Real-time adaptive cancellation of TENS feedback artifact on sEMG for prosthesis closed-loop control
We validated the filtering performance with twelve participants performing two experiments: artifact cancellation under variable conditions and a real-time hand control simulation called the target reaching experiment (TRE). The result showed that the Signal-to-Noise Ratio (SNR) increased by an average of 10.3dB, and the performance of four TRE indices recovered to the levels similar to those without TENS. The proposed method can significantly improve signal quality via artifact removal in the context of sensory feedback through TENS in prosthetic systems.
Authors
- Younggeol Cho (ORCID: https://orcid.org/0000-0001-8191-1751)
- Byung-Wook Lee (ORCID: https://orcid.org/0000-0002-4842-6081)
- Kyung-Soo Kim (ORCID: https://orcid.org/0000-0003-4856-1096)
Institutions
- Korea Advanced Institute of Science and Technology (KR)
- Italian Institute of Technology (IT)
Publication Details
- Journal
- Frontiers in Bioengineering and Biotechnology
- Published
- 2024-11-21
- DOI
- https://doi.org/10.3389/fbioe.2024.1492588
- Citations
- 1
- Primary Topic
- Muscle activation and electromyography studies
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- National Research Foundation
- Ministry of Education, India
- Korea Advanced Institute of Science and Technology
- Istituto Italiano di Tecnologia