Key result
A dual 60 GHz FMCW radar fusion system using a multi-bin technique estimated breathing rate with a maximum error of 1.9 breaths per minute and detected breath-hold periods with minimal false detections.
Why the study?
Existing vehicle health monitoring solutions are often inconvenient or risk leaking private information, whereas contactless radar systems can accurately and privately monitor driver breathing patterns to detect abnormalities.
A dual 60 GHz FMCW radar fusion system can accurately estimate driver breathing rates with a maximum error of 1.9 breaths per minute and detect breath-hold periods.
May improve road safety via early impairment detection; leaves open questions on practicality, validation, and privacy for adoption.
Monitoring the status of the driver is a crucial aspect of health monitoring inside vehicles as it helps to identify potential health or safety risks that could affect a driver's ability to operate a vehicle safely. This includes monitoring for fatigue, distraction, or impairment, among other things, which can potentially cause car crashes. Although many solutions for health monitoring in private vehicles have been proposed, the majority of them are inconvenient to use or have the risk of leaking private information. Radars have the potential to address the above drawbacks by their inherent privacy protection and contactless operation in addition to their high accuracy, convenience, affordable price, and resilience to environmental factors. Among many possible radar configurations, millimeter FMCW radars can accurately detect range and monitor displacements that are essential in breathing pattern monitoring. Breathing pattern monitoring is one of the key signatures of the driver’s health. An accurate estimation of the breathing pattern enables the detection of breathing abnormalities, including tachypnea, bradypnea, biot, cheyne–stokes, and apnea. The breathing pattern can be estimated from both the chest and abdomen. For this purpose, we employed two 60 GHz FMCW radars. The proposed algorithm is capable of detecting the mentioned breathing abnormalities through breathing rate (BR) estimation and breath-hold period detection. In addition, the proposed method in this paper estimates BR based on the multiple range bins. We conducted a study on the human radar geometry problem inside a vehicle to determine the accurate number of range bins for BR estimation. The experimental results demonstrate a maximum BR error of 1.9 breaths per minute using the proposed multi-bin technique. In addition, the dual radar fusion system can detect breath-hold periods with minimal false detections.
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Gharamohammadi et al. (2023) studied Driver monitoring for breathing abnormalities. Dual 60 GHz FMCW radar fusion system with multi-bin technique was evaluated on Breathing rate (BR) estimation error. A dual 60 GHz FMCW radar fusion system using a multi-bin technique estimated breathing rate with a maximum error of 1.9 breaths per minute and detected breath-hold periods with minimal false detections.
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