Contactless Real-Time Heartbeat Detection via 24 GHz Continuous-Wave Doppler Radar Using Artificial Neural Networks

Abstract

The measurement of human vital signs is a highly important task in a variety of environments and applications. Most notably, the electrocardiogram (ECG) is a versatile signal that could indicate various physical and psychological conditions, from signs of life to complex mental states. The measurement of the ECG relies on electrodes attached to the skin to acquire the electrical activity of the heart, which imposes certain limitations. Recently, due to the advancement of wireless technology, it has become possible to pick up heart activity in a contactless manner. Among the possible ways to wirelessly obtain information related to heart activity, methods based on mm-wave radars proved to be the most accurate in detecting the small mechanical oscillations of the human chest resulting from heartbeats. In this paper, we presented a method based on a continuous-wave Doppler radar coupled with an artificial neural network (ANN) to detect heartbeats as individual events. To keep the method computationally simple, the ANN took the raw radar signal as input, while the output was minimally processed, ensuring low latency operation (<1 s). The performance of the proposed method was evaluated with respect to an ECG reference (“ground truth”) in an experiment involving 21 healthy volunteers, who were sitting on a cushioned seat and were refrained from making excessive body movements. The results indicated that the presented approach is viable for the fast detection of individual heartbeats without heavy signal preprocessing.

An Inclusive Survey of Contactless Wireless Sensing: A Technology Used for Remotely Monitoring Vital Signs Has the Potential to Combating COVID-19

“…Authors claim that the device is able to accurately measure respiration even in a room of four people with the mean absolute respiration rate error of 0.73 bpm (breaths per minute). 11) Authors in [55] developed a continues real-time heartbeat monitoring device utilizing 24 GHz continuouswave Doppler radar as well as artificial neural networks (ANNs). The device was designed to have very low latency of less than one second.…”

Sensors, Signal and Image Processing in Biomedicine and Assisted Living

“…Another novel contactless heart rate measurement approach is presented in [ 2 ], where heart rate is detected with a continuous-wave Doppler radar and an artificial neural network (ANN). Its experimental evaluation on healthy volunteers indicates that this approach is viable for the fast detection of individual heartbeats without heavy signal preprocessing.…”

“…This special issue gathers a broad range of novel contributions on sensors, systems, and signal/image processing methods for biomedicine and assisted living. These include methods for heart, sleep and vital sign measurement [ 1 , 2 , 3 , 4 , 5 ]; human motion-related signal analysis in the context of rehabilitation and tremor assessment [ 6 , 7 , 8 ]; assistive systems for color deficient and visually challenged individuals, as well as for wheelchair control by people with motor disabilities [ 9 , 10 , 11 , 12 ]; and, image and video-based diagnostic systems [ 13 , 14 , 15 , 16 ].…”

Continuous In-Bed Monitoring of Vital Signs Using a Multi Radar Setup for Freely Moving Patients

“…In the process, different approaches and radar prototypes with different frequencies and modulations have been developed. For example, continuous-wave (CW) Doppler radars at [ 13 , 14 ], [ 15 ] and 24 [ 16 , 17 ] were built and used to measure respiration, heartbeat, or motion activity. Furthermore, frequency-modulated CW systems at 77 [ 18 , 19 ] and 122 [ 20 ] are used to measure vital parameters of several people simultaneously by separating the targets.…”