Vol. 14, no.3, 2022
РусскийEnglish

MEDICAL PHYSICS



Method of wave train electrical activity analysis – the theoretical basis and application

Olga S. Sushkova, Alexei A. Morozov, Nadezhda G. Petrova, Margarita N. Khokhlova

Kotelnikov Institute of Radioengineering and Electronics of RAS, http://www.cplire.ru/
Moscow 125009, Russian Federation
E-mail: o.sushkova@mail.ru, morozov@cplire.ru, petrova@cplire.ru, margokhokhlova@gmail.com
Alexandra V. Gabova, Karine Yu. Sarkisova
Institute of Higher Nervous Activity and Neurophysiology of RAS, http://ihna.ru/
Moscow 117485, Russian Federation
E-mail: agabova@yandex.ru, karine.online@yandex.ru
Alexei V. Karabanov, Larisa A. Chigaleychik
Research Center of Neurology, https://www.neurology.ru/
Moscow 125367, Russian Federation
E-mail: doctor.karabanov@mail.ru, chigalei4ick.lar@yandex.ru

Received August 18, 2022, peer-reviewed August 25, 2022, accepted August 31, 2022


Abstract:: Classical methods for signal analysis are limited to describe either the global features or the local features. This paper proposes a new mathematically founded concept called wave train electrical activity analysis to investigate both local and global features in biomedical signals simultaneously. First, mathematical means for the investigation of the properties of the wave trains observed in the biomedical signals, histograms of wave train parameters and AUC diagrams, are discussed. Second, several examples of the practical application of the method of the wave train electrical activity analysis are considered. Specifically, its application is demonstrated in the investigation of epileptic seizures as well as the differential diagnosis of neurodegenerative diseases, Parkinson’s disease and essential tremor.

Keywords: wave train electrical activity, biomedical signals, wave train, wavelet spectrogram, AUC diagrams, ROC analysis, epileptic seizure, differential diagnosis, Parkinson's disease, essential tremor

UDC 519.67, 612.8, 53.083, 519.24, 004.93

RENSIT, 2022, 14(3):317-330e DOI: 10.17725/rensit.2022.14.317.

Full-text electronic version of this article - web site http://en.rensit.ru/vypuski/article/457/14(3)317-330e.pdf