BERT: Accelerating Vital Signs Measurement for Bioradar with An Efficient Recursive Technique

TL;DR

This paper introduces BERT, an efficient recursive technique leveraging Markov model properties to accelerate vital signs measurement in bioradar systems while maintaining accuracy, addressing a key bottleneck in healthcare monitoring.

Contribution

The paper proposes a novel recursive method, BERT, that significantly reduces measurement time in bioradar vital signs sensing without sacrificing accuracy.

Findings

Lower time costs in VS measurement

Competitive accuracy in heart and breathing rate estimation

Potential for improved real-time healthcare monitoring

Abstract

Recent years have witnessed the great advance of bioradar system in smart sensing of vital signs (VS) for human healthcare monitoring. As an important part of VS sensing process, VS measurement aims to capture the chest wall micromotion induced by the human respiratory and cardiac activities. Unfortunately, the existing VS measurement methods using bioradar have encountered bottlenecks in making a trade-off between time cost and measurement accuracy. To break this bottleneck, this letter proposes an efficient recursive technique (BERT) heuristically, based on the observation that the features of bioradar VS meet the conditions of Markov model. Extensive experimental results validate that BERT measurement yields lower time costs, competitive estimates of heart rate, breathing rate, and heart rate variability. Our BERT method is promising us a new and superior option to measure VS for bioradar. This work seeks not only to solve the current issue of how to accelerate VS measurement with an acceptable accuracy, but also to inspire creative new ideas that spur further advances in this promising field in the future.