0000000000771087
AUTHOR
Fabian Horst
Revealing the unique features of each individual’s muscle activation signatures
AbstractThere is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear Support Vector Machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision making by the machine learning classification model, a Layer-wise Relevance Propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance scores for each i…
Explaining the unique nature of individual gait patterns with deep learning
Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases this comes with the disadvantage of acting as a black box, rarely providing information about what made them arrive at a particular prediction. This black box aspect of ML techniques can be problematic especially in medical diagnoses, so far hampering a clinical acceptance. The present paper studies the uniqueness of individual gait patterns in clinical biomechanics using DNNs. By attributing portions of the model predictions back to the input …
Fatigue-related changes in technique emerge at different timescales during repetitive training
Training consisting of numerous repetitions performed as closely as possible to ideal techniques is common in sports and every-day tasks. Little is known about fatigue-related technique changes that emerge at different timescales when repeating complex actions such as a karate front kick. Accordingly, 15 karatekas performed 600 kicks (1 pre-block and 9 blocks). The pre-block comprised 6 kicks (3 with each leg) at maximum intensity (K-100%). Each block comprised 60 kicks (10 with each leg) at 80% of their self-perceived maximum intensity (K-80%) plus 6 K-100%. In between blocks, the participants rested for 90 seconds. Right leg kinematics (peak joint angles, peak joint angular velocities, pe…
Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector Machine
The scientific and practical fields—especially high-performance sports—increasingly request a stronger focus be placed on individual athletes in human movement science research. Machine learning methods have shown efficacy in this context by identifying the unique movement patterns of individuals and distinguishing their intra-individual changes over time. The objective of this investigation is to analyze biomechanically described movement patterns during the fatigue-related accumulation process within a single training session of a high number of repeated executions of a ballistic sports movement—specifically, the frontal foot kick (mae-geri) in karate—in expert athletes. The two leading r…
Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people
Abstract Background Gait disorders are major symptoms of neurological diseases affecting the quality of life. Interventions that restore walking and allow patients to maintain safe and independent mobility are essential. Robot-assisted gait training (RAGT) proved to be a promising treatment for restoring and improving the ability to walk. Due to heterogenuous study designs and fragmentary knowlegde about the neural correlates associated with RAGT and the relation to motor recovery, guidelines for an individually optimized therapy can hardly be derived. To optimize robotic rehabilitation, it is crucial to understand how robotic assistance affect locomotor control and its underlying brain act…
Electrical Brain Activity and Its Functional Connectivity in the Physical Execution of Modern Jazz Dance
Besides the pure pleasure of watching a dance performance, dance as a whole-body movement is becoming increasingly popular for health-related interventions. However, the science-based evidence for improvements in health or well-being through dance is still ambiguous and little is known about the underlying neurophysiological mechanisms. This may be partly related to the fact that previous studies mostly examined the neurophysiological effects of imagination and observation of dance rather than the physical execution itself. The objective of this pilot study was to investigate acute effects of a physically executed dance with its different components (recalling the choreography and physical …
One-year persistence of individual gait patterns identified in a follow-up study – A call for individualised diagnose and therapy
Abstract Although a hunch about the individuality of human movements generally exists, differences in gait patterns between individuals are often neglected. To date, only a few studies distinguished individual gait patterns in terms of uniqueness and emphasised the relevance of individualised diagnoses and therapy. However, small sample sizes have been a limitation on identifying subjects based on gait patterns, and little is known about the permanence of subject-specific characteristics over time. The purpose of this study was (1) to prove the uniqueness of individual gait patterns within a larger sample and (2) to prove the long-term permanence of individual gait patterns. A sample of 128…
MOESM1 of Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people
Additional file 1: Figure S1. Normalized vertical ground reaction force (GRF; mean) during the stance phase of unassisted walking (UAW) for each individual participant. Figure S2. Normalized vertical ground reaction force (GRF; mean) during the stance phase of robot-assisted walking (RAW) for each individual participant.
Revealing the unique features of each individual's muscle activation signatures
International audience; There is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures, however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear support vector machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision-making by the machine learning classification model, a layer-wise relevance propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance …
Daily changes of individual gait patterns identified by means of support vector machines.
Despite the common knowledge about the individual character of human gait patterns and about their non-repeatability, little is known about their stability, their interactions and their changes over time. Variations of gait patterns are typically described as random deviations around a stable mean curve derived from groups, which appear due to noise or experimental insufficiencies. The purpose of this study is to examine the nature of intrinsic inter-session variability in more detail by proving separable characteristics of gait patterns between individuals as well as within individuals in repeated measurement sessions. Eight healthy subjects performed 15 gait trials at a self-selected spee…
Can Individual Movement Characteristics Across Different Throwing Disciplines Be Identified in High-Performance Decathletes?
Although the individuality of whole-body movements has been suspected for years, the scientific proof and systematic investigation that individuals possess unique movement patterns did not manifest until the introduction of the criteria of uniqueness and persistence from the field of forensic science. Applying the criteria of uniqueness and persistence to the individuality of motor learning processes requires complex strategies due to the problem of persistence in the learning processes. One approach is to examine the learning process of different movements. For this purpose, it is necessary to differentiate between two components of movement patterns: the individual-specific component and …
A public dataset of overground walking kinetics in healthy individuals
The dataset comprises raw kinetic data (both in .mat and .txt) of 128 healthy subjects (52 female, 76 male; M age: 23.8 years, SD 9.1; M body height: 1.76 m, SD 0.08; M body mass: 71.3 kg, SD 13.0; M body mass index: 22.9 kg/m², SD 2.8; M gait speed: 1.33 m/s, SD 0.13) during overground walking. All subjects met the inclusion criteria, which meant that during the study, they were free of lower extremity pain or injuries. In addition, before and during the study, they were free of any gait pathology. The .mat-file 'gait_grf_subject.mat' includes six 128x1 double variables containing one row value for each of the 128 subjects: subject_id [number] subject_gender [1 = "female" ; 0 ="male"] subj…