FEATURES ANALYSIS AND SYSTEM IDENTIFICATION OF MECHANOMYOGRAPHY AND ELECTROMYOGRAPHY UNDER TRANSCRANIAL MAGNETIC STIMULATION

Author:

ZHANG HANYANG1,ZHONG YANBIAO2,ZHANG YUE1,YANG KE1ORCID,XIA CHUNMING1,SHAN CHUNLEI2

Affiliation:

1. Department of Mechanical Engineering, East China University of Science and Technology, Shanghai 200237, P. R. China

2. School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New District, Shanghai 201203, P. R. China

Abstract

Transcranial magnetic stimulation (TMS) is an electrophysiological technique that uses alternating magnetic fields to deliver electric current and stimulate the cerebral cortex. When TMS is used for the evaluation of brain diseases, it is necessary to detect the contraction of the corresponding muscles in the cerebral cortex stimulated by TMS, and the muscle activity referred to as motor evoked potential (MEP). This study simultaneously recorded the mechanomyography (MMG) and electromyography (EMG) from the right abductor pollicis brevis muscle during TMS with different intensities in order to observe whether the MEP parameters from MMG signals showed similar trait of EMG recordings. Moreover, the subspace method (N4SID) and transfer function were used to identify the TMS–MMG system. In this system, the input was a pulse signal of TMS, and the output was the MMG signal detected from the target muscle. The TMS–MMG system was identified as a fourth-order model. This study also analyzed the internal features of the system and demonstrated that the poles of healthy subjects were distributed in a range, and the gain increased with the increase of the TMS intensity. It was found that MMG signals can be used as diagnostic indicators of TMS, and the TMS–MMG model can be used to further explore the details of how TMS generates responses measured with MMG.

Funder

National Key Research and Development Program of China

Program of Shanghai Academic Research Leader

Publisher

World Scientific Pub Co Pte Ltd

Subject

Biomedical Engineering

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