Multielectrode Surface Electromyography for Noninvasive Estimation of Motor Unit Size and Firing Patterns

• Main Authors: Tzyh-Yi Sun, 孫自宜
• Other Authors: Jia-Jin Chen
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/28545830339937829152

博士 === 國立成功大學 === 醫學工程研究所 === 87 === To noninvasively estimate the motor unit size and firing patterns, we present a novel surface EMG measurement system consisting of a surface multielectrode with 4 pin electrodes and a pair of surface disk electrodes. The surface motor unit action potential (MUAP) measured with the multielectrode, called multielectrode surface EMG (MSEMG), was spatially filtered to localize the sensing area and reduce the noise. In addition, a modified decomposition algorithm, considering the geometrical configuration of the multielectrode, was designed to identify the individual MUAPs in the measured MSEMG. To quantify the motor unit sizes, the trigger-averaged method had been employed. The identified MUAP was subsequently used as the triggering source for the EMG signals recorded by the surface disk electrodes. From a pool of 34 subjects with neuromuscular diseases and 14 normal subjects, the median amplitudes of surface-disk EMG after spike-triggered averaging, called MSEMG-MUAP, correlated well (r=0.82, P<0.0001) with those of macro EMG. Moreover, the MSEMG-MUAP recording during a ramp force contraction exhibited the common size principle phenomenon during motor unit recruitment. The results of this study demonstrate that the MSEMG-MUAP measurement is a feasible approach for estimating the motor unit size from the skin surface. To quantify the motor unit firing patterns in patients with central or peripheral lesions, the MSEMG was used to noninvasively measure the MUAPs for studying single motor unit firing patterns. The joint interval histogram representation was adopted herein, which was quantified by singular value decomposition (SVD) method. Computer simulations were carried out to confirm the meanings of two SVD parameters, the eigenvalue corresponding to the positive-slope eigenvector (PEV) and that corresponding to the negative-slope one (NEV). Results reveal that the NEV reflects the instantaneous firing variability, which is unaffected by human interventions, while the PEV/NEV ratio exhibits the relative effect of a trend in the firing pattern. In human studies, sessions of multielectrode surface EMG were recorded from first dorsal interosseous muscle during steady contraction in stroke, myopathy, neuropathy, and healthy control groups, with 16 subjects each. Results show most of the PEV/NEV ratio (74.0%) from normal subjects were less than 1, while 84.4% of that from the stroke patients were greater than 1. Different to stroke patients, wide spread distributions in both PEV and NEV were observed in subjects with neuromuscular diseases. These results suggest that SVD parameters can be used to differentiate the firing characteristics of patients with central or peripheral lesions.