Contactless biosensor measures stress signals in cars and airplanes

A team of scientists from the National University of Singapore has developed a biosensor that can wirelessly detect cardiopulmonary signals from people sitting in the cockpit of dynamic closed environments, such as a moving car or a flying airplane. The measurement of heartbeat and respiratory rate could be used to determine the driver's stress levels in order to prevent accidents.

The biosensor consists of conductive threads embroidered in a comb-shaped pattern on a seatbelt of a car, for example, as the researchers describe in the study "A digitally embroidered metamaterial biosensor for kinetic environments", which was published in Nature Electronics. The surface of the pattern can conduct radio waves and thus detect physiological movements through near-field interactions between wireless signals and the body.

The researchers have succeeded in extracting the heartbeat and breathing rate from these signals. Both can be used together to determine the stress level of a car driver or an airplane pilot, for example. This could be used to detect overload and prevent accidents.

Reliable signal detection

As the scientists found out in tests in a moving car and a flight simulator, the biosensor can reliably detect the information even when the driver or pilot is moving. Physiological signals can thus be recorded continuously.

The scientists point out that conventional sensors, which use body sounds as the basis for detecting heartbeat and breathing rate, for example, do not work reliably in such environments because the ambient noise is too loud, such as the humming of the engine. However, the biosensor developed by the researchers should provide cardiopulmonary signals at the same level and with the same reliability as a sensor that measures directly on the body.

"Our future research will focus on miniaturizing the sensor's wireless components and integrating them into compact modules for low-cost mass production," says Xi Tian, a co-author of the study. "We also want to develop algorithms that interpret physiological data to assess fatigue, stress and the driver's state of health. We plan to work with car manufacturers to refine and validate the system in practice."

(olb)