Muscle synergies for evaluating upper limb in clinical applications: A systematic review

K Zhao, Z Zhang, H Wen, B Liu, J Li, A d'Avella… - Heliyon, 2023‏ - cell.com
Introduction Muscle synergies have been proposed as a strategy employed by the central
nervous system to control movements. Muscle synergy analysis is a well-established …

Dep-rl: Embodied exploration for reinforcement learning in overactuated and musculoskeletal systems

P Schumacher, D Häufle, D Büchler, S Schmitt… - ar** review on EMG processing and synergy-based results in muscle synergy studies in Parkinson's disease
V Lanzani, C Brambilla, A Scano - Frontiers in Bioengineering and …, 2025‏ - frontiersin.org
Introduction Parkinson's Disease is the second most common neurodegenerative disease in
the world. It affects mainly people over 65 and the incidence increases with age. It is …

[HTML][HTML] SynergyAnalyzer: A Matlab toolbox implementing mixed-matrix factorization to identify kinematic-muscular synergies

M Russo, A Scano, C Brambilla, A d'Avella - Computer Methods and …, 2024‏ - Elsevier
Background and Objective A new direction in the study of motor control was opened about
two decades ago with the introduction of a model for the generation of motor commands as …

Analysis of muscle synergies and muscle network in sling exercise rehabilitation technique

X Li, G Xu, L Li, Z Hao, WLA Lo, C Wang - Computers in Biology and …, 2024‏ - Elsevier
The study assessed motor control strategies across the four sling exercises of supine sling
exercise (SSE), prone sling exercise (PSE), left side-lying sling exercise (LLSE), and right …

DynSyn: dynamical synergistic representation for efficient learning and control in overactuated embodied systems

K He, C Zuo, C Ma, Y Sui - arxiv preprint arxiv:2407.11472, 2024‏ - arxiv.org
Learning an effective policy to control high-dimensional, overactuated systems is a
significant challenge for deep reinforcement learning algorithms. Such control scenarios are …

Muscle synergies and muscle networks in multiple frequency components in post-stroke patients

K Zhao, Y Feng, L Li, Y Zhou, Z Zhang, J Li - Biomedical Signal Processing …, 2024‏ - Elsevier
As a neural control strategy employed by the central nervous system to control movements,
the extraction of muscle synergies from a broad range of electromyographic signals has …

Evidence of synergy coordination patterns of upper-limb motor control in stroke patients with mild and moderate impairment

K Zhao, C He, W **ang, Y Zhou, Z Zhang, J Li… - Frontiers in …, 2023‏ - frontiersin.org
Objectives: Previous studies showed that the central nervous system (CNS) controls
movements by recruiting a low-dimensional set of modules, usually referred to as muscle …

Using different matrix factorization approaches to identify muscle synergy in stroke survivors

Y Ma, S Ye, D Zhao, X Liu, L Cao, H Zhou, G Zuo… - Medical Engineering & …, 2023‏ - Elsevier
Over the past several decades, many scholars have investigated muscle synergy as a
promising tool for evaluating motor function. However, it is challenging to obtain favorable …

Continuous Prediction of Wrist Joint Kinematics Using Surface Electromyography from the Perspective of Muscle Anatomy and Muscle Synergy Feature Extraction

Z Wei, M Li, ZQ Zhang, SQ **e - IEEE Journal of Biomedical …, 2024‏ - ieeexplore.ieee.org
Post-stroke upper limb dysfunction severely impacts patients' daily life quality. Utilizing
sEMG signals to predict patients' motion intentions enables more effective rehabilitation by …