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Muscle Synergies in Parkinson's Disease.

Ilaria MiletiAlessandro ZampognaAlessandro SantuzFrancesco AsciZaccaria Del PreteAdamantios ArampatzisEduardo PalermoAntonio Suppa
Published in: Sensors (Basel, Switzerland) (2020)
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.
Keyphrases
  • skeletal muscle
  • upper limb
  • electronic health record
  • depressive symptoms
  • working memory
  • deep learning
  • replacement therapy
  • data analysis