Wavelet based noise removal from EMG signals
Wavelet transform has been applied in this research for removing noise from the surface electromyography signal (SEMG). The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Error. This paper reports on the effectiveness of the wavelet transform applied to th...
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| Format: | Article |
| Language: | English |
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Society for Microelectronics, Electric Components and Materials
2007
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| Online Access: | http://irep.iium.edu.my/29533/ http://irep.iium.edu.my/29533/1/MIDEM_37%282007%292p94.pdf |
| _version_ | 1848780141012975616 |
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| author | Chowdhury, Md. Sazzad Hossien Reaz, Mamun Bin Ibne Ibne Ibrahimy, Muhammad Ibn Ismail, Ahmad Faris Mohd-Yasin, Faisal |
| author_facet | Chowdhury, Md. Sazzad Hossien Reaz, Mamun Bin Ibne Ibne Ibrahimy, Muhammad Ibn Ismail, Ahmad Faris Mohd-Yasin, Faisal |
| author_sort | Chowdhury, Md. Sazzad Hossien |
| building | IIUM Repository |
| collection | Online Access |
| description | Wavelet transform has been applied in this research for removing noise from the surface electromyography signal (SEMG). The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Error. This paper reports on the effectiveness of the wavelet transform applied to the SEMG signal as means of removing noise to retrieve information related to muscle contraction and nerve system. Power spectrum analysis has been applied to SEMG signals where mean power frequency was calculated to indicate changes in muscle contraction. Wavelet based noise removal and power spectrum analysis on the EMG signal from the right "biceps brachii" muscle was performed using four wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze SEMG significantly. Results show that WFs Daubechies (db2) provide the best noise removal from the raw SEMG signals among other WFs Daubechies (db6, db8) and orthogonal Meyer. The algorithm is intended for FPGA implementation of portable bio medical equipments to detect neuromuscular disease and muscle fatigue. |
| first_indexed | 2025-11-14T15:28:57Z |
| format | Article |
| id | iium-29533 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:28:57Z |
| publishDate | 2007 |
| publisher | Society for Microelectronics, Electric Components and Materials |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-295332020-06-29T06:38:34Z http://irep.iium.edu.my/29533/ Wavelet based noise removal from EMG signals Chowdhury, Md. Sazzad Hossien Reaz, Mamun Bin Ibne Ibne Ibrahimy, Muhammad Ibn Ismail, Ahmad Faris Mohd-Yasin, Faisal T Technology (General) Wavelet transform has been applied in this research for removing noise from the surface electromyography signal (SEMG). The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Error. This paper reports on the effectiveness of the wavelet transform applied to the SEMG signal as means of removing noise to retrieve information related to muscle contraction and nerve system. Power spectrum analysis has been applied to SEMG signals where mean power frequency was calculated to indicate changes in muscle contraction. Wavelet based noise removal and power spectrum analysis on the EMG signal from the right "biceps brachii" muscle was performed using four wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze SEMG significantly. Results show that WFs Daubechies (db2) provide the best noise removal from the raw SEMG signals among other WFs Daubechies (db6, db8) and orthogonal Meyer. The algorithm is intended for FPGA implementation of portable bio medical equipments to detect neuromuscular disease and muscle fatigue. Society for Microelectronics, Electric Components and Materials 2007-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/29533/1/MIDEM_37%282007%292p94.pdf Chowdhury, Md. Sazzad Hossien and Reaz, Mamun Bin Ibne Ibne and Ibrahimy, Muhammad Ibn and Ismail, Ahmad Faris and Mohd-Yasin, Faisal (2007) Wavelet based noise removal from EMG signals. Informacije MIDEM: Journal of Microelectronics, Electronic Components and Materials, 37 (2). pp. 94-97. ISSN 0352-9045 http://www.midem-drustvo.si/journal.htm |
| spellingShingle | T Technology (General) Chowdhury, Md. Sazzad Hossien Reaz, Mamun Bin Ibne Ibne Ibrahimy, Muhammad Ibn Ismail, Ahmad Faris Mohd-Yasin, Faisal Wavelet based noise removal from EMG signals |
| title | Wavelet based noise removal from EMG signals |
| title_full | Wavelet based noise removal from EMG signals |
| title_fullStr | Wavelet based noise removal from EMG signals |
| title_full_unstemmed | Wavelet based noise removal from EMG signals |
| title_short | Wavelet based noise removal from EMG signals |
| title_sort | wavelet based noise removal from emg signals |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/29533/ http://irep.iium.edu.my/29533/ http://irep.iium.edu.my/29533/1/MIDEM_37%282007%292p94.pdf |