李牧, 吴彤, 田哲嘉. 基于热成像技术的非接触式生命体征测量方法[J]. 红外技术, 2022, 44(4): 428-436.
引用本文: 李牧, 吴彤, 田哲嘉. 基于热成像技术的非接触式生命体征测量方法[J]. 红外技术, 2022, 44(4): 428-436.
LI Mu, WU Tong, TIAN Zhejia. Non-contact Vital Signs Measurement by Thermal Imaging Technology[J]. Infrared Technology , 2022, 44(4): 428-436.
Citation: LI Mu, WU Tong, TIAN Zhejia. Non-contact Vital Signs Measurement by Thermal Imaging Technology[J]. Infrared Technology , 2022, 44(4): 428-436.

基于热成像技术的非接触式生命体征测量方法

Non-contact Vital Signs Measurement by Thermal Imaging Technology

  • 摘要: 针对目前临床上监测生命体征设备的不便携带、接触人体等问题实现了一种将红外热成像仪作为信息采集设备,通过分析人体面部血管模型及鼻孔位置温差变化得到心率值和呼吸信息的方法。首先对获取的热像图序列提取前景目标以缩短在整幅图像中进行人脸检测的时间,再利用各向异性扩散滤波法增强感兴趣区域内血管位置的对比度,并利用形态学处理获得人脸血管部位的灰度均值形成初始心率信号。最终通过趋势消除、小波阈值去噪方法去除时间序列中的趋势项和随机噪声获取最终的心率波形图和动态心率、呼吸值。与医院专用设备对比试验得出该方法可控制心率误差小于4%,平均的均值误差为 \left| \bar d \right| =0.718次/min。呼吸误差在1次/min内,具有较高的准确性和鲁棒性,能够满足实际需求。

     

    Abstract: To solve the problems of inconvenient carrying and contact with the human body when using current clinical vital signs monitoring equipment, a method of estimating heart rate and respiratory information is proposed by analyzing the facial vascular model and temperature difference of the nostril position using an infrared thermal imager as a transmission device. First, the foreground target is extracted from the obtained thermal image sequence to shorten the time of face detection in the entire image. Anisotropic diffusion is then used to enhance the contrast of the vascular position in the region of interest, and the gray mean of the vascular position in the face is obtained by morphological processing to form the initial heart rate signal. Finally, trend elimination, wavelet threshold denoising, and other filtering methods were used to remove the trend item and random noise in the time series to obtain the final heart rate waveform, dynamic heart, and respiration values. Compared with specialized equipment in the hospital, it was found that the method exhibited a heart rate error of less than 4%, and the average error of the average value was 0.718 beats/min. The breathing error is within 1 beat/min, showing high accuracy and robustness and that the method can meet actual needs.

     

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