Development of a model for sEMG based joint-torque estimation using Swarm techniques
Over the years, numerous researchers have explored the relationship between surface electromyography (sEMG) signal with joint torque that would be useful to develop a suitable controller for rehabilitation robot. This research focuses on the transformation of sEMG signal by adopting a mathematical m...
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Institute of Electrical and Electronics Engineers Inc.
2017
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my.utp.eprints.201532018-04-22T14:43:30Z Development of a model for sEMG based joint-torque estimation using Swarm techniques Nurhanim, K. Elamvazuthi, I. Izhar, L.I. Ganesan, T. Su, S.W. Over the years, numerous researchers have explored the relationship between surface electromyography (sEMG) signal with joint torque that would be useful to develop a suitable controller for rehabilitation robot. This research focuses on the transformation of sEMG signal by adopting a mathematical model to find the estimated joint torque of knee extension. Swarm techniques such as Particle Swarm Optimization (PSO) and Improved Particle Swarm Optimization (IPSO) were adapted to optimize the mathematical model for estimated joint torque. The correlation between the estimated joint torque and actual joint torque were determined by Coefficient of Determination (R2) and fitness value of Sum Squared Error (SSE). The outcome of the research shows that both the PSO and IPSO have yielded promising results. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015922961&doi=10.1109%2fROMA.2016.7847833&partnerID=40&md5=0e20efc222787d3f690f600731ce8840 Nurhanim, K. and Elamvazuthi, I. and Izhar, L.I. and Ganesan, T. and Su, S.W. (2017) Development of a model for sEMG based joint-torque estimation using Swarm techniques. 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016 . http://eprints.utp.edu.my/20153/ |
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Over the years, numerous researchers have explored the relationship between surface electromyography (sEMG) signal with joint torque that would be useful to develop a suitable controller for rehabilitation robot. This research focuses on the transformation of sEMG signal by adopting a mathematical model to find the estimated joint torque of knee extension. Swarm techniques such as Particle Swarm Optimization (PSO) and Improved Particle Swarm Optimization (IPSO) were adapted to optimize the mathematical model for estimated joint torque. The correlation between the estimated joint torque and actual joint torque were determined by Coefficient of Determination (R2) and fitness value of Sum Squared Error (SSE). The outcome of the research shows that both the PSO and IPSO have yielded promising results. © 2016 IEEE. |
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Nurhanim, K. Elamvazuthi, I. Izhar, L.I. Ganesan, T. Su, S.W. |
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Nurhanim, K. Elamvazuthi, I. Izhar, L.I. Ganesan, T. Su, S.W. Development of a model for sEMG based joint-torque estimation using Swarm techniques |
author_facet |
Nurhanim, K. Elamvazuthi, I. Izhar, L.I. Ganesan, T. Su, S.W. |
author_sort |
Nurhanim, K. |
title |
Development of a model for sEMG based joint-torque estimation using Swarm techniques |
title_short |
Development of a model for sEMG based joint-torque estimation using Swarm techniques |
title_full |
Development of a model for sEMG based joint-torque estimation using Swarm techniques |
title_fullStr |
Development of a model for sEMG based joint-torque estimation using Swarm techniques |
title_full_unstemmed |
Development of a model for sEMG based joint-torque estimation using Swarm techniques |
title_sort |
development of a model for semg based joint-torque estimation using swarm techniques |
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Institute of Electrical and Electronics Engineers Inc. |
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2017 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015922961&doi=10.1109%2fROMA.2016.7847833&partnerID=40&md5=0e20efc222787d3f690f600731ce8840 http://eprints.utp.edu.my/20153/ |
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