Refinement and evaluation of a hydraulic bed sensor

Abstract

Research indicates that long-term monitoring of vital signs and activity in elderly adults may provide opportunities for maintaining quality-of-life and extending independence into later years. Such a strategy requires development of a system to collect this data while imposing minimal intrusion into the lives of those being monitored. To further this goal, we have developed a hydraulic bed sensor to non-invasively monitor heartbeat and respiration during sleep. This paper describes the refinement of our developed prototype and signal processing methods, along with an evaluation of the robustness of our algorithms and results from testing. An evaluation of our sensor on a group of five diverse subjects (ranging in age from 24 to 67, two with cardiac history), in three different positions, demonstrates accuracy within 8 beats per minute up to 97.5% of the time.

Figures

Fig. 1

Positioning of bed sensor for testing

Fig. 2

Heartbeats detected from synthesized signal: (a) shows the cardiac component (extracted from real data), (b) shows the synthesized respiratory component (at 4 times the original captured frequency and ¼ the amplitude), (c) is the resulting composite (our synthesized signal), (d) shows detection of heartbeats from our algorithm compared to the ground truth.

Fig. 3

Detecting heartbeats from real data. Here, the subject was asked to breathe at approximately 30 breaths per minute: (a) shows the collected signal, (b) shows the extracted cardiac component, (c) shows the extracted respiratory component, (d) shows the respiratory ground truth (from a piezoelectric respiratory belt), (e) demonstrates identification of heartbeats by the hydraulic sensor and algorithm compared to the ground truth. Note that the algorithm detects heartbeats directly from (a); (b) is only shown for reference and comparison to (a).

Fig. 4

15-second segment of data from subject #5. This figure shows that detected heartbeats (the low-frequency signal) correspond well with the ground truth (the pulsed signal).

Fig. 5

Correspondence of the number of heartbeats detected via the hydraulic sensor (asterisks) and ground truth (circles). These data are for subject #5, using a WPPD window size of 150 ms and post-WPPD filter cutoff frequency of 1.5 Hz. Segments showing zero heartbeats were periods of noise due to movement.