PPG signal analysis and wavelet selection for feature extraction

Proceedings of International Scientific Conference „ALFATECH – Smart Cities and modern technologies“ (pp. 220-231) 

 

АУТОР(И) / AUTHOR(S): Zlatko Radovanović , Stevan Jokić , Ivan Jokić , Branislav Gerazov , Ana Kovačević , Nenad Gligorić

 

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DOI:  10.46793/ALFATECHproc25.220R

САЖЕТАК / ABSTRACT:

: Biomedical signals or biosignals are spatial, temporal or spatio-temporal records of a biological phenomenon. Biosignals contain information that is of great importance for understanding the specific physiological mechanisms of biological phenomena or the systems from which they originate. Signals provide important information about the internal state of organs, response to external stimuli, general state, general state of health and the state of various other parameters and are an indispensable part of modern medical diagnostic practice. The signal that arises as a result of the device’s action on the organism, the subject of this paper, is the signal obtained by the photoplethysmography (PPG) method. Certain artificial intelligence methods were used to analyze the PPG signal. In this paper, analysis using wavelet transformation will be used, and a special focus will be on the selection of wavelets (wavelets) that will be used for the purpose of machine learning. 

КЉУЧНЕ РЕЧИ / KEYWORDS:

characteristic parameters, diastolic peak, photoplethysmography (PPG), pulse width, machine learning, systolic peak, wavelet transform.

ПРОЈЕКАТ / ACKNOWLEDGEMENT:

ЛИТЕРАТУРА / REFERENCES:

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