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Achieving contactless heart rate measurement by the combination of genetic algorithm and UWB radar technology

Most of the heart rate measurement devices are required to be contacted to skins. These devices often degrade the quality of sleeping, or cause the damages of more delicate skins (like that of the baby’s or the elder’s) for long term usage. Ultra-wideband radars can measure heart rate in a far distance, and they can be placed on the beds. However, one might feel uneasy to move in beds with sensors. An alternative way is to insert the sensor into the mattress, but in this way the sensor signals would be disturbed by various noises so it is hard to design the filter. In this work, we design a mechanism to extract heart rates from the sensor signals, and develop a genetic-based approach to derive the best parameters to filter out the noises. Experiments have been conducted to evaluate the performance. The results show that our approach outperforms the baselines of two machine learning models.