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

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.

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).

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_max (Pearson correlation coefficient of 0.51 +/- 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/- 0.17).

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.

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.

Keywords: ballistocardiography; cuff-less blood pressure monitoring; force sensors; shared biomedical database; unobtrusive cardiac monitoring.

Figure 1

Two sample ballistocardiograms (BCGs) acquired with a bed system using electromechanical film and load cell sensing technologies along with a time-aligned electrocardiogram. The BCG signals have been scaled/shifted vertically. ECG: electrocardiogram; LC BCG: load cell BCG; EMFi: electromechanical film.

Figure 2

Approximate EMFi and load cell locations (not drawn to scale) (left) and the actual film locations (right), where the mattress has been removed and is leaning on the wall next to the bed.

Figure 3

Image of the bed system from another angle, accompanied by the CardioCap 5 patient monitor. The analog conditioning and National Instruments data collection hardware can be seen under the bed.

Figure 4

Signal management and acquisition. COP: center of position.

Figure 5

Bed system database excerpt for ten participants.

Figure 6

Representative raw signals collected from participant X1003.

Figure 7

Various cardiopulmonary waveforms and their associated features. The reconstructed brachial artery pressure (reBAP) waveform acquired by a Finapres Finometer PRO^® is scaled at 100 mmHg/volt. The BCG signals were scaled/shifted vertically and preprocessed as described in Section 2.4. ECG and PPG data are collected with a GE Datex Ohmeda CardioCap 5 patient monitor.

Figure 8

Representative signals collected from the Finapres Finometer PRO^®. As in Figure 7, the reBAP signal is scaled at 100 mmHg/volt. The interbeat interval, stroke volume, and dP/dt_max are scaled at 1000 ms/volt, 100 mL/volt, and 1 mmHg/s/volt, respectively.

Figure 9

Boxplots of the correlation coefficients for the pulse pressure (PP)–stroke volume (SV) and pulse arrival time (PAT)–systolic pressure (SP) predictor–response relationships.

Figure 10

Boxplots of the correlation coefficients for the predictor–response pairs described in Table 3. using the BCGs measured from Film 0. MP: multiple parameters (IJ time, IJ amp, JK time, and JK amp).