Muscle Synergies in Parkinson’s Disease

Sensors

Francesco Asci¹  Antonio Suppa¹  Alessandro Zampogna¹  Eduardo Palermo²  Zaccaria Del Prete²  Ilaria Mileti²  Alessandro Santuz³  Adamantios Arampatzis³ 

[1] Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy;Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy;Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany;

关键词: Parkinson’s disease;    muscle synergies;    motor modules;    motor primitives;    electromyography;    balance;   

DOI  :  10.3390/s20113209

来源: DOAJ

【 摘 要 】

Over the last two decades, experimental studies in humans and other vertebrates have increasingly used muscle synergy analysis as a computational tool to examine the physiological basis of motor control. The theoretical background of muscle synergies is based on the potential ability of the motor system to coordinate muscles groups as a single unit, thus reducing high-dimensional data to low-dimensional elements. Muscle synergy analysis may represent a new framework to examine the pathophysiological basis of specific motor symptoms in Parkinson’s disease (PD), including balance and gait disorders that are often unresponsive to treatment. The precise mechanisms contributing to these motor symptoms in PD remain largely unknown. A better understanding of the pathophysiology of balance and gait disorders in PD is necessary to develop new therapeutic strategies. This narrative review discusses muscle synergies in the evaluation of motor symptoms in PD. We first discuss the theoretical background and computational methods for muscle synergy extraction from physiological data. We then critically examine studies assessing muscle synergies in PD during different motor tasks including balance, gait and upper limb movements. Finally, we speculate about the prospects and challenges of muscle synergy analysis in order to promote future research protocols in PD.

【 授权许可】

Unknown