Vital-sign estimation using ultra-wideband (UWB) radar is preferable because it is contactless and less privacy-invasive. Recently, many approaches have been proposed for estimating heart rate from UWB radar data. However, their performance is still not reliable enough for practical applications. To improve the accuracy, this study employs convolutional neural networks to learn the special patterns of the heartbeats. In the proposed system, skin displacements of the target person are measured using UWB radar, and the radar signal is converted to a two-dimensional matrix, which is used as the input of the designed neural networks. Meanwhile, two triangular waves corresponding to the peaks and valleys in an electrocardiogram are adopted as the output of the networks. The proposed system then identifies each individual and estimates the heart rate automatically based on the already trained neural networks. The estimation error of the interbeat interval computed using our approach was reduced to 4.5 ms in the best case; and 48.5 ms in the worst case. Experiment results show that the proposed approach significantly outperforms a conventional method. The proposed machine learning approach achieves both personal identification and heart rate estimation simultaneously using UWB radar data for the first time. Moreover, this study found that using the respiration and heartbeat components together may enhance the accuracy of heart rate estimation, which is counter-intuitive, because the respiration is usually believed to interfere with the heartbeat. INDEX TERMS Ultra-wideband radar, heart rate, vital signs, convolutional neural networks.

No abstract

No abstract

The feasibility of measuring heart rate using radar echoes from a human head is demonstrated. Non‐contact measurement of vital signs using radar has been attracting much attention because such technologies can breakthrough benefits for monitoring health conditions without electrodes or wearable devices. Most existing studies have measured echoes from the torso, particularly the chest wall. However, this is difficult because of multiple interfering reflections from the complex shape of the torso and other body parts, such as limbs. The current study is the first demonstration that non‐contact heart rate measurement can be easily achieved using echoes from the human head. There are two important advantages of measurement from the human head: (i) the simple shape of the head makes an ideal radar target with only a single reflection, and (ii) the other undesired echoes can be removed using time‐gating when an ultra‐wideband radar is used. Nonetheless, because the displacement of the human head due to heart rate is small, a millimetre‐wave ultra‐wideband array radar system is developed, which is installed on the ceiling and used in the proposed measurements with participants.

FI G. I. Map of Alaska showing key locations. (Map background courtesy of Google Earth.) (a) State of Alaska and (b) the Cook Inlet region.

No abstract

No abstract

No abstract