DocumentCode :
3138225
Title :
A Portable MIDI Controller Using EMG-Based Individual Finger Motion Classification
Author :
Bitar, Fadi ; Madi, Nasr ; Ramly, Edmond ; Saghir, Mazen ; Karameh, Fadi
Author_Institution :
American Univ. of Beirut, Beirut
fYear :
2007
fDate :
27-30 Nov. 2007
Firstpage :
138
Lastpage :
141
Abstract :
Classifying the motion of the five fingers of the hand using non-invasive bio-signal readings from the forearm is still an unsolved research challenge. Its solution is relevant to hands-free remote control devices, on-stage live performances, consumer entertainment, the video game industry, and most importantly the design of hand prosthetics for amputees. This paper proposes a solution that uses the continuous wavelet transform (CWT) decompositions of electromyography (EMG) signals from the forearm muscles, and Support Vector Machines (SVM) classification. The resulting design is a low cost, low power and low complexity portable embedded system that is strapped to the arm, where it collects EMG signals, classifies them in real-time, and sends the resulting class labels via Bluetooth to a remote interface. These labels are then converted into musical instrument digital interface (MIDI) commands that can be used to control any MIDI-controllable device. While the design is still at the prototype stage at best, it provides a proof-of-concept of non-invasive finger motion classification solely based on EMG readings from the forearm muscles. Experimental simulation of the expected system achieved 91% accuracy.
Keywords :
Bluetooth; biomechanics; electromyography; feature extraction; learning (artificial intelligence); medical signal processing; musical instruments; prosthetics; signal classification; support vector machines; telecontrol; wavelet transforms; Bluetooth; EMG; SVM; consumer entertainment; continuous wavelet transform; electromyography; embedded system; finger motion classification; forearm muscle; hand prosthetics; hands-free remote control device; musical instrument digital interface command; noninvasive bio-signal reading; portable MIDI controller; support vector machine; video game industry; Continuous wavelet transforms; Electromyography; Fingers; Games; Industrial control; Motion control; Muscles; Support vector machine classification; Support vector machines; Toy industry; Classification; Electromyography; Hand prosthetics; Support vector machines; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference, 2007. BIOCAS 2007. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-1524-3
Electronic_ISBN :
978-1-4244-1525-0
Type :
conf
DOI :
10.1109/BIOCAS.2007.4463328
Filename :
4463328
Link To Document :
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