Real-Time Contactless Respiration Monitoring From a Radar Sensor Using Image Processing Method

The respiratory rate (RR) and waveform play an important role in reflecting health conditions. Some diseases such as Biot’s breathing and Chyne–Stokes respiration require long-term continuous respiration monitoring, which is normally conducted by hospitals or sleep centers. Portable sensor devices, such as piezoelectric sensors, watch-type monitoring devices, ultrasound technologies, radar sensors, and so on, are required to help patients that are difficult to attend to such settings. In terms of these choices, the radar sensor can provide a more comfortable and contactless experience. Most of the existing methods analyze the 1-D radar signal. The 2-D radar signal, such as the radar image, contains more spatial information that is easier to be interfaced with further pose or gesture recognition functions to extract useful information. This article presents an image processing approach with radar images generated from an ultrawideband (UWB) radar sensor to produce respiration waveforms and estimate RR in real-time. The raw signals from the radar sensor are converted to a 2-D heatmap image, and then an image-processing algorithm is employed to extract respiration information including the respiration waveform from the heatmap. Experimental results show that the proposed system can reliably measure respiration motion in static situations such as lying in the supine or lateral position with an average precision of 95.02%.