeler is presented that can be used to visualize and exaggerate the differences in male and female walking patterns.
Objective:
To explain and underscore the use of principal component analysis in clinical biomechanics as an expedient, unbiased means for reducing high-dimensional data sets to a small number of modes or structures, as well as for teasing apart structural (invariant) and variable components in such data sets.
Design:
The method is explained formally and then applied to both simulated and real (kinematic and electromyographic) data for didactical purposes, thus illustrating possible applications (and pitfalls) in the study of coordinated movement.
Background:
In the sciences at large, principal component analysis is a well-known method to remove redundant information in multidimensional data sets by means of mode reduction. At present, principal component analysis is starting to penetrate the fundamental and clinical study of human movement, which amplifies the need for an accessible explanation of the method and its possibilities and limitations. Besides mode reduction, we discuss principal component analysis in its capacity as a data-driven filter, allowing for a separation of invariant and variant properties of coordination, which, arguably, is essential in studies of motor variability.
Methods:
Principal component analysis is applied to kinematic and electromyographic time series obtained during treadmill walking by healthy humans.
Results:
Common signal structures or modes are identified in the time series that turn out to be readily interpretable. In addition, the identified coherent modes are eliminated from the data, leaving a filtered, residual pattern from which useful information may be gleaned regarding motor variability.
Conclusions:
Principal component analysis allows for the detection of modes (information reduction) in both kinematic and electromyographic data sets, as well as for the separation of invariant structure and variance in those data sets.
Relevance:
Principal component analysis can be successfully applied to movement data, both as feature extractor and as data-driven filter. Its potential for the (clinical) study of human movement sciences (e.g., diagnostics and evaluation of interventions) is evident but still largely untapped.
In this communication, the Standardization and Terminology Committee (STC) of the International Society of Biomechanics proposes a definition of a joint coordinate system (JCS) for the shoulder, elbow, wrist, and hand. For each joint, a standard for the local axis system in each articulating segment or bone is generated. These axes then standardize the JCS. The STC is publishing these recommendations so as to encourage their use, to stimulate feedback and discussion, and to facilitate further revisions. Adopting these standards will lead to better communication among researchers and clinicians.
Kinematic variability is caused, in part, by force fluctuations. It has been shown empirically and numerically that the effects of force fluctuations on kinematics can be suppressed by increasing joint impedance. Given that force variability increases with muscular fatigue, we hypothesized that joint impedance would increase with fatigue to retain a prescribed accuracy level. To test this hypothesis, subjects tracked a target by elbow flexion and extension both with fatigued and unfatigued elbow flexor and extensor muscles. Joint impedance was estimated from controlled perturbations to the elbow. Contrary to the hypothesis, elbow impedance decreased, whereas performance, expressed as the time-on-target, was unaffected by fatigue. Further analysis of the data revealed that subjects changed their control strategy with increasing fatigue. Although their overall kinematic variability increased, task performance was retained by staying closer to the center of the target when fatigued. In conclusion, the present study reveals a limitation of impedance modulation in the control of movement variability.
The aim of the present study was to investigate the effect of experimental and chronic neck-shoulder pain on the magnitude of cycle-to-cycle variability of task timing, kinematics and muscle activation during repetitive arm movement performed for 3 or 5 min. In an experimental part, acute muscle pain was induced in healthy subjects by intramuscular injection of hypertonic saline in trapezius (n = 10) and infraspinatus (n = 10) muscles. In a clinical part, workers with (n = 12) and without (n = 6) chronic neck-shoulder pain were compared. Cycle-to-cycle standard deviations of task duration, arm and trunk movement in 3D and surface electromyographic (EMG) root mean square activity were computed to assess the degree of variability. The variability in task timing increased in presence of both experimental and chronic pain (P < 0.05) compared with non-painful conditions. Experimental pain increased the variability of the starting position of the arm (P < 0.05), the arm range of motion (P < 0.01), the arm and trunk movement area (P < 0.01) and the acceleration of the arm (P < 0.01). In the chronic pain condition, the variability of arm and trunk acceleration (P < 0.01) and EMG activity (P < 0.05) was decreased compared with healthy controls. These results indicate that pain alters the magnitude of motor variability, and that the transition from acute to chronic pain is accompanied by changes in motor patterns. Experimental pain likely resulted in a quest for a motor solution reducing nociceptive influx, while chronic pain was characterised by a diminished motor flexibility.
Background:
The relationship between gait features and coordination in children with Cerebral Palsy is not sufficiently analyzed yet. Principal Component Analysis can help in understanding motion patterns decomposing movement into its fundamental components (Principal Movements). This study aims at quantitatively characterizing the functional connections between multi-joint gait patterns in Cerebral Palsy.
Methods:
65 children with spastic diplegia aged 10.6 (SD 3.7) years participated in standardized gait analysis trials; 31 typically developing adolescents aged 13.6 (4.4) years were also tested. To determine if posture affects gait patterns, patients were split into Crouch and knee Hyperextension group according to knee flexion angle at standing. 3D coordinates of hips, knees, ankles, metatarsal joints, pelvis and shoulders were submitted to Principal Component Analysis.
Findings:
Four Principal Movements accounted for 99% of global variance; components 1-3 explained major sagittal patterns, components 4-5 referred to movements on frontal plane and component 6 to additional movement refinements. Dimensionality was higher in patients than in controls (p<0.01), and the Crouch group significantly differed from controls in the application of components 1 and 4-6 (p<0.05), while the knee Hyperextension group in components 1-2 and 5 (p<0.05).
Interpretation:
Compensatory strategies of children with Cerebral Palsy (interactions between main and secondary movement patterns), were objectively determined. Principal Movements can reduce the effort in interpreting gait reports, providing an immediate and quantitative picture of the connections between movement components.
Human upright posture is maintained by postural movements, which can be quantified by "principal movements" (PMs) obtained through a principal component analysis (PCA) of kinematic marker data. The current study expands the concept of "principal movements" in analogy to Newton's mechanics by defining "principal position" (PP), "principal velocity" (PV), and "principal acceleration" (PA) and demonstrates that a linear combination of PPs and PAs determines the center of pressure (COP) variance in upright standing. Twenty-one subjects equipped with 27-markers distributed over all body segments stood on a force plate while their postural movements were recorded using a standard motion tracking system. A PCA calculated on normalized and weighted posture vectors yielded the PPs and their time derivatives, the PVs and PAs. COP variance explained by the PPs and PAs was obtained through a regression analysis. The first 15 PMs quantified 99.3% of the postural variance and explained 99.60%±0.22% (mean±SD) of the anterior-posterior and 98.82±0.74% of the lateral COP variance in the 21 subjects. Calculation of the PMs thus provides a data-driven definition of variables that simultaneously quantify the state of the postural system (PPs and PVs) and the activity of the neuro-muscular controller (PAs). Since the definition of PPs and PAs is consistent with Newton's mechanics, these variables facilitate studying how mechanical variables, such as the COP motion, are governed by the postural control system.
The log transformation has been widely used in biomedical research to deal with the skewed data. However, in the medical publications, we have found many misuses and misinterpretations of analysis based on log-transformed data. In this paper, we list some common scenarios of misuse and misinterpretation of log transformation in biomedical applications. We also provide both theoretical and practical justifications to support our viewpoints. Copyright © 2012 John Wiley & Sons, Ltd.
Movement variability has become an important field of research and has been studied to gain a better understanding of the neuro-muscular control of human movements. In addition to studies investigating "amplitude variability" there are a growing number of studies assessing the "temporal variability" in movements by applying non-linear analysis techniques. One limitation of the studies available to date is that they quantify variability features in specific, pre-selected biomechanical or physiological variables. In many cases it remains unclear if and to what degree these pre-selected variables quantify characteristics of the whole body movement. This technical note proposes to combine two analysis techniques that have already been applied for gait analysis in order to quantify variability features in walking with variables whose significance for the whole movements are known. Gait patterns were recorded using a full-body marker set on the subjects whose movements were captured with a standard motion tracing system. For each time frame the coordinates of all markers were interpreted as a high-dimensional "posture vector". A principal component analysis (PCA) conducted on these posture vectors identified the main one-dimensional movement components of walking. Temporal variability of gait was then quantified by calculating the maximum Lyapunov Exponent (LyE) of these main movement components. The effectiveness of this approach was demonstrated by determining differences in temporal variability between walking in unstable shoes and walking in a normal athletic-type control shoe. Several additional conceptual and practical advantages of this combination of analysis methods were discussed.
Fields studying movement generation, including robotics, psychology, cognitive science, and neuroscience utilize concepts and tools related to the pervasiveness of variability in biological systems. The concept of variability and the measures for nonlinear dynamics used to evaluate this concept open new vistas for research in movement dysfunction of many types. This review describes innovations in the exploration of variability and their potential importance in understanding human movement. Far from being a source of error, evidence supports the presence of an optimal state of variability for healthy and functional movement. This variability has a particular organization and is characterized by a chaotic structure. Deviations from this state can lead to biological systems that are either overly rigid and robotic or noisy and unstable. Both situations result in systems that are less adaptable to perturbations, such as those associated with unhealthy pathological states or absence of skillfulness.
Repetitive movements are common to many daily activities but often lead to the development of fatigue. We have previously shown that fatigue leads to changes in tridimensional spatial characteristics of the whole body. However, temporal aspects of these posture and movement adaptations have yet to be investigated. Healthy subjects (N = 14) performed a continuous reaching task by pointing between two targets placed at shoulder height, at 100 and 30% arm's length, anterior to the subject's midline until fatigue (assessed using the Borg CR-10 scale). Whole body kinematics and upper Trapezius EMG were recorded and analyzed at 1-min intervals to document the progression of fatigue on outcome variables. For all upper limb and postural variables analyzed, changes began to occur approximately midway to fatigue and were followed by an increase in Trapezius activity from baseline. Reach-to-reach variability of joint average positions and range of motion (ROM) increased in multiple directions for shoulder and elbow parameters. Reach-to-reach variability of the center-of-mass ROM also increased in several directions. Changes were also observed in within-movement inter-segmental timing. The peak velocities of elbow and endpoint occurred closer together in time during fatigue while the shoulder peak velocity occurrence showed a greater reach-to-reach variability. Our results suggest that the effects of fatigue on repetitive movement kinematics can be observed across three temporal dimensions of the task: (1) within individual movements, (2) from one movement to the next, and (3) as fatigue develops. Each observed change is discussed as a potential contributor to task-specific control strategies to prolong task performance.
In this field study, the size and structure of kinematics variability were assessed in relation to experience and discomfort during a deboning task. Eighteen workers divided in groups with low/high experience and with/without neck-shoulder discomfort participated. Standard deviation and coefficient of variation (amount of variability), as well as approximate entropy and sample entropy (complexity) and, correlation dimension (dimensionality) were computed for head-shoulder, shoulder-hip and elbow-hip displacement in the vertical direction. A longer work experience was associated with shorter work cycle duration and decreased amount of variability while complexity increased for the head-shoulder displacement, P<0.05. Shorter work cycle, lower amount of variability and, lower dimensionality for the head-shoulder displacement were found in relation to discomfort, P<0.05. While the amount of variability, complexity and dimensionality increased for the elbow-hip displacement, P<0.05. These findings suggest a functional role of experience via learning effects and discomfort through compensatory mechanisms on the size and structure of motor variability.
The logarithmic (log) transformation is a simple yet controversial step in the analysis of positive continuous data measured on an interval scale. Situations where a log transformation is indicated will be reviewed. This paper contends that the log transformation should not be classed with other transformations as it has particular advantages. Problems with using the data themselves to decide whether or not to transform will be discussed. It is recommended that log transformed analyses should frequently be preferred to untransformed analyses and that careful consideration should be given to use of a log transformation at the protocol design stage.
The nature of work-related musculoskeletal disorders of the neck and upper limbs is reviewed using both scientific data and the consensus view of experts, union bodies and government agencies across the European Union. Work-related musculoskeletal disorders describe a wide range of inflammatory and degenerative diseases and disorders. These conditions result in pain and functional impairment and may affect, besides others, the neck, shoulders, elbows, forearms, wrists and hands. They are work-related when the work activities and work conditions significantly contribute to their development or exacerbation but are not necessarily the sole determinant of causation. The classification and the need for standardised diagnostic methods for assessment of neck and upper limb musculoskeletal disorders are reviewed. These disorders are a significant problem within the European Union with respect to ill health, productivity and associated costs. The pathomechanisms of musculoskeletal disorders affecting tendons, ligaments, nerves, muscle, circulation and pain perception are reviewed and conceptual models for the pathogenesis of musculoskeletal disorders affecting the neck and upper limbs are presented. The epidemiological evidence on the work-relatedness of these disorders is discussed. A relationship between the performance of work and the occurrence of neck and upper limb musculoskeletal disorders is evident. Intervention strategies in the workplace for the reduction of both exposure and effect should focus upon factors within the work organisation as well as actively involving the individual worker. The current knowledge is sufficient to enable informed decisions to be made on future research needs and prevention strategies at the societal, organisational and individual level.
Work-related musculo-skeletal disorders have been previously related to movement repetition, inadequate postures, non-ergonomic environments, muscular imbalance and fatigue. However, no direct link between fatigue and injury has been experimentally shown. To address this problem, we compared the effects of fatigue and injury on the kinematics of repetitive hammering.
Healthy subjects (n=30) hammered repetitively both before and after fatigue. Fatigue was induced by a combination of static and dynamic procedures. Shoulder-injured subjects (n=15) hammered for 30s without fatigue. Kinematics of motion was recorded.
The movement time and shoulder range of motion during hammering were not affected by either fatigue or shoulder injury. When fatigued, the healthy subjects displayed decreased range of joint motion, peak velocity and peak acceleration of elbow motion during hammering as well as reduced grip strength. Shoulder-injured individuals had a smaller hammer trajectory amplitude than healthy controls with or without fatigue. They also had lower wrist range of motion, elbow peak velocity, and peak wrist and elbow acceleration compared to healthy subjects hammering without fatigue but only lower wrist peak acceleration compared to healthy subjects hammering with fatigue.
Results showed that fatigue affects elbow motion while shoulder injury affects both wrist and elbow motions during hammering. However, shoulder kinematics were not changed by either fatigue or shoulder injury. These changes at the wrist and elbow may reflect strategies used by individuals with shoulder injury to maintain constant movement duration and shoulder kinematics during movement.
This paper overviews the importance for sports biomechanics of movement variability, which has been studied for some time by cognitive and ecological motor skills specialists but, until quite recently, had somewhat been overlooked by sports biomechanists. The paper considers biomechanics research reporting inter- and intra-individual movement variability in javelin and discus throwing, basketball shooting, and locomotion. The overview does not claim to be comprehensive and we exclude such issues as the theoretical background to movement and coordination variability and their measurement. We overview evidence, both theoretical and empirical, of inter-individual movement variability in seeking to achieve the same task goal, in contrast to the concept of "optimal" movement patterns. Furthermore, even elite athletes cannot reproduce identical movement patterns after many years of training, contradicting the ideas of motor invariance and "representative" trials. We contend that movement variability, far from being solely due to neuromuscular system or measurement "noise"--as sports biomechanists may have previously supposed--is, or could be, functional. Such functionality could allow environmental adaptations, reduce injury risk, and facilitate changes in coordination patterns. We conclude by recommending that sports biomechanists should focus more of their research on movement variability and on important related topics, such as control and coordination of movement, and implications for practice and skill learning.
Fatigue affects the capacity of muscles to generate forces and is associated with characteristic changes in EMG signals. It may also influence interjoint and intermuscular coordination. To understand better the global effects of fatigue on multijoint movement, we studied movement kinematics and EMG changes in healthy volunteers asked to hammer repetitively. Movement kinematics and the activity of 20 muscles of the arm, trunk, and leg were recorded before and after subjects became fatigued (as measured using a Borg scale). When fatigue was reached, maximal grip strength and elbow range of motion decreased while the EMG amplitude of the contralateral external oblique muscle was increased. Fatigue did not affect shoulder and wrist kinematics or movement frequency. Results suggest that fatigue influences motion at both local and global levels. Specifically, interjoint and intermuscular coordination adapt to compensate for local effects of fatigue and to maintain key movement characteristics, such as the trajectory of the end effector and the movement frequency. Nonlocal compensations may be a focus of future studies of how fatigue affects complex movements such as those typically performed in the workplace.