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Erschienen in:
Comparative Analysis of Quasi-Differential Approaches in Inverse Kinematics Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Neural and Physiological Measures to Classify User’s Intention and Control Exoskeletons for Rehabilitation or Assistance: The Experience @NearLab

verfasst von : Simona Ferrante, Emilia Ambrosini, Claudia Casellato, Marta Gandolla, Alessandra Pedrocchi, Giancarlo Ferrigno

Erschienen in: Advances in Service and Industrial Robotics

Verlag: Springer International Publishing

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Abstract

Robotic systems to restore, augment and support human capabilities hinder the natural interaction with the world. Different approaches based on physiological measurements such as brain activity, muscle contraction, kinematics, or eye movement, can be exploited to automatically and reliably detect the intention of the user to perform a movement. Once the intention of the user is detected or classified, it can trigger or control an exoskeleton supporting the target gesture. All these features together provide a personalized communication between the robot and the user making human-robot interaction natural and seamless. Thus, the acceptability and usability of the system is maximized. Several integrated robotic actuators driven by user’s intention are here described to demonstrate the potentiality of these technologies both for rehabilitation and assistance purposes.

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Metadaten
Titel
Neural and Physiological Measures to Classify User’s Intention and Control Exoskeletons for Rehabilitation or Assistance: The Experience @NearLab
verfasst von
Simona Ferrante
Emilia Ambrosini
Claudia Casellato
Marta Gandolla
Alessandra Pedrocchi
Giancarlo Ferrigno
Copyright-Jahr
2018
Buch
Advances in Service and Industrial Robotics

Print ISBN: 978-3-319-61275-1

Electronic ISBN: 978-3-319-61276-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-61276-8_78

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