Time-frequency Features for sEMG Signals Classification

Somar Karheily; Ali Moukadem; Jean-Baptiste Courbot; Djaffar Ould Abdeslam

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Time-frequency Features for sEMG Signals Classification

Topics: Frequency Analysis & Wavelet Transform; Medical Signal Acquisition, Analysis and Processing; Pattern Recognition & Machine Learning for Biosignal Data

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSTEC, 244-249, 2020 , Valletta, Malta

Authors: Somar Karheily ; Ali Moukadem ; Jean-Baptiste Courbot and Djaffar Ould Abdeslam

Affiliation: Institute IRIMAS, University of Haute-Alsace, Mulhouse, France

Keyword(s): Time-frequency Analysis, Features Extraction, Prosthetic Arm, sEMG, Hand Gesture.

Abstract: This paper proposes a new approach for the identification of hand movements in order to control prosthetic hand. sEMG signals were used to identify movements by using two time frequency transforms: Short Time Fourier Transform and Stockwell transform. Then, we apply Singular Value Decomposition (SVD) to decrease the features dimension and to form the final features’ vector. These extracted features were used by two kinds of classifiers: K nearest neighbours and linear discriminant analysis. Finally, we numerically study these methods on a database of 10 subjects and 17 hand gestures.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 52.14.240.178

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:

Karheily, S.; Moukadem, A.; Courbot, J. and Abdeslam, D. (2020). Time-frequency Features for sEMG Signals Classification. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 244-249. DOI: 10.5220/0008971902440249

@conference{biosignals20,
author={Somar Karheily. and Ali Moukadem. and Jean{-}Baptiste Courbot. and Djaffar Ould Abdeslam.},
title={Time-frequency Features for sEMG Signals Classification},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS},
year={2020},
pages={244-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008971902440249},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - BIOSIGNALS
TI - Time-frequency Features for sEMG Signals Classification
SN - 978-989-758-398-8
IS - 2184-4305
AU - Karheily, S.
AU - Moukadem, A.
AU - Courbot, J.
AU - Abdeslam, D.
PY - 2020
SP - 244
EP - 249
DO - 10.5220/0008971902440249
PB - SciTePress