3D gait analysis in children using wearable sensors: feasibility of predicting joint kinematics and kinetics with personalized machine learning models and inertial measurement units.

Introduction: Children's walking patterns evolve with age, exhibiting less repetitiveness at a young age and more variability than adults. Three-dimensional gait analysis (3DGA) is crucial for understanding and treating lower limb movement disorders in children, traditionally performed using Optical Motion Capture (OMC). Inertial Measurement Units (IMUs) offer a cost-effective alternative to OMC, although challenges like drift errors persist. Machine learning (ML) models can mitigate these issues in adults, prompting an investigation into their applicability to a heterogeneous pediatric population. This study aimed at 1) quantifying personalized and generalized ML models' performance for predicting gait time series in typically developed (TD) children using IMUs data, 2) Comparing random forest (RF) and convolutional neural networks (CNN) models' performance, 3) Finding the optimal number of IMUs required for accurate predictions. Methodology: Seventeen TD children, aged 6 to 15, participated in data collection involving OMC, force plates, and IMU sensors. Joint kinematics and kinetics (targets) were computed from OMC and force plates' data using OpenSim. Tsfresh, a Python package, extracted features from raw IMU data. Each target's ten most important features were input in the development of personalized and generalized RF and CNN models. This procedure was initially conducted with 7 IMUs placed on all lower limb segments and then performed using only two IMUs on the feet. Results: Findings suggested that the RF and CNN models demonstrated comparable performance. RF predicted joint kinematics with a 9.5% and 19.9% NRMSE for personalized and generalized models, respectively, and joint kinetics with an NRMSE of 10.7% for personalized and 15.2% for generalized models in TD children. Personalized models provided accurate estimations from IMU data in children, while generalized models lacked accuracy due to the limited dataset. Furthermore, reducing the number of IMUs from 7 to 2 did not affect the results, and the performance remained consistent. Discussion: This study proposed a promising personalized approach for gait time series prediction in children, involving an RF model and two IMUs on the feet.

Shape-model scaling is more robust than linear scaling to marker placement error.

When reconstructing bone geometry to calculate joint kinematics, shape-model scaling can be more accurate and repeatable than linear scaling given the same anatomical landmarks. This study perturbed anatomical landmarks from optical motion capture and determined the robustness of shape-model scaling to misplaced markers compared to a traditional approach of linear scaling. We hypothesised that shape-model scaling would be less susceptible to variance in marker positions compared to linear scaling. The positions of hip joint centres and femoral/tibial segment lengths across perturbations were compared to determine each scaling method's range of geometric variation. The standard deviation (SD) of the hip joint centre location from the shape model had a maximum of 1.4 mm, compared to 4.2 mm for linear scaling. Femoral and tibial segments displayed SD's of 5.4 mm and 5.2 mm when shape-model scaled, compared to 9.2 mm and 9.5 mm with linear scaling, respectively, thus supporting our hypothesis. Geometric constraints within a shape model provide robustness to marker misplacement providing potential improvements in repeatability and data exchange.

Muscle synergies are associated with intermuscular coherence and cortico-synergy coherence in an isometric upper limb task.

To elucidate the underlying physiological mechanisms of muscle synergies, we investigated long-range functional connectivity by cortico-muscular (CMC), intermuscular (IMC) and cortico-synergy (CSC) coherence. Fourteen healthy participants executed an isometric upper limb task in synergy-tuned directions. Cortical activity was recorded using 32-channel electroencephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorisation (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy-preferred directions (PDs). A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Overall, we were able to identify four different synergies from the multidirectional task. A significant alpha band IMC was consistently present in all extracted synergies. Moreover, IMC alpha band was higher between muscles with higher weights within a synergy. Interestingly, CSC alpha band was also significantly higher across muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. The presence of a shared input onto synergistic muscles within a synergy supports the idea of neurally derived muscle synergies that build human movement. Our findings suggest cortical modulation of some of the synergies and the consequential existence of shared input between muscles within cortically modulated synergies.

Effects of arm weight support on neuromuscular activation during reaching in chronic stroke patients.

To better understand how arm weight support (WS) can be used to alleviate upper limb impairment after stroke, we investigated the effects of WS on muscle activity, muscle synergy expression, and corticomotor excitability (CME) in 13 chronic stroke patients and 6 age-similar healthy controls. For patients, lesion location and corticospinal tract integrity were assessed using magnetic resonance imaging. Upper limb impairment was assessed using the Fugl-Meyer upper extremity assessment with patients categorised as either mild or moderate-severe. Three levels of WS were examined: low = 0, medium = 50 and high = 100% of full support. Surface EMG was recorded from 8 upper limb muscles, and muscle synergies were decomposed using non-negative matrix factorisation from data obtained during reaching movements to an array of 14 targets using the paretic or dominant arm. Interactions between impairment level and WS were found for the number of targets hit, and EMG measures. Overall, greater WS resulted in lower EMG levels, although the degree of modulation between WS levels was less for patients with moderate-severe compared to mild impairment. Healthy controls expressed more synergies than patients with moderate-severe impairment. Healthy controls and patients with mild impairment showed more synergies with high compared to low weight support. Transcranial magnetic stimulation was used to elicit motor-evoked potentials (MEPs) to which stimulus-response curves were fitted as a measure of corticomotor excitability (CME). The effect of WS on CME varied between muscles and across impairment level. These preliminary findings demonstrate that WS has direct and indirect effects on muscle activity, synergies, and CME and warrants further study in order to reduce upper limb impairment after stroke.

Fatigue Influences the Recruitment, but Not Structure, of Muscle Synergies.

The development of fatigue elicits multiple adaptations from the neuromuscular system. Muscle synergies are common patterns of neuromuscular activation that have been proposed as the building blocks of human movement. We wanted to identify possible adaptations of muscle synergies to the development of fatigue in the upper limb. Recent studies have reported that synergy structure remains invariant during the development of fatigue, but these studies did not examine isolated synergies. We propose a novel approach to characterise synergy adaptations to fatigue by taking advantage of the spatial tuning of synergies. This approach allows improved identification of changes to individual synergies that might otherwise be confounded by changing contributions of overlapping synergies. To analyse upper limb synergies, we applied non-negative matrix factorization to 14 EMG signals from muscles of 11 participants performing isometric contractions. A preliminary multidirectional task was used to identify synergy directional tuning. A subsequent fatiguing task was designed to fatigue the participants in their synergies' preferred directions. Both tasks provided virtual reality feedback of the applied force direction and magnitude, and were performed at 40% of each participant's maximal voluntary force. Five epochs were analysed throughout the fatiguing task to identify progressive changes of EMG amplitude, median frequency, synergy structure, and activation coefficients. Three to four synergies were sufficient to account for the variability contained in the original data. Synergy structure was conserved with fatigue, but interestingly synergy activation coefficients decreased on average by 24.5% with fatigue development. EMG amplitude did not change systematically with fatigue, whereas EMG median frequency consistently decreased across all muscles. These results support the notion of a neuromuscular modular organisation as the building blocks of human movement, with adaptations to synergy recruitment occurring with fatigue. When synergy tuning properties are considered, the reduction of activation of muscle synergies may be a reliable marker to identify fatigue.

Medial Gastrocnemius Myotendinous Junction Displacement and Plantar-Flexion Strength in Patients Treated With Immediate Rehabilitation After Achilles Tendon Repair.

CONTEXT: Pathologic plantar flexion frequently occurs after operative repair of the Achilles tendon (AT) because of immobilization and non-weight bearing in the first weeks of traditional rehabilitation. Novel rehabilitation strategies that apply mobilization and weight bearing have been proposed, but their effects on medial gastrocnemius myotendinous junction displacement (MJD) and isometric plantar-flexion strength (PFS) are unknown. OBJECTIVE: To compare the effects of 12 weeks of immediate versus traditional rehabilitation on MJD and PFS in patients with percutaneous AT repair and to compare AT rupture scores (ATRSs) during follow-up. DESIGN: Controlled laboratory study. SETTING: Human performance laboratory. PATIENTS OR OTHER PARTICIPANTS: A total of 26 amateur soccer players (age = 42.3 ± 9.7 years, body mass index = 29.5 ± 3.9 kg/m2) with percutaneous AT repair. INTERVENTION(S): Athletes were randomly divided into 2 groups: an immediate group, given physical therapy from day 1 to day 84, and a traditional group, given physical therapy from day 29 to day 84. We used repeated-measures analysis of variance to compare the data. MAIN OUTCOME MEASURE(S): We measured MJD and PFS at days 28 (fourth week), 56 (eighth week), and 84 (12th week) after AT repair. RESULTS: After 12 weeks of rehabilitation, we observed a large clinically meaningful effect and statistical difference between groups. At day 28, the immediate group showed higher values for PFS (P = .002), MJD (P = .02), and ATRS (P = .002) than the traditional group. At day 56, the immediate group presented higher values for MJD (P = .02) and ATRS (P = .009). At day 84, the immediate group registered more MJD (P = .001). CONCLUSIONS: Compared with traditional rehabilitation, 12 weeks of immediate rehabilitation after percutaneous AT repair resulted in better MJD, PFS, and ATRS after 4 weeks; better MJD and ATRS after 8 weeks; and better MJD after 12 weeks.