scholarly journals 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 561 ◽  
Author(s):  
Jae-Hyun Park ◽  
Yeo-Jin Jeong ◽  
Ga-Eun Lee ◽  
Jun-Taek Oh ◽  
Jong-Ryul Yang
Keyword(s):  
Heart Rate ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Path Loss ◽  
Low Noise ◽  
Radar Sensor ◽  
Continuous Wave Doppler ◽  
Front End ◽  
Front End Module

A miniaturized continuous-wave Doppler radar sensor operating at 915 MHz to remotely detect both respiration and heart rate (beats per minute) is presented. The proposed radar sensor comprises a front-end module including an implemented complementary metal-oxide semiconductor low-noise amplifier (LNA) and fractal-slot patch antennas, whose area was reduced by 15.2%. The two-stage inverter-based LNA was designed with an interstage capacitor and a feedback resistor to acquire ultrawide bandwidth. Two operating frequencies, 915 MHz and 2.45 GHz, were analyzed with regard to path loss for efficient operation because frequency affects detection sensitivity, reflected signal power from the human body, and measurement distance in a far-field condition. Path-loss calculation based on the simplified layer model indicates that the reflected power of the 915 MHz radar could be higher than that of the 2.45 GHz radar. The implemented radar front-end module excluding the LNA occupies 35 × 55 mm2. Vital signs were obtained via a fast Fourier transform and digital filtering using raw signals. In an experiment with six subjects, the respiration and heart rate obtained at 0.8 m using the proposed radar sensor exhibited mean accuracies of 99.4% and 97.6% with respect to commercialized reference sensors, respectively.

scholarly journals Correction: Park, J.-H. et al. 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs. Electronics 2019, 8, 561

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 855 ◽  
Author(s):  
Park ◽  
Jeong ◽  
Lee ◽  
Oh ◽  
Yang
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Radar Sensor ◽  
Continuous Wave Doppler ◽  
Published Paper

The authors wish to make the following corrections to the published paper [...]

Basic feasibility of breathing and pulse detection with a continuous wave Doppler radar sensor

Resuscitation ◽  
2015 ◽  
Vol 96 ◽  
pp. 53-54
Author(s):  
Jens Muehlsteff ◽  
Ralph Wijshoff ◽  
Marek Bartula ◽  
Marc Fuller ◽  
Dawn B. Jorgenson ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Radar Sensor ◽  
Pulse Detection ◽  
Continuous Wave Doppler

scholarly journals Peak Detection Algorithm for Vital Sign Detection Using Doppler Radar Sensors

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1575 ◽  
Author(s):  
Ju-Yeon Kim ◽  
Jae-Hyun Park ◽  
Se-Young Jang ◽  
Jong-Ryul Yang
Keyword(s):  
Heart Rate ◽  
Doppler Radar ◽  
Vital Signs ◽  
Accurate Method ◽  
Detection Algorithm ◽  
Peak Detection ◽  
Operating Characteristics ◽  
Radar Sensor ◽  
Peak Detection Algorithm ◽  
Hrv Analysis

An accurate method for detecting vital signs obtained from a Doppler radar sensor is proposed. A Doppler radar sensor can remotely obtain vital signs such as heartbeat and respiration rate, but the vital signs obtained by using the sensor do not show clear peaks like in electrocardiography (ECG) because of the operating characteristics of the radar. The proposed peak detection algorithm extracts the vital signs from the raw data. The algorithm shows the mean accuracy of 96.78% compared to the peak count from the reference ECG sensor and a processing time approximately two times faster than the gradient-based algorithm. To verify whether heart rate variability (HRV) analysis similar to that with an ECG sensor is possible for a radar sensor when applying the proposed method, the continuous parameter variations of the HRV in the time domain are analyzed using data processed with the proposed peak detection algorithm. Experimental results with six subjects show that the proposed method can obtain the heart rate with high accuracy but cannot obtain the information for an HRV analysis because the proposed method cannot overcome the characteristics of the radar sensor itself.

scholarly journals High-Accuracy Real-Time Monitoring of Heart Rate Variability Using 24 GHz Continuous-Wave Doppler Radar

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 74721-74733 ◽  
Author(s):  
Vladimir L. Petrovic ◽  
Milica M. Jankovic ◽  
Anita V. Lupsic ◽  
Veljko R. Mihajlovic ◽  
Jelena S. Popovic-Bozovic
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Real Time ◽  
Continuous Wave ◽  
Doppler Radar ◽  
High Accuracy ◽  
Real Time Monitoring ◽  
Continuous Wave Doppler ◽  
24 Ghz

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

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2351 ◽  
Author(s):  
Nebojša Malešević ◽  
Vladimir Petrović ◽  
Minja Belić ◽  
Christian Antfolk ◽  
Veljko Mihajlović ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Ground Truth ◽  
Mental States ◽  
Radar Signal ◽  
Heart Activity ◽  
Continuous Wave Doppler ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

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.

scholarly journals High Accuracy Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition and Matched Filter

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi
Keyword(s):  
Heart Rate ◽  
Singular Value Decomposition ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Matched Filter ◽  
Singular Value ◽  
Home Healthcare ◽  
Body Motion ◽  
Sitting Posture ◽  
Value Decomposition

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.

scholarly journals A 1.5–40 GHz frequency modulated continuous wave radar receiver front-end

2021 ◽  
pp. 1-11
Author(s):  
Mantas Sakalas ◽  
Niko Joram ◽  
Frank Ellinger
Keyword(s):  
Continuous Wave ◽  
Noise Figure ◽  
Supply Voltage ◽  
Low Noise ◽  
Ultra Wideband ◽  
Front End ◽  
Wave Radar ◽  
Bicmos Technology ◽  
Circuit Components ◽  
High Band

Abstract This study presents an ultra-wideband receiver front-end, designed for a reconfigurable frequency modulated continuous wave radar in a 130 nm SiGe BiCMOS technology. A variety of innovative circuit components and design techniques were employed to achieve the ultra-wide bandwidth, low noise figure (NF), good linearity, and circuit ruggedness to high input power levels. The designed front-end is capable of achieving 1.5–40 GHz bandwidth, 30 dB conversion gain, a double sideband NF of 6–10.7 dB, input return loss better than 7.5 dB and an input referred 1 dB compression point of −23 dBm. The front-end withstands continuous wave power levels of at least 25 and 20 dBm at low band and high band inputs respectively. At 3 V supply voltage, the DC power consumption amounts to 302 mW when the low band is active and 352 mW for the high band case, whereas the total IC size is $3.08\, {\rm nm{^2}}$ .

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