T-HSER: Transformer Network Enabling Heart Sound Envelope Signal Reconstruction Based on Low Sampling Rate Millimeter Wave Radar

The four stages (first heart sound (S1), systole, second heart sound (S2), and diastole) of heartbeat sounds recorded by contact seismocardiogram (SCG) reflect the health of the heart, but these stages are challenging to measure by noncontact millimeter wave radar. If the sampling rate of millimeter wave radar is increased, this will increase the amount of data storage needed for the long-term monitoring of human vital signs. This article presents an algorithm for reconstructing the envelope of high-frequency heart sound signals using low-frequency millimeter wave radar signals, as well as a heart sound envelope segmentation algorithm based on peak points. Its design principle is a combination of signal processing and a transformer network, which is called T-HSER. This technique maps the low-frequency radar signal into a high-frequency heart sound envelope signal through the transformer network and determines the four different stages of the heart sound using appropriate thresholds. Based on the training of more than 30000 heartbeats of 25 healthy subjects and the prediction evaluation of six subjects, the T-HSER algorithm is shown to reconstruct the high-frequency heart sound envelope signal with high correlation. Moreover, the mean correlation can reach 0.85 on one minute of data, which is higher than that of the bidirectional long short-term memory algorithm, and can effectively distinguish the four stages of the heart sound so that the mean absolute error (MAE) between the predicted value and the ground truth of S1 and S2 is within a tolerable range (70 ms). At the same time, the algorithm is suitable for low sampling rate radar, which greatly reduces the amount of data storage required.