A Novel Approach for Heartbeat Rate Estimation Using 3-D Lidar and Multibeam MIMO Doppler Radar

• Published in: IEEE sensors journal Vol. 23; no. 24; pp. 31259 - 31277
• Main Authors: Bouazizi, Mondher, Yamamoto, Kohei, Endo, Koji, Ohtsuki, Tomoaki
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.12.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3-D light detection and ranging (Lidar); Chest; deep learning (DL); depth image; Doppler radar; Estimation; Heart beat; Heart rate; heart rate (HR) estimation; Laser radar; Lidar; MIMO communication; Monitoring; pose detection; Radar detection; Sensors
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3330472

Noncontact heartbeat detection and heart rate (HR) estimation have been hot topics of research over the last few years. By employing wireless sensors, such as Doppler sensors, the goal of these tasks is to detect subtle movements associated with heart movements. The detection is either used to reconstruct the R-peaks, thus the heartbeat detection, or simply identify the HR. However, due to the nature of the faint movements of the chest caused by the heart beats, unless the person is still, such movements are overwhelmingly obscured by the motion of the person. That being the case, we are interested in this work in identifying such instances where the person is not in motion, in which case, we measure their heartbeats and HR. To do so, we use a combination of a 3-D light detection and ranging (LiDAR) and a multiple-input multiple-output (MIMO) Doppler Radar. The former's objective is to recognize when the person is still, in which case their position and distance from the sensors are reported. The latter's objective is to create a beam directed toward the person's detected chest and measure the reflected signal, for heartbeat detection, HR, or respiration rate (RR) estimation. Our experiments demonstrate that determining the subject's location and distance and identifying their chest position using LiDAR, then collecting the data accordingly using the Doppler radar leads to better HR detection and R-R intervals (RRIs) estimation. For five different scenarios, the RRI estimation error reaches values between 112 and 231 ms.