Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device

The conventional robotic assistive device was based on pre-programmed functions by the robot expert. This makes it difficult for stroke patients use it effectively due to difficulty of torque setting that is suitable for the user movement. Electromyography (EMG) signal measures the electrical signal...

Full description

Main Authors: Nurhanim, K., Elamvazuthi, I., Vasant, P., Ganesan, T., Parasuraman, S., Ahamed Khan, M.K.A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31782 /
Published: Elsevier B.V. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925609274&doi=10.1016%2fj.procs.2014.11.049&partnerID=40&md5=44e15092b2d1933f2c14eb6f985d6b2a
http://eprints.utp.edu.my/31782/
Tags: Add Tag
No Tags, Be the first to tag this record!
id utp-eprints.31782
recordtype eprints
spelling utp-eprints.317822022-03-29T03:37:14Z Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device Nurhanim, K. Elamvazuthi, I. Vasant, P. Ganesan, T. Parasuraman, S. Ahamed Khan, M.K.A. The conventional robotic assistive device was based on pre-programmed functions by the robot expert. This makes it difficult for stroke patients use it effectively due to difficulty of torque setting that is suitable for the user movement. Electromyography (EMG) signal measures the electrical signal of muscle contraction. The EMG-based robotics assistive technology would enable the stroke patients to control the robot movement according to the user's own strength of natural movement. This paper discusses the mapping of surface electromyography signals (sEMG) to torque for robotic rehabilitation. Particle swarm optimization (PSO) has been applied as a control algorithm for a number of selected mathematical models. sEMG signals were determined as input data to the mathematical model where parameters of the mathematical model were optimized using PSO. Hence, the good correlated estimated torque as output was obtained. © 2014 The Authors. Elsevier B.V. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925609274&doi=10.1016%2fj.procs.2014.11.049&partnerID=40&md5=44e15092b2d1933f2c14eb6f985d6b2a Nurhanim, K. and Elamvazuthi, I. and Vasant, P. and Ganesan, T. and Parasuraman, S. and Ahamed Khan, M.K.A. (2014) Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device. In: UNSPECIFIED. http://eprints.utp.edu.my/31782/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The conventional robotic assistive device was based on pre-programmed functions by the robot expert. This makes it difficult for stroke patients use it effectively due to difficulty of torque setting that is suitable for the user movement. Electromyography (EMG) signal measures the electrical signal of muscle contraction. The EMG-based robotics assistive technology would enable the stroke patients to control the robot movement according to the user's own strength of natural movement. This paper discusses the mapping of surface electromyography signals (sEMG) to torque for robotic rehabilitation. Particle swarm optimization (PSO) has been applied as a control algorithm for a number of selected mathematical models. sEMG signals were determined as input data to the mathematical model where parameters of the mathematical model were optimized using PSO. Hence, the good correlated estimated torque as output was obtained. © 2014 The Authors.
format Conference or Workshop Item
author Nurhanim, K.
Elamvazuthi, I.
Vasant, P.
Ganesan, T.
Parasuraman, S.
Ahamed Khan, M.K.A.
spellingShingle Nurhanim, K.
Elamvazuthi, I.
Vasant, P.
Ganesan, T.
Parasuraman, S.
Ahamed Khan, M.K.A.
Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
author_sort Nurhanim, K.
title Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
title_short Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
title_full Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
title_fullStr Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
title_full_unstemmed Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device
title_sort joint torque estimation model of surface electromyography(semg) based on swarm intelligence algorithm for robotic assistive device
publisher Elsevier B.V.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925609274&doi=10.1016%2fj.procs.2014.11.049&partnerID=40&md5=44e15092b2d1933f2c14eb6f985d6b2a
http://eprints.utp.edu.my/31782/
_version_ 1741197635129180160
score 11.62408

Similar Items