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DOI: 10.17586/1023-5086-2020-87-12-67-75

УДК: 004.021:004.415.2:004.622:004.623:004.624:004.67:681.518.3:681.586004.93'1:004.932.2

Automatic estimation of human blood pressure based on the joint analysis of morphological and spectral parameters of the photoplethysmogram67-75

Zaluskaya V.S., Karaseva, E.A., Lutsiv, V.R.

Full text «Opticheskii Zhurnal»

Full text on elibrary.ru

Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Залуская В.С., Карасева Е.А., Луцив В.Р. Автоматическое оценивание давления крови человека на основе совместного анализа морфологических и спектральных параметров фотоплетизмограммы // Оптический журнал. 2020. Т. 87. № 12. С. 67 –75. http://doi.org/10.17586/1023-5086-2020-87-12-67-75

For citation (Journal of Optical Technology):

V. S. Zaluskaya, E. A. Karaseva, and V. R. Lutsiv, "Automatic estimation of human blood pressure based on the joint analysis of morphological and spectral parameters of the photoplethysmogram," Journal of Optical Technology. 87(12), 750-755 (2020). https://doi.org/10.1364/JOT.87.000750

Abstract:

A method for the automatic assessment of the systolic and diastolic blood pressure of people by means of a joint analysis of spectral and morphological features of the pulse waveform on a photoplethysmogram is proposed. For extraction of the used features, algorithms have been developed for the preliminary processing of the original photoplethysmogram signal, its automatic division into periods corresponding to individual cardiac cycles, and the selection of characteristic features of the pulse waveform in each period. The selected signal periods are used to calculate the spectral characteristics of the photoplethysmogram, and the expediency of using triplets of successive cycles for this purpose is shown experimentally. The parameters calculated from the features of the pulse waveform and its calculated spectral characteristics are automatically analyzed using a specially trained artificial neural network, which forms an estimate of the patient’s systolic and diastolic blood pressure at the output. The expediency of automatic determination of blood pressure based on the joint analysis of spectral and morphological characteristics of photoplethysmograms is shown experimentally.

Keywords:

photoplethysmogram, blood pressure measurement, neural network, spectral features, morphological features

OCIS codes: 170.3890, 170.1610, 280.1415, 120.5240, 230.3990, 230.0230, 280.4788, 080.1753

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