Non-Contact Heart-Rate Measurement Method Using Both Transmitted Wave Extraction and Wavelet Transform

Abstract

Continuous monitoring of heart-rate is expected to lead to early detection of physical discomfort. In this study, we propose a non-contact heart-rate measurement method which can be used in an environment such as driver heart-rate monitoring with body movement. The method is based on the electric field strength transmitted through the human body that changes with the diastole and systole of the heart. Unlike conventional displacement detection of the skin surface, we attempted to capture changes in the internal structure of the human body by irradiating the human body with microwaves and acquiring microwaves that pass through the heart. We first estimated the electric field strength transmitted through the heart using three receiving sensors to reduce the body movement effect. Then we decomposed the estimated transmitted electric field using stationary wavelet transform to eliminate significant distortion due to body movement. As a result, we achieved an estimation accuracy of heart-rate as high as 98% in a verification experiment with normal body movement.

Method for the Statistical Analysis of the Signals Generated by an Acquisition Card for Pulse Measurement

“…Their effectiveness in vehicle environments remains unclear. 2021/ [9] Non-contact, automated cardiac pulse measurements using video imaging and blind source separation.…”

“…Market research forecasts growth of heavy future investment in terms of industrial research, to improve the sensors in terms of flexibility, motion, and smart textiles. Within the state of the art, there is a large number of devices whose purpose is the use of signals [7][8][9][10][11]. In addition to health devices, other devices based on the use of signals are being integrated into critical applications, to name a few: remote patient monitoring, space exploration, industry, detection, control, and monitoring systems.…”

Innovative non-contact r-r intervals estimation using viterbi algorithm with Squared Branch Metric (VSBM)

“…In an attempt to address these challenges, the authors proposed a wavelet-transform-based peak detection method (Li & Lin, 2018) for rapid heart rate detection using a 5.8 GHz Continuous Wave (CW) Doppler radar with 3-5 s data lengths. This method distinguishes respiratory harmonics from the heartbeat signal by examining the peak properties of the combined wavelet frequency spectrum (Yang et al, 2021). However, the limited 3-5 s data length may lead to incorrect peak detection.…”