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Scaling Stroke: A Biomechanical Insight into Muscle Synergy Disruptions in Stroke Survivors

Federico Bauducco

Scaling Stroke: A Biomechanical Insight into Muscle Synergy Disruptions in Stroke Survivors.

Rel. Danilo Demarchi, Paolo Bonato, Giulia Corniani. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2023

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Abstract:

Stroke is the second-leading cause of death and a prominent source of both mortality and morbidity. Its profound impact necessitates a deeper understanding of its physiology and consequences, as well as the development of innovative assessment methods and treatments for post-stroke rehabilitation. This dual approach would not only enhance our knowledge but also mitigate the substantial strain strokes place on the healthcare system. One pivotal aspect of understanding and addressing post-stroke complications is the study of motor control strategies, particularly muscle synergies, employed by the Central Nervous System (CNS). In healthy individuals, the CNS utilizes these muscle synergies for efficient motor control, streamlining complex multi-muscular movements and simplifying its computational tasks. However, following a stroke, there's substantial evidence indicating a disruption in these synergies. Past studies have delved into the specific muscle coordination patterns in the affected arm of stroke survivors, highlighting the preservation, merging, and fractionation of the synergies observed in unaffected arms. Despite these insights, a significant gap remains: the relationship between these disrupted muscle synergies and movement kinematics isn't well understood. The proposed study aims to bridge this gap by quantifying the disruption in muscle synergies and the associated motor primitives due to cortical damage in stroke survivors. While assessing muscle synergies offers valuable clinical insights, the process is resource-intensive, time-consuming, and requires specialized personnel. Ideally, clinicians could gauge the health status of the CNS by observing movement patterns, inferring from there the state of muscle synergies and the impact of the stroke event. Establishing a solid link between muscle synergies and movement kinematics would be a game-changer, allowing for more efficient and accessible evaluations. This research seeks to provide that missing link, empowering clinicians to optimize rehabilitation based on biomechanical observations alone. We collected kinematic and muscle activation signals and analyzed motor primitives and muscle synergies of 7 stroke survivors across various tasks, including drawing, reaching, targeted, and random movements. Motor primitives were determined for each component of the velocity time series, defining a Cartesian coordinate system aligned with the anatomical planes. This approach effectively identified a variety of complex upper-limb movements that can be described as combinations of motor primitives with a bell-shaped velocity profile. These primitives also showed scalability across various movement sizes. For every drawing and targeted task, we predicted the ideal trajectory and velocity profile, assessing their similarity to the actual ones. Muscle synergies were derived from the acquired sEMG signals via Non-Negative Matrix Factorization (NNMF). By comparing the similarity between the unaffected and affected side’s muscle synergies and the results from our kinematic analysis, we discovered a strong correlation between the two. Our findings highlight the feasibility of quantifying muscle synergy disruptions through biomechanical assessments alone.

Relators: Danilo Demarchi, Paolo Bonato, Giulia Corniani
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 123
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Biomedica
Classe di laurea: New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING
Ente in cotutela: Motion Analysis Laboratory, Spaulding Rehabilitation Hospital, Harvard Medical School (STATI UNITI D'AMERICA)
Aziende collaboratrici: Spaulding Rehabilitation Hospital
URI: http://webthesis.biblio.polito.it/id/eprint/29948
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