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A spectrum estimation approach for accurate heartbeat detection using Doppler radar based on combination of FTPR and TWV
EURASIP Journal on Advances in Signal Processing ( IF 1.7 ) Pub Date : 2022-07-26 , DOI: 10.1186/s13634-022-00899-8
Haipeng Pan , Yongyang Zou , Minming Gu

Non-contact heartbeat detection using Doppler radar is extremely valuable for remotely monitoring and medical diagnosis on special occasions. Nevertheless, fast and accurate heart rate (HR) detection endures several challenges due to influential respiration interference and insufficient frequency spectrum resolution. In this paper, a novel heartbeat detection method with a compact Doppler radar is employed to accurately estimate some indicators of HR and heart rate variability. Firstly, a multiresolution analysis approach based on maximal overlap discrete wavelet transform is introduced to accomplish the preliminary separation of respiration and heartbeat. Subsequently, a template matched filter algorithm is further implemented to maximize the enhancement of the concealed heartbeat component and retrieve the heartbeat signal. Eventually, a novel spectrum estimation method combining frequency–time phase regression with time-window-variation technology is proposed to evaluate the real-time HR. It solves serious dominant frequency estimation deviation and insufficient frequency spectrum resolution in short-period time windows. The accuracy and timeliness of our proposed method are validated by 6 sets of experimental data sampled at the actual office. As a result, the HR detection accuracy is up to 99.70% in different-period time windows of 10 s and 92.09% in 3s. In addition, the mean relative error of extracted beat-to-beat intervals in 3 s ranges from 0.76 to 1.02%.



中文翻译:

一种基于FTPR和TWV结合的多普勒雷达准确检测心跳的频谱估计方法

使用多普勒雷达进行非接触式心跳检测对于特殊场合的远程监测和医疗诊断极具价值。然而,由于有影响的呼吸干扰和频谱分辨率不足,快速准确的心率 (HR) 检测遇到了一些挑战。在本文中,采用紧凑型多普勒雷达的新型心跳检测方法来准确估计 HR 和心率变异性的一些指标。首先,引入了一种基于最大重叠离散小波变换的多分辨率分析方法,实现了呼吸与心跳的初步分离。随后,进一步实现模板匹配滤波算法,以最大限度地增强隐藏的心跳分量并检索心跳信号。最终,提出了一种将频率-时间相位回归与时间-窗口变化技术相结合的新型频谱估计方法来评估实时HR。解决了短周期窗口中主频估计偏差严重和频谱分辨率不足的问题。通过在实际办公室采样的 6 组实验数据验证了我们提出的方法的准确性和及时性。结果,HR检测精度在10 s和3 s的不同时间窗口内分别达到99.70%和92.09%。此外,在 3 秒内提取的逐搏间隔的平均相对误差范围为 0.76% 至 1.02%。解决了短周期窗口中主频估计偏差严重和频谱分辨率不足的问题。通过在实际办公室采样的 6 组实验数据验证了我们提出的方法的准确性和及时性。结果,HR检测精度在10 s和3 s的不同时间窗口内分别达到99.70%和92.09%。此外,在 3 秒内提取的逐搏间隔的平均相对误差范围为 0.76% 至 1.02%。解决了短周期窗口中主频估计偏差严重和频谱分辨率不足的问题。通过在实际办公室采样的 6 组实验数据验证了我们提出的方法的准确性和及时性。结果,HR检测精度在10 s和3 s的不同时间窗口内分别达到99.70%和92.09%。此外,在 3 秒内提取的逐搏间隔的平均相对误差范围为 0.76% 至 1.02%。

更新日期:2022-07-27
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