Quality improvement of diagnosis of the electromyography data based on statistical characteristics of the measured signals

Research and systematization of motor disorders, taking into account the clinical and neurophysiologic phenomena, are important and actual problem of neurology. The article describes a technique for decomposing surface electromyography (EMG), using Principal Component Analysis. The decomposition is achieved by a set of algorithms that uses a specially developed for analyze EMG. The accuracy was verified by calculation of Mahalanobis distance and Probability error.