| Autor: |
Larisa A. Chigaleychik, A. V. Gabova, Olga S. Sushkova, Alexei A. Morozov, A. V. Karabanov |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Advances in Intelligent Systems and Computing ISBN: 9789811578335 |
| Popis: |
An investigation of the 0.5–4 Hz little-studied frequency range of acceleration signals (ACC) was performed in patients with Parkinson’s disease (PD) and essential tremor (ET). In this frequency range, new neurophysiological regularities were revealed. A new method was used to analyze the wave train electrical activity of the muscles based on the analysis of Morlet wavelet spectrograms and ROC curves. The method idea is to find local extrema (named “wave trains”) in the Morlet wavelet spectrogram and to calculate various parameters describing these wave trains: the number of wave trains per second, the duration of the wave trains in periods, the leading frequency of the wave trains, the width of the wave train frequency band. The AUC functional dependence on the values of the bounds of the ranges of these parameters is investigated. This method is aimed at studying changes in the time-frequency parameters (the shape) of signals including changes that are not related to the power spectral density of the signal. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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