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Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters.

Authors :
Carlson C
Turpin VR
Suliman A
Ade C
Warren S
Thompson DE
Source :
Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Dec 29; Vol. 21 (1). Date of Electronic Publication: 2020 Dec 29.
Publication Year :
2020

Abstract

Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms.<br />Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters).<br />Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/- 0.15), dP/dt <subscript>max</subscript> (Pearson correlation coefficient of 0.51 +/- 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/- 0.17).<br />Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume.<br />Significance: To the best of the authors' knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.

Details

Language :
English
ISSN :
1424-8220
Volume :
21
Issue :
1
Database :
MEDLINE
Journal :
Sensors (Basel, Switzerland)
Publication Type :
Academic Journal
Accession number :
33383739
Full Text :
https://doi.org/10.3390/s21010156