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

• Published in: Scientific reports Vol. 12; no. 1; p. 7601
• Main Authors: Kanzler, Christoph M, Averta, Giuseppe, Schwarz, Anne, Held, Jeremia P O, Gassert, Roger, Bicchi, Antonio, Santello, Marco, Lambercy, Olivier, Bianchi, Matteo
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 09.05.2022; Nature Publishing Group UK; Nature Portfolio
• Subjects: Age; Algorithms; Arm; Decomposition; Grasping; Hand; Hand Strength; Humans; Kinematics; Movement; Principal components analysis; Robotics; Sensorimotor system; Statistical analysis; Stroke; Velocity
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-11806-4

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.