Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms

Szymon Sieciński; Paweł S. Kostka; Ewaryst J. Tkacz; Natalia Piaseczna; Marta Wadas

doi:10.1007/978-3-030-23762-2_42

Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms

Szymon Sieciński^*, Paweł S. Kostka, Ewaryst J. Tkacz, Natalia Piaseczna, Marta Wadas

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Medizinische Informatik

Silesian University of Technology

Abstract

Heart rate variability (HRV) is the physiological variation of time between consecutive heart beats. Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular vibrations transmitted to the chest wall. Mobile devices can monitor health parameters thanks to embedded sensors. In this study we compare HRV indices calculated from heart beats obtained from reference beats and tested beat detection algorithm on three SCG signals. Proposed algorithm consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was compared to reference beat detector and defined as sensitivity (Se) and positive predictive value (PPV). We achieved average Se = 0.958 and PPV = 0.912, and in the best case Se =1.000 and PPV =1.000 for tested beat detector. HRV indices are influenced by the performance of heart beat detector. The smallest differences between HRV indices calculated from heart beats determined by different detectors were achieved for mean inter-beat interval, RMSSD, pNN50, PLF, PHF and LF/HF.

Originalsprache	Englisch
Titel	Advances in Intelligent Systems and Computing : Information Technology in Biomedicine. ITIB 2019.
Band	1011
Herausgeber (Verlag)	Springer, Cham
Erscheinungsdatum	2019
Seiten	473-480
ISBN (Print)	978-3-030-23761-5
ISBN (elektronisch)	978-3-030-23762-2
DOIs	https://doi.org/10.1007/978-3-030-23762-2_42
Publikationsstatus	Veröffentlicht - 2019
Veranstaltung	7th International Conference on Information Technology in Biomedicine - Kamień Śląski, Polen Dauer: 18.06.2019 → 20.06.2019 Konferenznummer: 229749

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10.1007/978-3-030-23762-2_42

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Sieciński, S., Kostka, P. S., Tkacz, E. J., Piaseczna, N., & Wadas, M. (2019). Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms. in Advances in Intelligent Systems and Computing: Information Technology in Biomedicine. ITIB 2019. (Band 1011, S. 473-480). Springer, Cham. https://doi.org/10.1007/978-3-030-23762-2_42

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title = "Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms",

abstract = "Heart rate variability (HRV) is the physiological variation of time between consecutive heart beats. Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular vibrations transmitted to the chest wall. Mobile devices can monitor health parameters thanks to embedded sensors. In this study we compare HRV indices calculated from heart beats obtained from reference beats and tested beat detection algorithm on three SCG signals. Proposed algorithm consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was compared to reference beat detector and defined as sensitivity (Se) and positive predictive value (PPV). We achieved average Se = 0.958 and PPV = 0.912, and in the best case Se =1.000 and PPV =1.000 for tested beat detector. HRV indices are influenced by the performance of heart beat detector. The smallest differences between HRV indices calculated from heart beats determined by different detectors were achieved for mean inter-beat interval, RMSSD, pNN50, PLF, PHF and LF/HF.",

author = "Szymon Sieci{\'n}ski and Kostka, {Pawe{\l} S.} and Tkacz, {Ewaryst J.} and Natalia Piaseczna and Marta Wadas",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 7th International Conference on Information Technology in Biomedicine<br/>, ITIB 2019 ; Conference date: 18-06-2019 Through 20-06-2019",

year = "2019",

doi = "10.1007/978-3-030-23762-2_42",

language = "English",

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volume = "1011",

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booktitle = "Advances in Intelligent Systems and Computing",

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}

Sieciński, S, Kostka, PS, Tkacz, EJ, Piaseczna, N & Wadas, M 2019, Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms. in Advances in Intelligent Systems and Computing: Information Technology in Biomedicine. ITIB 2019. . Bd. 1011, Springer, Cham, S. 473-480, 7th International Conference on Information Technology in Biomedicine
, Kamień Śląski, Polen, 18.06.19. https://doi.org/10.1007/978-3-030-23762-2_42

Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms. / Sieciński, Szymon; Kostka, Paweł S.; Tkacz, Ewaryst J. et al.
Advances in Intelligent Systems and Computing: Information Technology in Biomedicine. ITIB 2019. . Band 1011 Springer, Cham, 2019. S. 473-480.

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms

AU - Sieciński, Szymon

AU - Kostka, Paweł S.

AU - Tkacz, Ewaryst J.

AU - Piaseczna, Natalia

AU - Wadas, Marta

N1 - Conference code: 229749

PY - 2019

Y1 - 2019

N2 - Heart rate variability (HRV) is the physiological variation of time between consecutive heart beats. Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular vibrations transmitted to the chest wall. Mobile devices can monitor health parameters thanks to embedded sensors. In this study we compare HRV indices calculated from heart beats obtained from reference beats and tested beat detection algorithm on three SCG signals. Proposed algorithm consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was compared to reference beat detector and defined as sensitivity (Se) and positive predictive value (PPV). We achieved average Se = 0.958 and PPV = 0.912, and in the best case Se =1.000 and PPV =1.000 for tested beat detector. HRV indices are influenced by the performance of heart beat detector. The smallest differences between HRV indices calculated from heart beats determined by different detectors were achieved for mean inter-beat interval, RMSSD, pNN50, PLF, PHF and LF/HF.

AB - Heart rate variability (HRV) is the physiological variation of time between consecutive heart beats. Seismocardiography (SCG) is a non-invasive method of analyzing and recording cardiovascular vibrations transmitted to the chest wall. Mobile devices can monitor health parameters thanks to embedded sensors. In this study we compare HRV indices calculated from heart beats obtained from reference beats and tested beat detection algorithm on three SCG signals. Proposed algorithm consists of signal preprocessing, RMS envelope calculation and peak finding. Algorithm performance was compared to reference beat detector and defined as sensitivity (Se) and positive predictive value (PPV). We achieved average Se = 0.958 and PPV = 0.912, and in the best case Se =1.000 and PPV =1.000 for tested beat detector. HRV indices are influenced by the performance of heart beat detector. The smallest differences between HRV indices calculated from heart beats determined by different detectors were achieved for mean inter-beat interval, RMSSD, pNN50, PLF, PHF and LF/HF.

U2 - 10.1007/978-3-030-23762-2_42

DO - 10.1007/978-3-030-23762-2_42

M3 - Conference contribution

SN - 978-3-030-23761-5

VL - 1011

SP - 473

EP - 480

BT - Advances in Intelligent Systems and Computing

PB - Springer, Cham

T2 - 7th International Conference on Information Technology in Biomedicine<br/>

Y2 - 18 June 2019 through 20 June 2019

ER -

Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms

Abstract

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