Comparative Analysis of Methods for Differential Diagnosis of Parkinson's Disease and Essential Tremor Based on the Study of Wave Train Electrical Activity

The method for analyzing wave train electrical activity represents a novel approach to studying biomedical signals, focusing on identifying local maxima on wavelet spectrograms of signals and statistically analyzing their parameters. This method has been successfully applied to the analysis of epileptic discharges in laboratory animals, as well as human electroencephalographic and electromyographic signals. One of the first applications of the method was the differential diagnosis of neurodegenerative diseases, such as Parkinson's disease and essential tremor. Throughout the development of the method, two fundamentally different approaches to the differential diagnosis of Parkinson's disease and essential tremor have been explored. The first approach is based on the analysis of local maxima on wavelet spectrograms of accelerometer signals and the envelopes of electromyographic signals. The second approach is based on the analysis of local maxima on cross-wavelet spectrograms of the envelopes of electromyographic signals from antagonist muscle pairs. Both methods have been patented. This paper compares two aforementioned methods for differential diagnosis of Parkinson's disease and essential tremor, based on two years of clinical experience in applying these methods at the Research Center of Neurology. Conclusions are drawn regarding the advisability of using these methods in clinical practice. The prospects for applying the developed methods for the diagnosis of atypical parkinsonism are discussed.