DTA

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Tesi etd-11162020-171048

Tipo di tesi
Dottorato
Autore
CAMARDELLA, CRISTIAN
URN
etd-11162020-171048
Titolo
INNOVATIVE REHABILITATION STRATEGIES FOR ROBOTIC EXOSKELETONS USING MACHINE LEARNING AND BIOMETRIC SIGNALS
Settore scientifico disciplinare
ING-IND/13
Corso di studi
Istituto di Tecnologie della Comunicazione, dell'Informazione e della Percezione - PH.D. PROGRAMME IN EMERGING DIGITAL TECHNOLOGIES (EDT)
Commissione
Presidente Prof. FRISOLI, ANTONIO
Membro Prof. TONG, RAYMOND
Membro Dott.ssa CREA, SIMONA
Membro Prof. SOLAZZI, MASSIMILIANO
Membro Prof. BEVILACQUA, VITOANTONIO
Parole chiave
  • exoskeleton
  • muscle synergy
  • myo-control
  • rehabilitation robotics
  • virtual reality
Data inizio appello
30/03/2021;
Disponibilità
completa
Riassunto analitico
-INTRODUCTION
STATE OF ART OF ROBOTIC REHABILITATION EXOSKELETONS
UPPER LIMB EXOSKELETONS
LOWER LIMB EXOSKELETONS
STATE OF ART OF EXOSKELETONS CONTROL STRATEGIES
MODEL-BASED STRATEGIES
MODEL-FREE STRATEGIES
REHABILITATION TECHNOLOGIES
EXOSKELETONS AND VIRTUAL REALITY

-MUSCLES SYNERGIES
THEORY OF MUSCLES SYNERGIES
EXTRACTION OF MUSCLES SYNERGIES
AUTOENCODER-BASED ALGORITHM
TASK-ORIENTED EXTRACTION
SYNERGIES IN REHABILITATION

-THE MYOELECTRIC CONTROL FOR UPPER LIMB DEVICES
WHAT MYOCONTROL IS?
MODEL-GENERATION THROUGH INTERPOLATION
THE SYNERGY-BASED MYOCONTROL
THE REAL-TIME MYOCONTROL

-EXOSKELETONS IN VIRTUAL REALITY TASKS
THE METAPHORICAL INTERACTION
HAPTICS IN VR
THE ISLAND EXPERIMENT

-LOWER LIMB EXOSKELETONS FOR REHABILITATION
THE TRANSPARENCY PROBLEM
THE BLEND CONTROL

-CONCLUSIONS
-CREDITS
-BIBLIOGRAPHY
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