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Assessment of LSVT-BIG Therapy using CIMAP algorithm

Gregorio Dotti

Assessment of LSVT-BIG Therapy using CIMAP algorithm.

Rel. Gabriella Balestra, Marco Ghislieri, Samanta Rosati. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021

Abstract:

The CIMAP (Clustering for Identification of Muscle Activation Pattern) has been applied to data collected from Parkinson's Disease subjects during gait to assess the outcome of LSVT-BIG therapy. Cleaning and pre-processing methods were applied to the data. The CIMAP was adapted and validated for new types of dataset and then the results of the output from the CIMAP were analysed using the Asymmetry Index and the Muscle Functional Index.

Relators: Gabriella Balestra, Marco Ghislieri, Samanta Rosati
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 49
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: University College Dublin (IRLANDA)
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/17577
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