Detailed muscle state analysis method based on real-time wavelet analysis of surface myoelectric potential

Abstract

Myoelectric refers to the use of electricity generated by muscles and is harnessed in the development of electrically powered prostheses, which are controlled by electromyographic (EMG) signals created in the residual musculature. Assistant professor Hidetoshi Nagai, Department of Artificial Intelligence, Kyushu Institute of Technology, Japan, is interested in surface myoelectric signals and is working on a project to develop technology that can advance their use. Nagai will capture motor unit activities using surface electromyography, which is easy to measure during exercise, and use this as the basis for more detailed muscle activity analysis. The methods Nagai has developed require no special equipment, other than the ability to sample at frequencies of several tens of kHz, and only require a single channel, which indicates the potential for more sophisticated analysis when multiple channels of information are present. It is also a simple and lightweight process that can be executed in real time. Conventional analysis and evaluation of muscle activity cannot be performed from the perspective of motor unit activity but Nagai has built on the basic premise that given that muscle activity is the sum of motor unit activities, the analysis of muscle activity should be based on the analysis of motor unit activity. He will analyse the surface EMG signal from the viewpoint of its component waveform the motor unit waveform so that muscle activity analysis can be performed as it should be.