Pattern recognition methods for EMG prosthetic control

Baccherini, Simona (2016) Pattern recognition methods for EMG prosthetic control. [Laurea magistrale], Università di Bologna, Corso di Studio in Matematica [LM-DM270]
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Abstract

In this work we focus on pattern recognition methods related to EMG upper-limb prosthetic control. After giving a detailed review of the most widely used classification methods, we propose a new classification approach. It comes as a result of comparison in the Fourier analysis between able-bodied and trans-radial amputee subjects. We thus suggest a different classification method which considers each surface electrodes contribute separately, together with five time domain features, obtaining an average classification accuracy equals to 75% on a sample of trans-radial amputees. We propose an automatic feature selection procedure as a minimization problem in order to improve the method and its robustness.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Baccherini, Simona
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Curriculum A: Generale e applicativo
Ordinamento Cds
DM270
Parole chiave
pattern recognition EMG signals principal component analysis support vector machine spectral clustering k-means neural networks
Data di discussione della Tesi
28 Ottobre 2016
URI

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