Vol. 11, no.2, 2019
РусскийEnglish
MEDICAL PHYSICS
INVESTIGATION OF THE 0.5-4 HZ LOW-FREQUENCY RANGE IN THE WAVE TRAIN ELECTRICAL ACTIVITY OF MUSCLES IN PATIENTS WITH PARKINSON'S DISEASE AND ESSENTIAL TREMOR
Olga S. Sushkova, Aleksey A. Morozov
Kotelnikov Institute of Radioengineering and Electronics of RAS, http://www.cplire.ru
Moscow 125009, Russian Federation
Alexandra V. Gabova
Institute of Higher Nervous Activity and Neurophysiology of RAS, http://ihna.ru/
Moscow 117485, Russian Federation
Alexei V. Karabanov, Larisa A. Chigaleychik
Research Center of Neurology of RF Ministry of Education and Science, https://www.neurology.ru/
Moscow 125367, Russian Federation
Received 25.06.2019, accepted 29.06.2019
Abstract. An investigation of the 0.5-4 Hz little-studied frequency range electromyograms (EMG) was performed in patients with Parkinson's disease (PD) and essential tremor (ET). In this frequency range, new neurophysiological regularities were revealed that were not previously described in the literature. There are statistically significant differences between groups of patients with PD/ET and a control group of subjects. A new method for analyzing wave train electrical activity of the muscles based on the wavelet analysis and ROC analysis was used. This method enables to study the time-frequency features of EMG signals in patients with PD and ET. The idea of the method is to find local maxima (that correspond to the wave trains) in the wavelet spectrogram and to calculate various characteristics describing these maxima: the leading frequency, the duration in periods, the bandwidth, the number of wave trains per second. The degree of difference of the group of patients from the control group of subjects is analyzed in the space of these parameters. ROC analysis is used for this purpose. The functional dependence of AUC (the area under the ROC curve) on the values of the bounds of the ranges of the parameters under consideration is investigated. This method is aimed at studying changes in the time-frequency characteristics (the shape) of signals including changes that are not related to the power spectral density of the signal. The application of the method allowed revealing new statistical regularities in EMG signals, which previously were not detected using standard spectral methods based on the analysis of the power spectral density of signals.
Keywords: Parkinson's disease, essential tremor, trembling hyperkinesis, electromyogram, EMG, tremor, wave trains, wavelet spectrogram
UDC 519.67, 612.8, 53.088
RENSIT, 2019, 11(2):225-236 DOI: 10.17725/rensit.2019.11.225
Full-text electronic version of this article - web site http://en.rensit.ru/vypuski/article/283/11(2)225-236e.pdf