eprintid: 6136
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/61/36
datestamp: 2023-11-09 16:17:53
lastmod: 2023-11-09 16:17:53
status_changed: 2023-11-09 16:05:00
type: conference_item
metadata_visibility: show
creators_name: Elamvazuthi, I.
creators_name: Duy, N.H.X.
creators_name: Ali, Z.
creators_name: Su, S.W.
creators_name: Khan, M.K.A.A.
creators_name: Parasuraman, S.
title: Electromyography (EMG) based Classification of Neuromuscular Disorders using Multi-Layer Perceptron
ispublished: pub
keywords: Classification (of information); Electromyography; Extraction; Feature extraction; Intelligent control; Multilayers; Neural networks; Neuromuscular rehabilitation; Neurophysiology; Robotics; Signal processing; Smart sensors, Absolute values; Autoregressive methods; Multi layer perceptron; Neuromuscular disease; Root Mean Square; Zero-crossings, Biomedical signal processing
note: cited By 52; Conference of IEEE International Symposium on Robotics and Intelligent Sensors, IEEE IRIS 2015 ; Conference Date: 18 October 2015 Through 20 October 2015; Conference Code:123218
abstract: Electromyography (EMG) signals are the measure of activity in the muscles. The aim of this study is to identify the neuromuscular disease based on EMG signals by means of classification. The neuromuscular diseases that have been identified are myopathy and neuropathy. The classification was carried out using Artificial Neural Network (ANN). There are five feature extraction techniques that were used to extract the signals such as Autoregressive (AR), Root Mean Square (RMS), Zero Crossing (ZC), Waveform length (WL) and Mean Absolute Value (MAV). A comparative analysis of these different techniques were carried out based on the results. The Multilayer Perceptron (MLP) was used for carrying out the classification.
date: 2015
publisher: Elsevier B.V.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962834084&doi=10.1016%2fj.procs.2015.12.346&partnerID=40&md5=d342f3b67f100cc89c746d2fb4f9bb44
id_number: 10.1016/j.procs.2015.12.346
full_text_status: none
publication: Procedia Computer Science
volume: 76
pagerange: 223-228
refereed: TRUE
issn: 18770509
citation:   Elamvazuthi, I. and Duy, N.H.X. and Ali, Z. and Su, S.W. and Khan, M.K.A.A. and Parasuraman, S.  (2015) Electromyography (EMG) based Classification of Neuromuscular Disorders using Multi-Layer Perceptron.  In: UNSPECIFIED.