Human-computer interaction system design based on surface EMG signals

Author

Han Li ; Xi Chen ; Pengfei Li

Author_Institution

Nat. Key Lab. of Mechatron. Eng. & Control, Beijing Inst. of Technol., Beijing, China

fYear

2014

fDate

3-5 Dec. 2014

Firstpage

94

Lastpage

98

Abstract

Surface electromyography signals (SEMG) aquisition is a kind of multi-channel non-invasive detection method. In this paper, we designed a human-computer interaction system based on the multi-channel SEMG of hand motions. The system detects the forearm muscle multi-channel SEMG, the AR model is established to extract the signal eigenvalue and the artificial neural network classifier (BP) is utilized to distinguish the four different gestures that the results of pattern recognition are applied as the quad copter control signals. At last, the results of pattern recognition are used as control signal of aircraft to complete real-time interactive process.

Keywords

backpropagation; electromyography; feature extraction; gesture recognition; human computer interaction; muscle; neural nets; pattern recognition; AR model; SEMG aquisition; aircraft; artificial neural network classifier; complete real-time interactive process; forearm muscle multichannel SEMG; human-computer interaction system; multichannel noninvasive detection method; pattern recognition; quad copter control signals; surface EMG signals; surface electromyography signal aquisition; Electrodes; Flexible printed circuits; Human computer interaction; Muscles; Neural networks; Pattern recognition; Real-time systems; AR model; human-computer interaction; surface EMG;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling, Identification & Control (ICMIC), 2014 Proceedings of the 6th International Conference on

Conference_Location

Melbourne, VIC

Type

conf

DOI

10.1109/ICMIC.2014.7020734

Filename

7020734