Artificial Neural Networks for classification of EMG data in hand myoelectric control

Tarullo, Viviana (2019) Artificial Neural Networks for classification of EMG data in hand myoelectric control. [Laurea magistrale], Università di Bologna, Corso di Studio in Matematica [LM-DM270]
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Abstract

This thesis studies the state-of-the-art in myoelectric control of active hand prostheses for people with trans-radial amputation using pattern recognition and machine learning techniques. Our work is supported by Centro Protesi INAIL in Vigorso di Budrio (BO). We studied the control system developed by INAIL consisting in acquiring EMG signals from amputee subjects and using pattern recognition methods for the classifcation of acquired signals, associating them with specifc gestures and consequently commanding the prosthesis. Our work consisted in improving classifcation methods used in the learning phase. In particular, we proposed a classifer based on a neural network as a valid alternative to the INAIL one-versus-all approach to multiclass classifcation.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Tarullo, Viviana
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Curriculum A: Generale e applicativo
Ordinamento Cds
DM270
Parole chiave
ANN artificial neural networks classification method ML machine learning prosthetic control EMG
Data di discussione della Tesi
25 Ottobre 2019
URI

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