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G.A.I.T. Gait Analysis Interactive Tool A pipeline for Automatic Detection of Gait Events across Neuromotor Disorders

Matteo Nocilli

G.A.I.T. Gait Analysis Interactive Tool A pipeline for Automatic Detection of Gait Events across Neuromotor Disorders.

Rel. Valentina Agostini, Stefano Scafa, Marco Ghislieri. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2023

Abstract:

We introduce a tool able to automatically extract the timing of gait events during unconstrained locomotion across neuromotor disorders. Our approach relies only on inertial sensors placed on the feet, and has been validated on people with normal and pathological kinematic patterns. The algorithm achieved an average accuracy of 99.23% when tested on healthy participants, either with average weight or overweight , and a performance of 94.84% when evaluated on patients with Parkinson’s disease. G.A.I.T. is conceived as an assistant for gait assessment studies, both in healthy participants or in people with neuromotor impairments affecting gait symmetry, regularity, or balance, as usually encountered in patients with Neurological disorders. Our open-access pipeline makes it possible to automatically identify the time of key gait events (heel strike, toe off) from a single gyroscope axis (lateral mid-axis), which simplifies experimental protocols and can easily be used in everyday life conditions. The code is userfriendly and interactive. At each analysis stage, it allows for possible adjustments and manual corrections of undetected or mismatched events.

Relators: Valentina Agostini, Stefano Scafa, Marco Ghislieri
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 55
Additional Information: Tesi secretata. Fulltext non presente
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: SUPSI (SVIZZERA)
Aziende collaboratrici: SUPSI
URI: http://webthesis.biblio.polito.it/id/eprint/26140
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