Pulse wave extraction for non-contact heart rate measurement based on polarization multispectral imaging
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摘要: 目的 成像式光电容积描记(IPPG)技术是一种非接触式生理参数检测技术，目前已经广泛用于常用生理参数的测量中，但准确性和稳定性不够。本研究的目的是通过探索一种新的从手掌中提取脉搏的方法，从而提高测量数据的精度。方法 本研究利用偏振多光谱成像技术，研究了脉搏波在不同波长和偏振态组合下的信噪比(SNR)变化。使用白光LED作为主动光源，并用7种波长滤光片(450、525、550、590、610、650、690nm)和4种偏光片实现生物组织的偏光多光谱成像。使用商用RGB相机作为获取人手掌偏振多光谱图像的探测器，然后结合成像光电体积描记技术，从偏振多光谱图像中提取脉搏波。结果 本研究利用普通商用RGB相机实现了高质量脉搏波的提取，提出了一种全局平均帧间差分算法(GA-IFD)，将此方法结合运动跟踪算法来实现目标区域(ROI)的自适应选择，使组织的血液灌注与ROI的选择相关联。该算法能有效避免噪声干扰，提高脉搏波质量。本研究方法以非接触方式估计了5名志愿者的心率，达到较高的测量精度(最小MAE 0.67，最大MAE 2.30)。根据Bland-Altman一致性分析，该方法的心率测量值与真实值吻合度高。结论 本研究创新性提出了一种从手掌中提取心脏脉搏波的非接触方法，这对提高人体非接触式生理参数测量精度具有重要意义。Abstract: Objective Imaging Photoplethysmography(IPPG) technology is a non-contact physiological parameter detection technology, which has been widely used in the measurement of common physiological parameters, but the accuracy and stability Sex is not enough. The purpose of this study was to improve the accuracy of the measurement data by exploring a new method for pulse extraction from the palm.Methods In this study, the signal-to-noise ratio(SNR) changes of pulse waves under different combinations of wavelengths and polarization states were studied by using polarization multispectral imaging technology. Polarized multispectral imaging of biological tissues was achieved using a white LED as the active light source and seven wavelength filters(450, 525, 550, 590, 610, 650, 690nm) and four polarizers. A commercial RGB camera was used as a detector to acquire polarized multispectral images of the human palm, and then combined with imaging photoplethysmography, pulse waves were extracted from the polarized multispectral images.Results In this study, a common commercial RGB camera was used to achieve high-quality pulse wave extraction, and to solve the problem of hand micro-motion caused by breathing, which led to the baseline shift of pulse waves, and a global average inter-frame difference algorithm(GA-IFD) was proposed. This method is combined with motion tracking algorithm to realize the adaptive selection of region of interest(ROI), so that the blood perfusion of the tissue is associated with the selection of ROI. The algorithm can effectively avoid noise interference and improve pulse wave quality. The present study method estimated the heart rate of five volunteers in a non-contact manner, achieving high measurement accuracy(minimum MAE 0.67, maximum MAE 2.30). According to the Bland-Altman agreement analysis, the heart rate measurement value of this method is in good agreement with the true value.Conclusion Based on the above innovative methods, this study innovatively proposes a non-contact method to extract cardiac pulse waves from the palm of the hand, which is of great significance for improving the measurement accuracy of non-contact physiological parameters of the human body.
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表 1 心率估计结果
bpm Subject ID MAE RMSE SD 1 0.67 0.96 0.69 2 1.61 2.11 1.37 3 0.84 1.08 0.68 4 0.98 1.46 1.08 5 2.30 2.55 1.55 
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