Tesi etd-11082017-133632 | 
    Link copiato negli appunti
  
    Tipo di tesi
  
  
    Tesi di laurea magistrale
  
    Autore
  
  
    PELAEZ MURCIEGO, LUIS  
  
    URN
  
  
    etd-11082017-133632
  
    Titolo
  
  
    Simultaneous and proportional EMG finger control for a rehabilitation exoskeleton hand: a synergy-based approach.
  
    Dipartimento
  
  
    INGEGNERIA DELL'INFORMAZIONE
  
    Corso di studi
  
  
    EMBEDDED COMPUTING SYSTEMS
  
    Relatori
  
  
    relatore Prof. Frisoli, Antonio
correlatore Dott. Barsotti, Michele
  
correlatore Dott. Barsotti, Michele
    Parole chiave
  
  - bayes
 - bayesian
 - classification
 - classifier
 - control
 - controllo
 - dextrous
 - EMG
 - exoskeleton
 - finger
 - hand
 - mano
 - myoelectric
 - NMF
 - prosthetic
 - protesi
 - robotic
 - robotica
 - synergy
 
    Data inizio appello
  
  
    24/11/2017
  
    Consultabilità
  
  
    Completa
  
    Riassunto
  
  In this pilot study an approach for simultaneous and proportional myoelectric control of individual fingers is developed. This method is based on the non negative matrix factorization (NMF) of the bayesian estimators of the forearm EMG signals, which extract the synergies for each degree-of-freedom (DOF) using a semi-supervised algorithm with a short training phase. A synergy-based classifier is then introduced to select only the control signals corresponding to the active DOF’s. The first experiment is based on the second iteration of the NinaPro database, which includes the force at the fingertips of 40 different subjects. A second experimental protocol is proposed by using an exoskeleton hand specifically developed for stroke patient rehabilitation. The promising results show this method has the potential of providing a dexterous hand control for clinic rehabilitation and prosthetic control.  
    File
  
  | Nome file | Dimensione | 
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| FinalMas...hesis.pdf | 5.56 Mb | 
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