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Surface electromyogram signals classification based on bispectrum

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4 Author(s)
Orosco, E. ; Fac. de Ing., Univ. Nac. de San Juan, San Juan, Argentina ; López, N. ; Soria, C. ; di Sciascio, F.

This paper bispectrum is used to classify human arm movements and control a robotic arm based on upper limb's surface electromyogram signals (sEMG). We use bispectrum based on third-order cumulant to parameterize sEMG signals and classify elbow flexion and extension, forearm pronation and supination, and rest states by an artificial neural network (ANN). Finally, a robotic manipulator is controlled based on classification and parameters extracted from the signals. All this process is made in real-time using QNX ® operative system.

Published in:

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Date of Conference:

Aug. 31 2010-Sept. 4 2010