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Updated: Jan 31, 2026
09:42
Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
Published on: January 24, 2025
1.3K
[An endpoint-detection algorithm of surface electromyography insensitive to electrocardiogram interference]
Weizhao Xu1, Hongqiang Mo2, Lianfang Tian1
1School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, P.R.China.
Summary
This study introduces a new algorithm for accurate surface electromyography (sEMG) endpoint detection, unaffected by electrocardiogram (ECG) interference. The method achieves high accuracy, improving sEMG analysis in clinical and sports applications.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Neuroscience
Context:
- Surface electromyography (sEMG) is crucial in clinical medicine, rehabilitation, and sports science.
- Accurate endpoint detection is vital for meaningful sEMG analysis.
- ECG interference poses a significant challenge for sEMG endpoint detection, especially near the heart.
Purpose:
- To develop an sEMG endpoint detection algorithm robust to ECG interference.
- To enhance the accuracy of sEMG signal analysis in the presence of noise.
Summary:
- A novel algorithm utilizes short-time energy and zero-crossing rates for sEMG endpoint detection.
- Algorithm thresholds are determined by statistically differentiating sEMG from ECG and background noise.
- Validated on rectus abdominis muscle sEMG, the algorithm achieved a 95.6% accuracy rate.
Impact:
- Provides a reliable method for sEMG endpoint detection, overcoming ECG interference.
- Enhances the quality and trustworthiness of sEMG data in research and clinical practice.
- Facilitates more precise biomechanical and physiological assessments in various fields.
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