| Title |
Evaluation of SEMG Amplitude Estimation Parameters by Amount of Probabilistic Information |
| DOI |
https://doi.org/10.5370/KIEE.2022.71.1.261 |
| Keywords |
surface EMG; amplitude estimation parameters; information theory |
| Abstract |
Optimal Amplitude estimation from the SEMG(surface electromyogram) signal is important because it can be used potential sources to control prosthetics and robotics. In this paper, four representative SEMG amplitude estimation parameters(ARV:average rectified value, RMS:root mean square, MTA:mean turn amplitude, MSA:mean spike amplitude) were evaluated based on probabilistic information theory, which determine the amount of information that each parameter is able to extract from SEMG signal. Surface EMG signals from eleven subjects were recorded in biceps brachii muscle with constant isometric 20, 50, and 80%MVC contractions.
The parameters were investigated by the amount of mutual information between stimulus(contraction level) and response(amplitude estimation parameter) variables. Results of this study show there are no statistical significant differences(p<0.05) in the point of amount of information among the four variables. Although the evaluation method suggested here were applied to amplitude estimation parameters, it can also be considered as alternative tool to evaluate various processing technique in different areas of surface EMG analysis. |