Tsai Yu-Chiao, Lai Shih-Hsuan, Ho Ching-Ju, Wu Fang-Ming, Henrickson Lindor, Wei Chia-Chien, Chen Irwin, Wu Vincent, Chen Jyehong
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:232-235. doi: 10.1109/EMBC44109.2020.9175161.
A 24GHz Doppler radar system for accurate contactless monitoring of heart and respiratory rates is demonstrated here. High accuracy predictions are achieved by employing a CNN+LSTM neural network architecture for regression analysis. Detection accuracies of 99% and 98% have been attained for heart rate and respiration rate, respectively.Clinical Relevance- This work establishes a non-contact radar system with 99% detection accuracy for a heart rate variability warning system. This system can enable convenient and fast monitoring for daily care at home.
本文展示了一种用于精确非接触式监测心率和呼吸频率的24GHz多普勒雷达系统。通过采用CNN+LSTM神经网络架构进行回归分析，实现了高精度预测。心率和呼吸频率的检测准确率分别达到了99%和98%。临床意义——这项工作建立了一个用于心率变异性预警系统的检测准确率为99%的非接触式雷达系统。该系统可为家庭日常护理提供便捷快速的监测。
