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Muscle Synergy Analysis for Quantifying Post-Stroke Rehabilitation Progress

Diego Sartoris

Muscle Synergy Analysis for Quantifying Post-Stroke Rehabilitation Progress.

Rel. Laura Gastaldi, Elena Gutierrez-Farewik. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2025

Abstract:

The quantification of rehabilitation progress in post-stroke subjects is essential for establishing the efficacy of a therapy. To achieve that, recent studies have suggested the implementation of the muscle synergy hypothesis, which states that the central nervous system (CNS) reduces the complexity of motor control by activating coordinated groups of muscles, referred to as synergies. Researchers also suggested employing manifold similarity measurements to better evaluate the muscle synergy similarities between the affected subjects and a control group. To validate these hypotheses, this study involved 6 able-bodied subjects (control group) and 13 post-stroke subjects, 6 of whom underwent a Functional Electrical Stimulation (FES) combined with conventional rehabilitation, while the other 7 were subjected to conventional rehabilitation alone. Gait kinematics were also analysed to assess whether the observed changes in muscle synergy similarity were consistent with functional outcome measures. The results indicated that the combination of FES with conventional rehabilitation can promote more physiological muscle synergy patterns. Gait kinematics suggested that traditional rehabilitation reliably increased walking speed in all subjects, while FES produced more variable effects in this measure. Both treatments, however, did assist in improving joint angle similarity and inter-joint coordination. Functional recovery also occurred when muscle synergy similarity decreased, indicating that although compensatory patterns could reduce muscle synergy similarity, they may facilitate motor recovery. These results suggested that a multimodal assessment, including muscle synergy analysis and functional evaluation, could provide a better understanding of recovery patterns.

Relatori: Laura Gastaldi, Elena Gutierrez-Farewik
Anno accademico: 2025/26
Tipo di pubblicazione: Elettronica
Numero di pagine: 195
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Biomedica
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-21 - INGEGNERIA BIOMEDICA
Ente in cotutela: KTH Royal Institute of Technology (SVEZIA)
Aziende collaboratrici: KTH Royal Institute of Technology
URI: http://webthesis.biblio.polito.it/id/eprint/37396
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