Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking (IPCAN), College of Information Science and Electronic Engineering (ISEE), Zhejiang University, Hangzhou 310027, China.
Sorbonne Universités, UR2, L2E, F-75005 Paris, France.
Sensors (Basel). 2018 Jul 12;18(7):2254. doi: 10.3390/s18072254.
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.
在这项研究中，应用了一种有界约束优化算法，通过检测人体呼吸和心跳引起的位移，利用 60GHz 多普勒雷达估计人体的生理数据（脉搏和呼吸频率）。在理论框架中分析了这两种运动之间相互调相的影响，并且证明了优化算法的应用能够准确地检测呼吸和心跳率，尽管它们之间存在互调效应。比较了不同的优化过程，并且表明与直接的频谱分析相比，它们对接收器噪声和随机身体运动的伪影更具有鲁棒性。在有大规模约束边界的情况下，提出了一种在子范围内执行的并行优化过程，以在缩短的时间跨度内实现准确检测。
