loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Simone Benatti 1 ; Elisabetta Farella 2 ; Emanuele Gruppioni 3 and Luca Benini 4

Affiliations: 1 University of Bologna, Italy ; 2 University of Bologna and Fondazione Bruno Kessler, Italy ; 3 INAIL, Italy ; 4 University of Bologna and ETHZ, Italy

ISBN: 978-989-758-011-6

Keyword(s): EMG, Patter Recognition, Multisession, Active Prosthesis.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Detection and Identification ; Devices ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Real-Time Systems ; Sensor Networks ; Soft Computing ; Wearable Sensors and Systems

Abstract: Control of active hand prostheses is an open challenge. In fact, the advances in mechatronics made available prosthetic hands with multiple active degrees of freedom; however the predominant control strategies are still not natural for the user, enabling only few gestures, thus not exploiting the prosthesis potential. Pattern recognition and machine learning techniques can be of great help when applied to surface electromyography signals to offer a natural control based on the contraction of muscles corresponding to the real movements. The implementation of such approach for an active prosthetic system offers many challenges related to the reliability of data collected to train the classification algorithm. This paper focuses on these problems and propose an implementation suitable for an embedded system.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.83.192.109

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Benatti, S.; Farella, E.; Gruppioni, E. and Benini, L. (2014). Analysis of Robust Implementation of an EMG Pattern Recognition based Control.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014) ISBN 978-989-758-011-6, pages 45-54. DOI: 10.5220/0004800300450054

@conference{biosignals14,
author={Simone Benatti. and Elisabetta Farella. and Emanuele Gruppioni. and Luca Benini.},
title={Analysis of Robust Implementation of an EMG Pattern Recognition based Control},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)},
year={2014},
pages={45-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004800300450054},
isbn={978-989-758-011-6},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2014)
TI - Analysis of Robust Implementation of an EMG Pattern Recognition based Control
SN - 978-989-758-011-6
AU - Benatti, S.
AU - Farella, E.
AU - Gruppioni, E.
AU - Benini, L.
PY - 2014
SP - 45
EP - 54
DO - 10.5220/0004800300450054

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.