College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China.
Sensors (Basel). 2022 Oct 9;22(19):7646. doi: 10.3390/s22197646.
Continuous-wave doppler radar, which has the advantages of simple structure, low cost, and low power consumption, has attracted extensive attention in the detection of human vital signs. However, while respiration and heartbeat signals are mixed in the echo phase, the amplitude difference between the two signals is so large that it becomes difficult to measure the heartrate (HR) from the interference of respiration stably and accurately. In this paper, the difference quadratic sum demodulation method is proposed. According to the mixed characteristics of respiration and heartbeat after demodulation, the heartbeat features can be extracted with the help of the easy-to-detect breathing signal; combined with the constrained nearest neighbor search algorithm, it can realize sleeping HR monitoring overnight without body movements restraint. Considering the differences in vital-sign characteristics of different individuals and the irregularity of sleep movements, 54 h of sleep data for nine nights were collected from three subjects, and then compared with ECG-based HR reference equipment. After excluding the periods of body turning over, the HR error was within 10% for more than 70% of the time. Experiments confirmed that this method, as a tool for long-term HR monitoring, can play an important role in sleeping monitoring, smart elderly care, and smart homes.
连续波多普勒雷达具有结构简单、成本低、功耗低等优点，在人体生命体征检测中受到广泛关注。然而，在回波相位中，呼吸和心跳信号混合在一起，由于两个信号的幅度差异很大，因此很难从干扰中稳定、准确地测量心率 (HR)。本文提出了差二次和解调方法。根据解调后呼吸和心跳的混合特征，借助易于检测的呼吸信号提取心跳特征；结合约束最近邻搜索算法，可以实现夜间无身体运动限制的睡眠 HR 监测。考虑到不同个体生命体征特征的差异和睡眠运动的不规则性，从三个受试者中收集了 9 个晚上共 54 小时的睡眠数据，并与基于心电图的 HR 参考设备进行了比较。在排除翻身期后，HR 误差在 10%以内的时间超过 70%。实验证实，该方法作为长期 HR 监测工具，在睡眠监测、智能老年护理和智能家居中可以发挥重要作用。
