Aim: To evaluate the clinical usability of mechanomyography (MMG) in the evaluation of upper-limb spasticity states of hemiplegia patients with likelihood ratio analysis. Methods: The MMG signals from the 30 hemiplegia patients’ biceps and triceps were recorded with three-dimensional wireless accelerometer (Trigno Wireless System, Delsys Inc), when they extended or bent their elbow passively. At the same time, the physiotherapist assessed the MAS (Modified Ashworth Scale) of all the patients who participated in the study and would be divided them into four groups based on the MAS values (MAS0, MAS1, MAS1+ and MAS2). The MMG sensors were built with triaxial accelerometers named as X, Y and Z that represent the muscle fibers lengthwise movement, the cross movement and the vertical the muscle moving direction, respectively. The root mean square (RMS) value of the MMG signal was calculated for analysis. Likelihood ratio analysis were used in the study. Results: All of the variables of the X, Y, Z axis of signals of MMG of BB and TB have related with muscle spasticity grading during passive elbow flexion in multinomial logistic regression (P=0.000, P<0.001). The regression coefficient of Y axis signal of MMG of BB is the largest. The 5 variables of the X, Y, Z axis of signals of MMG of BB and X, Y axis of TB have related with Muscle spasticity grading during passive elbow extension in multinomial logistic regression (P=0.000, P<0.001). The regression coefficient of Y axis signal of MMG of BB is the largest in equation and the Y axis signal of MMG of TB is second large. Conclusions: The effect of agonist is more than the antagonist during the MAS assessment, especially the muscle fibers cross movement and the vertical movement by the MMG assessment.
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