A low-dimensional representation of arm movements and hand grip forces in post-stroke individuals

Christoph M. Kanzler, Giuseppe Averta, Anne Schwarz, Jeremia P.O. Held, Roger Gassert, Antonio Bicchi, Marco Santello, Olivier Lambercy, Matteo Bianchi

Research output: Contribution to journalArticlepeer-review

Abstract

Characterizing post-stroke impairments in the sensorimotor control of arm and hand is essential to better understand altered mechanisms of movement generation. Herein, we used a decomposition algorithm to characterize impairments in end-effector velocity and hand grip force data collected from an instrumented functional task in 83 healthy control and 27 chronic post-stroke individuals with mild-to-moderate impairments. According to kinematic and kinetic raw data, post-stroke individuals showed reduced functional performance during all task phases. After applying the decomposition algorithm, we observed that the behavioural data from healthy controls relies on a low-dimensional representation and demonstrated that this representation is mostly preserved post-stroke. Further, it emerged that reduced functional performance post-stroke correlates to an abnormal variance distribution of the behavioural representation, except when reducing hand grip forces. This suggests that the behavioural repertoire in these post-stroke individuals is mostly preserved, thereby pointing towards therapeutic strategies that optimize movement quality and the reduction of grip forces to improve performance of daily life activities post-stroke.

Original languageEnglish (US)
Article number7601
JournalScientific reports
Volume12
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

ASJC Scopus subject areas

  • General

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