Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance

Abstract With a sound sensing system using stochastic resonance (4SR), it became possible to obtain an acoustic pulse wave (APW)—a waveform created via a mixture of apex beat and heart sound. We examined 50 subjects who were healthy, with no underlying cardiovascular diseases. We could determine bou...

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Autores principales:	Etsunori Fujita, Masahiro Horikawa, Yoshika Nobuhiro, Shinichiro Maeda, Shigeyuki Kojima, Yumi Ogura, Kohji Murata, Tomohiko Kisaka, Kazushi Taoda, Shigehiko Kaneko, Masao Yoshizumi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/93c0a43ce5494fa9b125a4255e32b734
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spelling	oai:doaj.org-article:93c0a43ce5494fa9b125a4255e32b7342021-12-02T14:33:57ZExtraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance10.1038/s41598-021-92983-62045-2322https://doaj.org/article/93c0a43ce5494fa9b125a4255e32b7342021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92983-6https://doaj.org/toc/2045-2322Abstract With a sound sensing system using stochastic resonance (4SR), it became possible to obtain an acoustic pulse wave (APW)—a waveform created via a mixture of apex beat and heart sound. We examined 50 subjects who were healthy, with no underlying cardiovascular diseases. We could determine boundary frequency (BF) using APW and phonocardiogram signals. APW data was divided into two bands, one from 0.5 Hz to BF, and a second one from BF to 50 Hz. This permitted the extraction of cardiac apex beat (CAB) and cardiac acoustic sound (CAS), respectively. BF could be expressed by a quadratic function of heart rate, and made it possible to collect CAB and CAS in real time. According to heart rate variability analysis, the fluctuation was 1/f, which indicated an efficient cardiac movement when heart rate was 70 to 80/min. In the frequency band between 0.5 Hz and BF, CAB readings collected from the precordial region resembled apex cardiogram data. The waveforms were classified into five types. Therefore, the new 4SR sensing system can be used as a physical diagnostic tool to obtain biological pulse wave data non-invasively and repeatedly over a long period, and it shows promise for broader applications, including AI analysis.Etsunori FujitaMasahiro HorikawaYoshika NobuhiroShinichiro MaedaShigeyuki KojimaYumi OguraKohji MurataTomohiko KisakaKazushi TaodaShigehiko KanekoMasao YoshizumiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Etsunori Fujita Masahiro Horikawa Yoshika Nobuhiro Shinichiro Maeda Shigeyuki Kojima Yumi Ogura Kohji Murata Tomohiko Kisaka Kazushi Taoda Shigehiko Kaneko Masao Yoshizumi Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
description	Abstract With a sound sensing system using stochastic resonance (4SR), it became possible to obtain an acoustic pulse wave (APW)—a waveform created via a mixture of apex beat and heart sound. We examined 50 subjects who were healthy, with no underlying cardiovascular diseases. We could determine boundary frequency (BF) using APW and phonocardiogram signals. APW data was divided into two bands, one from 0.5 Hz to BF, and a second one from BF to 50 Hz. This permitted the extraction of cardiac apex beat (CAB) and cardiac acoustic sound (CAS), respectively. BF could be expressed by a quadratic function of heart rate, and made it possible to collect CAB and CAS in real time. According to heart rate variability analysis, the fluctuation was 1/f, which indicated an efficient cardiac movement when heart rate was 70 to 80/min. In the frequency band between 0.5 Hz and BF, CAB readings collected from the precordial region resembled apex cardiogram data. The waveforms were classified into five types. Therefore, the new 4SR sensing system can be used as a physical diagnostic tool to obtain biological pulse wave data non-invasively and repeatedly over a long period, and it shows promise for broader applications, including AI analysis.
format	article
author	Etsunori Fujita Masahiro Horikawa Yoshika Nobuhiro Shinichiro Maeda Shigeyuki Kojima Yumi Ogura Kohji Murata Tomohiko Kisaka Kazushi Taoda Shigehiko Kaneko Masao Yoshizumi
author_facet	Etsunori Fujita Masahiro Horikawa Yoshika Nobuhiro Shinichiro Maeda Shigeyuki Kojima Yumi Ogura Kohji Murata Tomohiko Kisaka Kazushi Taoda Shigehiko Kaneko Masao Yoshizumi
author_sort	Etsunori Fujita
title	Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
title_short	Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
title_full	Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
title_fullStr	Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
title_full_unstemmed	Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
title_sort	extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/93c0a43ce5494fa9b125a4255e32b734
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Extraction of apex beat waveform from acoustic pulse wave by sound sensing system using stochastic resonance

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