Electromyogram (EMG) signal processing analysis for clinical rehabilitation application
Analysis of electromyogram (EMG) signal processing and its application to identify human muscle strength of rehabilitation purpose has been successfully carried out in this paper. Single channel EMG signal was obtained from human muscle using non-invasive electrodes and further process by signal acq...
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my.ums.eprints.186022018-02-03T13:52:48Z https://eprints.ums.edu.my/id/eprint/18602/ Electromyogram (EMG) signal processing analysis for clinical rehabilitation application Ismail Saad Nur Husna Bais Bun Seng, C Mohd Zuhir Hamzah Nurmin Bolong Q Science (General) Analysis of electromyogram (EMG) signal processing and its application to identify human muscle strength of rehabilitation purpose has been successfully carried out in this paper. Single channel EMG signal was obtained from human muscle using non-invasive electrodes and further process by signal acquisition circuit to get a suitable signal to be process. In the first part of signal acquisition, the amplification circuit for the small EMG signal has been design successfully. After amplification stage EMG signal was digitized through analogue and digital converter (ADC) then further process in microcontroller (ATmega328) for getting accurate EMG signal. Finally, the processed EMG signal was classified into 6 different levels in order to display the muscle strength level of the user. This EMG device can be used to help the weak person or an elderly to identity their strength level of muscle for clinical rehabilitation purpose. 2016 Conference or Workshop Item PeerReviewed text en https://eprints.ums.edu.my/id/eprint/18602/1/Electromyogram.pdf Ismail Saad and Nur Husna Bais and Bun Seng, C and Mohd Zuhir Hamzah and Nurmin Bolong (2016) Electromyogram (EMG) signal processing analysis for clinical rehabilitation application. In: Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation, 2-4 December 2015, Kota Kinabalu, Malaysia. https://doi.org/10.1109/AIMS.2015.76 |
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Q Science (General) Ismail Saad Nur Husna Bais Bun Seng, C Mohd Zuhir Hamzah Nurmin Bolong Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
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Analysis of electromyogram (EMG) signal processing and its application to identify human muscle strength of rehabilitation purpose has been successfully carried out in this paper. Single channel EMG signal was obtained from human muscle using non-invasive electrodes and further process by signal acquisition circuit to get a suitable signal to be process. In the first part of signal acquisition, the amplification circuit for the small EMG signal has been design successfully. After amplification stage EMG signal was digitized through analogue and digital converter (ADC) then further process in microcontroller (ATmega328) for getting accurate EMG signal. Finally, the processed EMG signal was classified into 6 different levels in order to display the muscle strength level of the user. This EMG device can be used to help the weak person or an elderly to identity their strength level of muscle for clinical rehabilitation purpose. |
format |
Conference or Workshop Item |
author |
Ismail Saad Nur Husna Bais Bun Seng, C Mohd Zuhir Hamzah Nurmin Bolong |
author_facet |
Ismail Saad Nur Husna Bais Bun Seng, C Mohd Zuhir Hamzah Nurmin Bolong |
author_sort |
Ismail Saad |
title |
Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
title_short |
Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
title_full |
Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
title_fullStr |
Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
title_full_unstemmed |
Electromyogram (EMG) signal processing analysis for clinical rehabilitation application |
title_sort |
electromyogram (emg) signal processing analysis for clinical rehabilitation application |
publishDate |
2016 |
url |
https://eprints.ums.edu.my/id/eprint/18602/1/Electromyogram.pdf https://eprints.ums.edu.my/id/eprint/18602/ https://doi.org/10.1109/AIMS.2015.76 |
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1760229468237987840 |
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13.211869 |