A composite evaluation indicator of wavelet denoising in surface electromyography of rhesus
monkey(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2020年第9期
- Page:
- 1169-1174
- Research Field:
- 医学人工智能
- Publishing date:
Info
- Title:
- A composite evaluation indicator of wavelet denoising in surface electromyography of rhesus
monkey
- Author(s):
- LIU Ruoxi1; RAO Jiasheng1; 2; WEI Ruihan1; ZHAO Can2; 3; YANG Zhaoyang2; 4; LI Xiaoguang1; 2; 4
- 1. Beijing Key Laboratory for Biomaterials and Neural Regeneration, School of Biological Science and Medical Engineering, Beihang
University, Beijing 100083, China 2. Beijing International Cooperation Bases for Science and Technology on Biomaterials and Neural
Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100083, China 3. School
of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100083, China 4. Department of Neurobiology,
School of Basic Medicine, Capital Medical University, Beijing 100069, China
- Keywords:
- rhesus monkey surface electromyography denoising coefficient of variation evaluation indicator
- PACS:
- R318
- DOI:
- 10.3969/j.issn.1005-202X.2020.09.017
- Abstract:
- The denoising of the surface electromyography (sEMG) of rhesus monkey has great significance for the kinematics
research, and its effect directly affects the accuracy of motor function evaluation. Aiming at the problem of the lack of method
for comprehensively evaluating sEMG denoising effect, a composite evaluation indicator determined by the coefficient of
variation is proposed. The original indicators such as signal-to-noise ratio, root-mean-square error, smoothness and cross
correlation coefficient were firstly calculated, and then were processed with positive management and averaging.
Subsequently, the coefficient of variation was used to calculate the weights, and the preprocessed original indicators were
combined into a composite indicator. Further simulation experiments and actual experimental data calculations show that the
composite indicator proposed in this study achieves a sensitivity of 1.72%±0.02% and an accuracy of 83.64%, which are
significantly higher than the sensitivity (1.04%±0.01%) and the accuracy (75.76%) of existing indicator. The proposed
composite indicator which can be used to better represent the wavelet denoising effect has certain application value in the
study of the behavior of rhesus monkeys.
Last Update: 2020-09-25