scholarly journals Software-Defined Doppler Radar Sensor for Human Breathing Detection

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3085 ◽  
Author(s):  
Sandra Costanzo
Keyword(s):  
Software Defined Radio ◽  
Doppler Radar ◽  
Low Cost ◽  
Vital Signs ◽  
Phase Correlation ◽  
Wireless Sensing ◽  
Radar Sensor ◽  
Human Respiration ◽  
Critical Issues ◽  
Radio Transceiver

Non-contact wireless sensing approaches have emerged in recent years, in order to enable novel enhanced developments in the framework of healthcare and biomedical scenarios. One of these technologically advanced solutions is given by software-defined radar platforms, a low-cost radar implementation, where all operations are implemented and easily changed via software. In the present paper, a software-defined radar implementation with Doppler elaboration features is presented, to be applied for the non-contact monitoring of human respiration signals. A quadrature receiver I/Q (In-phase/Quadrature) architecture is adopted in order to overcome the critical issues related to the occurrences of null detection points, while the phase-locked loop components included in the software defined radio transceiver are successfully exploited to guarantee the phase correlation between I/Q signal components. The proposed approach leads to a compact, low-cost, and flexible radar solution, whose application abilities may be simply changed via software, with no need for hardware modifications. Experimental results on a human target are discussed so as to demonstrate the feasibility of the proposed approach for vital signs detection.

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 [...]

Noncontact Measurement of River Surface Velocity and Discharge Estimation With a Low-Cost Doppler Radar Sensor

2020 ◽  
Vol 58 (7) ◽  
pp. 5195-5207 ◽  
Author(s):  
Federico Alimenti ◽  
Stefania Bonafoni ◽  
Elisa Gallo ◽  
Valentina Palazzi ◽  
Roberto Vincenti Gatti ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Low Cost ◽  
Surface Velocity ◽  
Radar Sensor ◽  
Noncontact Measurement ◽  
Discharge Estimation

scholarly journals Non-Contact Measurement of Human Respiration and Heartbeat Using W-band Doppler Radar Sensor

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5209 ◽  
Author(s):  
Heesoo Kim ◽  
Jinho Jeong
Keyword(s):  
Doppler Radar ◽  
Band Pass Filter ◽  
Radar Sensor ◽  
Pass Filter ◽  
Contact Measurement ◽  
W Band ◽  
Compact Size ◽  
Human Respiration ◽  
Low Pass ◽  
Respiration Signal

This paper presents a W-band continuous-wave (CW) Doppler radar sensor for non-contact measurement of human respiration and heartbeat. The very short wavelength of the W-band signal allows a high-precision detection of the displacement of the chest surface by the heartbeat as well as respiration. The CW signal at 94 GHz is transmitted through a high-gain horn antenna to the human chest at a distance of 1 m. The phase-modulated reflection signal is down-converted to the baseband by the quadrature mixer with an excellent amplitude and phase matches between I and Q channels, which makes the IQ mismatch correction in the digital domain unnecessary. The baseband I and Q data are digitized using data acquisition (DAQ) board. The arctangent demodulation with automatic phase unwrapping is applied to the low-pass filtered I and Q data to effectively solve the null point problem. A slow-varying DC component is rejected in the demodulated signal by the trend removal algorithm. Then, the respiration signal with a frequency of 0.27 Hz and a displacement of ~6.1 mm is retrieved by applying a low-pass filter. Finally, the respiration signal is removed by the band-pass filter and the heartbeat signal is extracted, showing a frequency of 1.35 Hz and a displacement of ~0.26 mm. The extracted respiration and heartbeat rates are very close to the manual measurement results. The demonstrated W-band CW radar sensors can be easily applied to find the angular location of the human body by using a phased array under a compact size.

scholarly journals Evaluation of a Doppler radar sensor system for vital signs detection and activity monitoring in a radio-frequency shielded room

Measurement ◽  
2015 ◽  
Vol 68 ◽  
pp. 135-142 ◽  
Author(s):  
Jussi Kuutti ◽  
Mikko Paukkunen ◽  
Miro Aalto ◽  
Pekka Eskelinen ◽  
Raimo E. Sepponen
Keyword(s):  
Radio Frequency ◽  
Doppler Radar ◽  
Vital Signs ◽  
Activity Monitoring ◽  
Sensor System ◽  
Radar Sensor

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 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.

Sign in / Sign up

Export Citation Format

Share Document