Micro-vibration based health monitoring: effect of external factors on ballistocardiogram signals

Vital health parameters can provide a staggering amount of information about the general health of an individual, and continuous vital monitoring plays a significant role in the identification of clinical deterioration. Ballistocardiography (BCG), a technique to measure the micro-vibrations caused by cardiac contractions and body movements, allows for long-term non-invasive, contactless vitals monitoring. However, the effect of external factors, such as body posture, sensor position, bed angle, and mattress thickness, on the BCG signals remains to be analyzed in detail. Hence, this research focuses on characterizing BCG signals concerning the aforementioned factors by employing Dozee, a BCG-based contactless continuous vital parameters monitoring system, in a simulated use environment. Data was gathered from 10 volunteers, and the waveforms for HR and RR were extracted. Unsupervised learning models were used to analyze the signal quality and observe the trends among the volunteers to gauge the impact of the studied factors. The optimal signal was observed across individuals in the supine position, with the sensors positioned near the head and heart; bed angles between 30 degrees and 50 degrees, and mattress thicknesses between 5.5-8.5 cm. This study will aid in improving the signal-to-noise ratio of the BCG signals and perhaps identify the external factors influencing it, contributing to an improved non-intrusive patient monitoring experience.