Real-time Classification of Finger Movements using Two-channel Surface Electromyography

Khairul Anam; Adel Al-Jumaily

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

Real-time Classification of Finger Movements using Two-channel Surface Electromyography

In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: RoboAssist, 218-223, 2013 , Vilamoura, Algarve, Portugal

Authors: Khairul Anam ¹ and Adel Al-Jumaily ²

Affiliations: ¹ University of Jember and University of Technology, Indonesia ; ² University of Technology, Australia

Keyword(s): Surface EMG, Extreme Learning Machine, Finger Movements.

Abstract: The use of a small number of Electromyography (EMG) channels for classifying the finger movement is a challenging task. This paper proposes the recognition system for decoding the individual and combined finger movements using two channels surface EMG. The proposed system utilizes Spectral Regression Discriminant Analysis (SRDA) for dimensionality reduction, Extreme Learning Machine (ELM) for classification and the majority vote for the classification smoothness. The experimental results show that the proposed system was able to classify ten classes of individual and combined finger movements, offline and online with accuracy 97.96 % and 97.07% respectively.

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 3.143.5.161

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:

Anam, K. and Al-Jumaily, A. (2013). Real-time Classification of Finger Movements using Two-channel Surface Electromyography. In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics (NEUROTECHNIX 2013) - RoboAssist; ISBN 978-989-8565-80-8, SciTePress, pages 218-223. DOI: 10.5220/0004663002180223

@conference{roboassist13,
author={Khairul Anam. and Adel Al{-}Jumaily.},
title={Real-time Classification of Finger Movements using Two-channel Surface Electromyography},
booktitle={Proceedings of the International Congress on Neurotechnology, Electronics and Informatics (NEUROTECHNIX 2013) - RoboAssist},
year={2013},
pages={218-223},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004663002180223},
isbn={978-989-8565-80-8},
}

TY - CONF

JO - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics (NEUROTECHNIX 2013) - RoboAssist
TI - Real-time Classification of Finger Movements using Two-channel Surface Electromyography
SN - 978-989-8565-80-8
AU - Anam, K.
AU - Al-Jumaily, A.
PY - 2013
SP - 218
EP - 223
DO - 10.5220/0004663002180223
PB - SciTePress