Mitigation of Noise on Surface Electromyography (sEMG) Signals through Signal Filtering Algorithms
Surface electromyography (sEMG) is crucial in sports science, offering insights into muscle activation patterns. However, standard devices like the Delsys Trigno Wireless System are relatively costly. This study presents a prototype that simultaneously obtains sEMG and IMU signals to measure muscle activity. The presence of noise necessitates signal processing techniques to be applied to the raw signal, including feed-forward comb, adaptive, and wavelet filters. Evaluation against a reference signal revealed that the wavelet filter performed best, exhibiting the lowest MSE and highest SNR scores. Specifically, it achieved MSE scores of 2.62E-10 in the time domain, 6.25E-22 in PSD, and SNR scores 13.96 for squats. These findings underscore the effectiveness of the wavelet filter in reducing sEMG signal noise.
Authors
- Jehiel D. Santos
- Jose M. Sandoval (ORCID: https://orcid.org/0000-0002-3786-3534)
- Justine B. Duran (ORCID: https://orcid.org/0009-0002-3329-7114)
- Ma. Madecheen S. Pangaliman (ORCID: https://orcid.org/0009-0003-2200-634X)
- Angelito A. Silverio (ORCID: https://orcid.org/0000-0002-3425-3466)
- Seigfred V. Prado (ORCID: https://orcid.org/0000-0002-0111-7193)
- Consuelo Gonzalez-Suarez (ORCID: https://orcid.org/0000-0001-8382-474X)
- Reil Vinard Espino (ORCID: https://orcid.org/0000-0002-9695-1614)
- Jazzmine Gale Flores
- Elaine Nicole S. Bulseco
- Denisse V. Cunanan
- Ma. Belinda C. Fidel
- Regina Rose B. Magpantay
- James Andrew M. Roxas
- Akira Ryodji P. Tagura
Institutions
- University of Santo Tomas (PH)
Publication Details
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tencon61640.2024.10902985
- Citations
- 2
- Primary Topic
- Muscle activation and electromyography studies
- Type
- article
- Field-Weighted Citation Impact
- 0.37