Title :
Human forearm motion discrimination based on myoelectric signal by fuzzy inference
Author :
Kiso, Atsushi ; Seki, Hirokazu
Author_Institution :
Electr., Electron. & Comput. Eng., Chiba Inst. of Technol., Narashino, Japan
Abstract :
This paper describes a human forearm motion discrimination method based on the myoelectric signal by the fuzzy inference. In the conventional studies, the neural network is often used to estimate motion intention by the myoelectric signal and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signal. This study designs the membership function and the fuzzy rules from the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.
Keywords :
biomechanics; electromyography; fuzzy reasoning; medical signal processing; fuzzy inference; human forearm; membership function; motion discrimination; myoelectric hand simulator; myoelectric potential; myoelectric signal; Electromyography; Fuzzy neural networks; Hidden Markov models; Humans; Linear discriminant analysis; Motion analysis; Motion estimation; Neural networks; Root mean square; Samarium;
Conference_Titel :
Rehabilitation Robotics, 2009. ICORR 2009. IEEE International Conference on
Conference_Location :
Kyoto International Conference Center
Print_ISBN :
978-1-4244-3788-7
Electronic_ISBN :
1945-7898
DOI :
10.1109/ICORR.2009.5209587