Abstract
In this study, a bound-constrained optimization algorithm is applied for estimating physiological data (pulse and breathing rate) of human body using 60 GHz Doppler radar, by detecting displacements induced by breathing and the heartbeat of a human subject. The influence of mutual phasing between the two movements is analyzed in a theoretical framework and the application of optimization algorithms is proved to be able to accurately detect both breathing and heartbeat rates, despite intermodulation effects between them. Different optimization procedures are compared and shown to be more robust to receiver noise and artifacts of random body motion than a direct spectrum analysis. In case of a large-scale constrained bound, a parallel optimization procedure executed in subranges is proposed to realize accurate detection in a reduced span of time.
Highlights
Patient telemonitoring is a good solution to help manage medical environments such as nursing homes and hospitals in daily tasks as well as patient managing, health monitoring, abnormality- and distress-situation detection [1], and activities of daily living recognition [2]
We investigate the estimation of human vital signs using signals received from an in-phase quadrature (IQ) demodulator-based 60 GHz Doppler radar
cumulative distribution function (CDF) obtained from the three optimization algorithms (GA, particle swarm optimization (PSO), least-square minimization (LSM)) in the time and frequency domains are plotted in Figure 4a,b respectively
Summary
Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), College of Information Science and Electronic Engineering (ISEE), Zhejiang University, Hangzhou 310027, China.
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