EMG based classification of thumb posture using portable thumb training system

EMG based classification of thumb posture using portable thumb training system

Loss of human limbs that are caused by traumatic accidents, vascular diseases and diabetes that lead to amputation has great impact to the well-being of the affected segment of societies. They usually require prostheses to restore the original functionality of the missing limbs so to be able to ass...

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Main Authors: Roslan, Muhammad Rozaidi, Sidek, Shahrul Na'im, Sidek, Sabrilhakim, Mohd Khalid, Mohd Shukry
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2017
Subjects:
TA164 Bioengineering
Online Access:http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/25/53829-edited.pdf
http://irep.iium.edu.my/53829/13/53829-EMG%20based%20classification%20of%20thumb%20posture%20using%20portable%20thumb%20training%20system_SCOPUS.pdf
id iium-53829
recordtype eprints
spelling iium-538292019-01-10T04:54:00Z http://irep.iium.edu.my/53829/ EMG based classification of thumb posture using portable thumb training system Roslan, Muhammad Rozaidi Sidek, Shahrul Na'im Sidek, Sabrilhakim Mohd Khalid, Mohd Shukry TA164 Bioengineering Loss of human limbs that are caused by traumatic accidents, vascular diseases and diabetes that lead to amputation has great impact to the well-being of the affected segment of societies. They usually require prostheses to restore the original functionality of the missing limbs so to be able to assist them in the activities of daily living. Extensive works have been reported in developing prostheses that not only could work as close as the natural limbs but also look alike the original ones. Many of these prostheses are based on the myoelectric control which requires the electromyography (EMG) signal to be measured and analyzed from the remaining nerves or muscles left after amputation. It is still a challenge however to detect, process, classify and apply the signal appropriately. In this paper, a study on the relationship of thumb-tip force related to EMG signals using a well-designed, portable thumb training system is conducted. The EMG signal is classified by using machine learning techniques when the thumb is flexed at different angles and exerts different magnitude of forces at its tip. The thumb training system is developed with compliances to fit different shape and size of human hands. The result from the analysis done using WEKA software shows that the EMG signal can be used to estimate the posture of the thumb at different flexed angles and thumb tip forces. IEEE 2017-02-03 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/53829/25/53829-edited.pdf application/pdf en http://irep.iium.edu.my/53829/13/53829-EMG%20based%20classification%20of%20thumb%20posture%20using%20portable%20thumb%20training%20system_SCOPUS.pdf Roslan, Muhammad Rozaidi and Sidek, Shahrul Na'im and Sidek, Sabrilhakim and Mohd Khalid, Mohd Shukry (2017) EMG based classification of thumb posture using portable thumb training system. In: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 4th-8th December 2016, Kuala Lumpur. http://ieeexplore.ieee.org/document/7843552/ 10.1109/IECBES.2016.7843552
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic TA164 Bioengineering
spellingShingle TA164 Bioengineering
Roslan, Muhammad Rozaidi
Sidek, Shahrul Na'im
Sidek, Sabrilhakim
Mohd Khalid, Mohd Shukry
EMG based classification of thumb posture using portable thumb training system
description Loss of human limbs that are caused by traumatic accidents, vascular diseases and diabetes that lead to amputation has great impact to the well-being of the affected segment of societies. They usually require prostheses to restore the original functionality of the missing limbs so to be able to assist them in the activities of daily living. Extensive works have been reported in developing prostheses that not only could work as close as the natural limbs but also look alike the original ones. Many of these prostheses are based on the myoelectric control which requires the electromyography (EMG) signal to be measured and analyzed from the remaining nerves or muscles left after amputation. It is still a challenge however to detect, process, classify and apply the signal appropriately. In this paper, a study on the relationship of thumb-tip force related to EMG signals using a well-designed, portable thumb training system is conducted. The EMG signal is classified by using machine learning techniques when the thumb is flexed at different angles and exerts different magnitude of forces at its tip. The thumb training system is developed with compliances to fit different shape and size of human hands. The result from the analysis done using WEKA software shows that the EMG signal can be used to estimate the posture of the thumb at different flexed angles and thumb tip forces.
format Conference or Workshop Item
author Roslan, Muhammad Rozaidi
Sidek, Shahrul Na'im
Sidek, Sabrilhakim
Mohd Khalid, Mohd Shukry
author_facet Roslan, Muhammad Rozaidi
Sidek, Shahrul Na'im
Sidek, Sabrilhakim
Mohd Khalid, Mohd Shukry
author_sort Roslan, Muhammad Rozaidi
title EMG based classification of thumb posture using portable thumb training system
title_short EMG based classification of thumb posture using portable thumb training system
title_full EMG based classification of thumb posture using portable thumb training system
title_fullStr EMG based classification of thumb posture using portable thumb training system
title_full_unstemmed EMG based classification of thumb posture using portable thumb training system
title_sort emg based classification of thumb posture using portable thumb training system
publisher IEEE
publishDate 2017
url http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/
http://irep.iium.edu.my/53829/25/53829-edited.pdf
http://irep.iium.edu.my/53829/13/53829-EMG%20based%20classification%20of%20thumb%20posture%20using%20portable%20thumb%20training%20system_SCOPUS.pdf
first_indexed 2023-09-18T21:16:09Z
last_indexed 2023-09-18T21:16:09Z
_version_ 1777411575567613952

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