Circularly Polarized Ultra-Wideband Radar System for Vital Signs Monitoring

2013 ◽  
Vol 61 (5) ◽  
pp. 2069-2075 ◽  
Author(s):  
Kevin Khee-Meng Chan ◽  
Adrian Eng-Choon Tan ◽  
Karumudi Rambabu
Animals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 205 ◽  
Author(s):  
Pengfei Wang ◽  
Yangyang Ma ◽  
Fulai Liang ◽  
Yang Zhang ◽  
Xiao Yu ◽  
...  

As pets are considered members of the family, their health has received widespread attention. Since pets cannot talk and complain when they feel uncomfortable, monitoring vital signs becomes very helpful in disease detection, as well as observing their progression and response to treatment. In this study, we proposed an ultra-wideband radar-based, non-contact animal vital sign monitoring scheme that could monitor the breathing and heart rate of a pet in real-time. The primary advantage of the ultra-wideband radar was its ability to operate remotely without electrodes or wires and through any clothing or fur. Because of the existing noise and clutter in non-contact detection, background noise removal was applied. Furthermore, the respiration rate was directly obtained through spectrum analysis, while the heartbeat signal was extracted by the variational mode decomposition algorithm. By using electrocardiogram measurements, we verified the accuracy of the radar technology in detecting the anesthetized animals’ respiratory rate and heart rate. Besides, three beagles and five cats in a non-sedated state were measured by radar and contact pressure sensors simultaneously; the experimental results showed that radar could effectively measure the respiration of cats and dogs, and the accuracy rate was over 95%. Due to its excellent performance, the proposed method has the potential to become a new choice in application scenarios, such as pet sleep monitoring and health assessment.


2017 ◽  
Vol 27 (13) ◽  
pp. 1730046 ◽  
Author(s):  
Hang Xu ◽  
Ying Li ◽  
Jianguo Zhang ◽  
Hong Han ◽  
Bing Zhang ◽  
...  

We propose and experimentally demonstrate an ultra-wideband (UWB) chaos life-detection radar. The proposed radar transmits a wideband chaotic-pulse-position modulation (CPPM) signal modulated by a single-tone sinusoidal wave. A narrow-band split ring sensor is used to collect the reflected sinusoidal wave, and a lock-in amplifier is utilized to identify frequencies of respiration and heartbeat by detecting the phase change of the sinusoidal echo signal. Meanwhile, human location is realized by correlating the CPPM echo signal with its delayed duplicate and combining the synthetic aperture technology. Experimental results demonstrate that the human target can be located accurately and his vital signs can be detected in a large dynamic range through a 20-cm-thick wall using our radar system. The down-range resolution is 15[Formula: see text]cm, benefiting from the 1-GHz bandwidth of the CPPM signal. The dynamic range for human location is 50[Formula: see text]dB, and the dynamic ranges for heartbeat and respiration detection respectively are 20[Formula: see text]dB and 60[Formula: see text]dB in our radar system. In addition, the bandwidth of the CPPM signal can be adjusted from 620[Formula: see text]MHz to 1.56[Formula: see text]GHz to adapt to different requirements.


Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5503
Author(s):  
Xinyue Zhang ◽  
Xiuzhu Yang ◽  
Yi Ding ◽  
Yili Wang ◽  
Jialin Zhou ◽  
...  

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.


Author(s):  
Giovanni Diraco ◽  
Alessandro Leone ◽  
Pietro Siciliano

Continuous in-home monitoring of older adults living alone aims to improve their quality of life and independence, by detecting early signs of illness and functional decline or emergency conditions. To meet requirements for technology acceptance by seniors (unobtrusiveness, non-intrusiveness, privacy-preservation), this study presents and discusses a new smart sensor system for the detection of abnormalities during daily activities, based on ultra-wideband radar providing rich, not privacy-sensitive, information useful for sensing both cardiorespiratory and body movements, regardless of ambient lighting conditions and physical obstructions (through-wall sensing). The radar sensing is a very promising technology, enabling the measurement of vital signs and body movements at a distance, and thus meeting both requirements of unobtrusiveness and accuracy. In particular, impulse-radio ultra-wideband radar has attracted considerable attention in recent years thanks to many properties that make it useful for assisted living purposes. The proposed sensing system, evaluated in meaningful assisted living scenarios by involving 30 participants, exhibited the ability to detect vital signs, to discriminate among dangerous situations and activities of daily living, and to accommodate individual physical characteristics and habits. The reported results show that vital signs can be detected also while carrying out daily activities or after a fall event (post-fall phase), with accuracy varying according to the level of movements, reaching up to 95% and 91% in detecting respiration and heart rates, respectively. Similarly, good results were achieved in fall detection by using the micro-motion signature and unsupervised learning, with sensitivity and specificity greater than 97% and 90%, respectively.


IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 10300-10309 ◽  
Author(s):  
Jeong Woo Choi ◽  
Sung Sik Nam ◽  
Sung Ho Cho

Author(s):  
Alexander Kaineder ◽  
Oliver Lang ◽  
Reinhard Feger ◽  
Paul Dollhaubl ◽  
Andreas Stelzer ◽  
...  

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