Assessment of upper limb muscle tone level based on estimated impedance parameters

Many strategies have been developed by occupational and physical therapists for the assessment of poststroke patients’ upper limb muscle tone and physical recovery progress. Despite, having the appropriate skills, they face serious challenges in quantifying continuously, the patients’ recovery p...

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Main Authors: Zaw, Zaw Lay Htoon, Sidek, Shahrul Na'im, Fatai, Sado, Yunahar, Taufik
Format: Proceeding Paper
Language:English
English
Published: IEEE 2017
Subjects:
Online Access:http://irep.iium.edu.my/53828/
http://irep.iium.edu.my/53828/19/53828-Assessment%20of%20Upper%20Limb%20Muscle%20Tone%20Level%20based.pdf
http://irep.iium.edu.my/53828/13/Assessment%20of%20upper%20limb%20muscle%20tone%20level%20based%20on%20estimated%20impedance%20parameters.pdf
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author Zaw, Zaw Lay Htoon
Sidek, Shahrul Na'im
Fatai, Sado
Yunahar, Taufik
author_facet Zaw, Zaw Lay Htoon
Sidek, Shahrul Na'im
Fatai, Sado
Yunahar, Taufik
author_sort Zaw, Zaw Lay Htoon
building IIUM Repository
collection Online Access
description Many strategies have been developed by occupational and physical therapists for the assessment of poststroke patients’ upper limb muscle tone and physical recovery progress. Despite, having the appropriate skills, they face serious challenges in quantifying continuously, the patients’ recovery progress. Moreover, the therapy has become more costly and time consuming since the patients are required to have a face-to-face contact with the therapist over a long period of time. By deploying robot-assisted rehabilitation therapy, some of these problems have been addressed, however, serious challenges still exist in the aspect of proper estimation and assessment of patients muscle tone level and recovery progress during rehabilitation therapy. This paper proposes an appropriate strategy for prediction and assessment of subjects’ muscle tone level and recovery based on the estimation of upper-limb mechanical impedance parameters. The subjects’ mechanical impedance parameters are estimated using a recursive least square estimator method and the muscle tone level are predicted by Artificial Neural Network (ANN) which has been trained using the estimated impedance parameters. Preliminary experimental result shows that the upper-limb impedance parameters can be estimated to an accuracy level of 90%, while simulation studies have revealed that the muscle tone level can be reliably predicted at 95.01% accuracy level.
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format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
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publishDate 2017
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spelling iium-538282019-01-10T04:53:38Z http://irep.iium.edu.my/53828/ Assessment of upper limb muscle tone level based on estimated impedance parameters Zaw, Zaw Lay Htoon Sidek, Shahrul Na'im Fatai, Sado Yunahar, Taufik TA164 Bioengineering Many strategies have been developed by occupational and physical therapists for the assessment of poststroke patients’ upper limb muscle tone and physical recovery progress. Despite, having the appropriate skills, they face serious challenges in quantifying continuously, the patients’ recovery progress. Moreover, the therapy has become more costly and time consuming since the patients are required to have a face-to-face contact with the therapist over a long period of time. By deploying robot-assisted rehabilitation therapy, some of these problems have been addressed, however, serious challenges still exist in the aspect of proper estimation and assessment of patients muscle tone level and recovery progress during rehabilitation therapy. This paper proposes an appropriate strategy for prediction and assessment of subjects’ muscle tone level and recovery based on the estimation of upper-limb mechanical impedance parameters. The subjects’ mechanical impedance parameters are estimated using a recursive least square estimator method and the muscle tone level are predicted by Artificial Neural Network (ANN) which has been trained using the estimated impedance parameters. Preliminary experimental result shows that the upper-limb impedance parameters can be estimated to an accuracy level of 90%, while simulation studies have revealed that the muscle tone level can be reliably predicted at 95.01% accuracy level. IEEE 2017-02-06 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/53828/19/53828-Assessment%20of%20Upper%20Limb%20Muscle%20Tone%20Level%20based.pdf application/pdf en http://irep.iium.edu.my/53828/13/Assessment%20of%20upper%20limb%20muscle%20tone%20level%20based%20on%20estimated%20impedance%20parameters.pdf Zaw, Zaw Lay Htoon and Sidek, Shahrul Na'im and Fatai, Sado and Yunahar, Taufik (2017) Assessment of upper limb muscle tone level based on estimated impedance parameters. In: IEEE-EMBS Conference of Biomedical, Engineering and Sciences (IECBES 2016), 4th-8th Dec. 2016, Kuala Lumpur. http://ieeexplore.ieee.org/document/7843549/ 10.1109/IECBES.2016.7843549
spellingShingle TA164 Bioengineering
Zaw, Zaw Lay Htoon
Sidek, Shahrul Na'im
Fatai, Sado
Yunahar, Taufik
Assessment of upper limb muscle tone level based on estimated impedance parameters
title Assessment of upper limb muscle tone level based on estimated impedance parameters
title_full Assessment of upper limb muscle tone level based on estimated impedance parameters
title_fullStr Assessment of upper limb muscle tone level based on estimated impedance parameters
title_full_unstemmed Assessment of upper limb muscle tone level based on estimated impedance parameters
title_short Assessment of upper limb muscle tone level based on estimated impedance parameters
title_sort assessment of upper limb muscle tone level based on estimated impedance parameters
topic TA164 Bioengineering
url http://irep.iium.edu.my/53828/
http://irep.iium.edu.my/53828/
http://irep.iium.edu.my/53828/
http://irep.iium.edu.my/53828/19/53828-Assessment%20of%20Upper%20Limb%20Muscle%20Tone%20Level%20based.pdf
http://irep.iium.edu.my/53828/13/Assessment%20of%20upper%20limb%20muscle%20tone%20level%20based%20on%20estimated%20impedance%20parameters.pdf