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

^*Corresponding author for this work

Institute of Medical Informatics

Silesian University of Technology

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Advances in Intelligent Systems and Computing : Information Technology in Biomedicine. ITIB 2019.
Volume	1011
Publisher	Springer, Cham
Publication date	2019
Pages	473-480
ISBN (Print)	978-3-030-23761-5
ISBN (Electronic)	978-3-030-23762-2
DOIs	https://doi.org/10.1007/978-3-030-23762-2_42
Publication status	Published - 2019
Event	7th International Conference on Information Technology in Biomedicine - Kamień Śląski, Poland Duration: 18.06.2019 → 20.06.2019 Conference number: 229749

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 9 Industry, Innovation, and Infrastructure

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

Cite this

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. (Vol. 1011, pp. 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",

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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. . vol. 1011, Springer, Cham, pp. 473-480, 7th International Conference on Information Technology in Biomedicine
, Kamień Śląski, Poland, 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. . Vol. 1011 Springer, Cham, 2019. p. 473-480.

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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

UN SDGs

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