Use of Sample Entropy Extracted from Intramuscular EMG Signals for the Estimation of Force
This study investigates the use of sample entropy as a feature extracted from intramuscular electromyography (EMG) for the estimation of force. Grasping force and intra-muscular EMG) signals were measured in 10 able-bodied subjects. Constraint sample entropy (CSE) was extracted from the EMG signal (window size of 200 ms). The association be-tween the CSE and force was modeled using an artificial neural network. The accuracy of estimation was on average R2 = 0.89 ± 0.05 and root mean square difference (RMSD) = 6.67 ± 2.17 N). It was concluded that sample entropy does capture the dynamics in the intramuscular EMG, and that a single channel of intramuscular EMG can be used for muscle force estimation. The information of muscle force is necessary in proportional myoelectric control.
Keywordsgrasping force intramuscular EMG sample entropy proportional control
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