CASPIAN JOURNAL
MANAGEMENT AND HIGH TECHNOLOGIES
Using emg patterns for human gait cycle recognition
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Read | Bobe A.S., Konyshev D.V., Vorotnikov S.A. Using emg patterns for human gait cycle recognition // Caspian journal : management and high technologies. — 2016. — №3. — pp. 21-28. |
Bobe A.S. - Engineer, Neurobotics Ltd, 4922 passage, 2/4 Yuzhnaya promzona, Moscow, Zelenograd, 124498, Russian Federation, a.bobe@neurobotics.ru
Konyshev D.V. - post-graduate student, Bauman Moscow State Technical University, 5/1 Baumanskaya 2nd St., Moscow, 105005, Russian Federation, konyshev-dmitri@yandex.ru
Vorotnikov S.A. - C.Sc. (Egineering), Associate professor, Bauman Moscow State Technical University, 5/1 Baumanskaya 2nd St., Moscow, 105005, Russian Federation
The article describes the system for human gait cycle recognition based on EMG signal processing. The analysis of electrical signals produced by lower limb muscles during gait is carried out. The correlation between EMG signal characteristics and actual leg movements during gait are researched. The method of signal preprocessing and adaptive segmentation for detection of muscle activation patterns is developed. The most informative muscles for analysis are selected basing on signal to noise ratio. The pattern sequences processing method for gait cycle coding is proposed. The algorithm is implemented in C# and has shown about 90 % recognition rate during testing. The system can be used for exoskeleton control as well as in functional diagnostics and sports medicine applications.
Key words: electromiography, biosignal processing, pattern recognition, lower limb muscles, gait, signal filtering, functional diagnostics, movement analysis, electrophysiology, электромиография, обработкабиосигналов, распознавание паттернов, мышцы нижних конечносте