We present for the first time a novel method that utilizes the chest movement-modulated radio signals for non-contact acquisition of the photoplethysmography (PPG) signal. Under the proposed method, a software-defined radio (SDR) exposes the chest of a subject sitting nearby to an orthogonal frequency division multiplexing signal with 64 sub-carriers at a center frequency 5.24 GHz, while another SDR in the close vicinity collects the modulated radio signal reflected off the chest. This way, we construct a custom dataset by collecting 160 minutes of labeled data (both raw radio data as well as the reference PPG signal) from 16 healthy young subjects. With this, we first utilize principal component analysis for dimensionality reduction of the radio data. Next, we denoise the radio signal and reference PPG signal using wavelet technique, followed by segmentation and Z-score normalization. We then synchronize the radio and PPG segments using cross-correlation method. Finally, we proceed to the waveform translation (regression) task, whereby we first convert the radio and PPG segments into frequency domain using discrete cosine transform (DCT), and then learn the non-linear regression between them. Eventually, we reconstruct the synthetic PPG signal by taking inverse DCT of the output of regression block, with a mean absolute error of 8.1294. The synthetic PPG waveform has a great clinical significance as it could be used for non-contact performance assessment of cardiovascular and respiratory systems of patients suffering from infectious diseases, e.g., covid19.

翻译：本文首次提出一种利用胸部运动调制无线电信号实现非接触式光电容积描记（PPG）信号获取的新方法。在所提方法中，软件定义无线电（SDR）向附近受试者的胸部发射中心频率为5.24 GHz、具有64个子载波的正交频分复用信号，同时另一台邻近的SDR采集胸部反射的调制无线电信号。我们通过采集16名健康年轻受试者共160分钟的标注数据（包括原始无线电数据及参考PPG信号）构建了自定义数据集。首先采用主成分分析对无线电数据进行降维处理，随后利用小波技术对无线电信号和参考PPG信号进行去噪，并完成分段和Z-score归一化。接着通过互相关方法实现无线电段与PPG段的同步，最终进行波形转换（回归）任务：先利用离散余弦变换（DCT）将无线电段和PPG段转换至频域，再学习二者间的非线性回归关系。通过逆DCT重构回归模块输出得到合成PPG信号，平均绝对误差为8.1294。该合成PPG波形具有重要临床意义，可用于传染病患者（如COVID-19）心血管与呼吸系统的非接触式功能评估。