Journal
ENTROPY
Volume 18, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/e18020041
Keywords
EMG; complexity; wavelet packet; frequency band local-energy; Shannon entropy
Categories
Funding
- National Nature Science Foundation of China [61271142]
- Natural Science Foundation of Hebei, China [F2015203372]
- Youth Natural Science Foundation for Hebei Higher Education, China [QN2014074]
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An efficient analytical method for electromyogram (EMG) signals is of great significance to research the inherent mechanism of a motor-control system. In this paper, we proposed an improved approach named wavelet-packet-based local band spectral entropy (WP-LBSE) by introducing the concept of frequency band local-energy (ELF) into the wavelet packet entropy, in order to characterize the time-varying complexity of the EMG signals in the local frequency band. The EMG data were recorded from the biceps brachii (BB) muscle and triceps brachii (TB) muscle at 40 degrees, 100 degrees and 180 degrees of elbow flexion by 10 healthy participants. Significant differences existed among any pair of the three patterns (p < 0.05). The WP-LBSE values of the EMG signals in BB muscle and TB muscle demonstrated a decreased tendency from 40 degrees to 180 degrees of elbow flexion, while the distributions of spectral energy were decreased to a stable state as time periods progressed under the same pattern. The result of this present work is helpful to describe the time-varying complexity characteristics of the EMG signals under different joint angles, and is meaningful to research the dynamic variation of the activated motor units and muscle fibers in the motor-control system.
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