scholarly journals Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5503
Author(s):  
Xinyue Zhang ◽  
Xiuzhu Yang ◽  
Yi Ding ◽  
Yili Wang ◽  
Jialin Zhou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vital Signs ◽  
Motion Artifacts ◽  
Body Motion ◽  
Ultra Wideband ◽  
Body Movements ◽  
Range Resolution ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
Empirical Wavelet Transform

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.

scholarly journals Adaptive Separation of Respiratory and Heartbeat Signals among Multiple People Based on Empirical Wavelet Transform Using UWB Radar

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4913 ◽  
Author(s):  
Mi He ◽  
Yongjian Nian ◽  
Luping Xu ◽  
Lihong Qiao ◽  
Wenwu Wang
Keyword(s):  
Wavelet Transform ◽  
Continuous Wave ◽  
Body Movement ◽  
Vital Signs ◽  
Initial Boundary ◽  
Tight Frame ◽  
Ultra Wideband ◽  
Clinical Monitoring ◽  
Uwb Radar ◽  
Empirical Wavelet Transform

The non-contact monitoring of vital signs by radar has great prospects in clinical monitoring. However, the accuracy of separated respiratory and heartbeat signals has not satisfied the clinical limits of agreement. This paper presents a study for automated separation of respiratory and heartbeat signals based on empirical wavelet transform (EWT) for multiple people. The initial boundary of the EWT was set according to the limited prior information of vital signs. Using the initial boundary, empirical wavelets with a tight frame were constructed to adaptively separate the respiratory signal, the heartbeat signal and interference due to unconscious body movement. To verify the validity of the proposed method, the vital signs of three volunteers were simultaneously measured by a stepped-frequency continuous wave ultra-wideband (UWB) radar and contact physiological sensors. Compared with the vital signs from contact sensors, the proposed method can separate the respiratory and heartbeat signals among multiple people and obtain the precise rate that satisfies clinical monitoring requirements using a UWB radar. The detection errors of respiratory and heartbeat rates by the proposed method were within ±0.3 bpm and ±2 bpm, respectively, which are much smaller than those obtained by the bandpass filtering, empirical mode decomposition (EMD) and wavelet transform (WT) methods. The proposed method is unsupervised and does not require reference signals. Moreover, the proposed method can obtain accurate respiratory and heartbeat signal rates even when the persons unconsciously move their bodies.

scholarly journals A robust multi-feature based method for distinguishing between humans and pets to ensure signal source in vital signs monitoring using UWB radar

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yangyang Ma ◽  
Pengfei Wang ◽  
Wenzhe Huang ◽  
Fugui Qi ◽  
Fulai Liang ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Recursive Feature Elimination ◽  
Support Vector ◽  
Signal Source ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
Svm Model ◽  
Feature Based

AbstractPets have been indispensable members for many families in modern life, especially significant for the elderly and the blind. However, they may cause false alarm when misused as signal source in non-contact monitoring of the vital signs using ultra-wideband (UWB) radar. Distinguishing between humans and pets can help ensure the correct signal source. Nevertheless, existing solutions are few or only utilize a single feature, which can hinder robustness and accuracy because of individual differences. In this study, we proposed a robust multi-feature based method to solve the problem. First, 19 discriminative features were extracted to reflect differences in aspects of energy, frequency, wavelet entropy, and correlation coefficient. Second, the features were ranked by recursive feature elimination algorithm and the top eight were then selected to build an optimal support vector machine (SVM) model. The area under the receiver operating characteristic curve (AUC) of the optimal SVM model reached 0.9620. The false and missing alarms for identifying humans were 0.0962 and 0.0600, respectively. Finally, comparison with the state-of-the-art method that only employed one feature validated the advance and accuracy of the proposed method. The method is envisioned to facilitate the UWB radar applications in non-contact and continuous vital signs monitoring.

Ultra-Wideband Chaos Life-Detection Radar with Sinusoidal Wave Modulation

2017 ◽  
Vol 27 (13) ◽  
pp. 1730046 ◽  
Author(s):  
Hang Xu ◽  
Ying Li ◽  
Jianguo Zhang ◽  
Hong Han ◽  
Bing Zhang ◽  
...  
Keyword(s):  
Dynamic Range ◽  
Vital Signs ◽  
Radar System ◽  
Ultra Wideband ◽  
Thick Wall ◽  
Sinusoidal Wave ◽  
Echo Signal ◽  
Range Resolution ◽  
Life Detection ◽  
Lock In

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.

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
Keyword(s):  
Vital Signs ◽  
Radar System ◽  
Ultra Wideband ◽  
Circularly Polarized ◽  
Vital Signs Monitoring ◽  
Wideband Radar

scholarly journals A Radar-Based Smart Sensor for Unobtrusive Elderly Monitoring in Ambient Assisted Living Applications

2017 ◽  
Author(s):  
Giovanni Diraco ◽  
Alessandro Leone ◽  
Pietro Siciliano
Keyword(s):  
Technology Acceptance ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Daily Activities ◽  
Smart Sensor ◽  
Body Movements ◽  
Ambient Lighting ◽  
Wideband Radar

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.

scholarly journals Short-Range Vital Signs Sensing Based on EEMD and CWT Using IR-UWB Radar

2016 ◽  
Author(s):  
Xikun Hu ◽  
Tian Jin
Keyword(s):  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Vital Signs ◽  
Ensemble Empirical Mode Decomposition ◽  
The Body ◽  
Ultra Wideband ◽  
Detection Range ◽  
Wall Movement ◽  
Uwb Radar ◽  
Mode Decomposition

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities, and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.

scholarly journals Preclinical evaluation of noncontact vital signs monitoring using real-time IR-UWB radar and factors affecting its accuracy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun-Young Park ◽  
Yonggu Lee ◽  
Ran Heo ◽  
Hyun-Kyung Park ◽  
Seok-Hyun Cho ◽  
...  
Keyword(s):  
Real Time ◽  
Vital Sign ◽  
Vital Signs ◽  
Embedded Processors ◽  
Sitting Position ◽  
Mixed Effect ◽  
Factors Affecting ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
The Absolute

AbstractRecently, noncontact vital sign monitors have attracted attention because of issues related to the transmission of contagious diseases. We developed a real-time vital sign monitor using impulse-radio ultrawideband (IR-UWB) radar with embedded processors and software; we then evaluated its accuracy in measuring heart rate (HR) and respiratory rate (RR) and investigated the factors affecting the accuracy of the radar-based measurements. In 50 patients visiting a cardiology clinic, HR and RR were measured using IR-UWB radar simultaneously with electrocardiography and capnometry. All patients underwent HR and RR measurements in 2 postures—supine and sitting—for 2 min each. There was a high agreement between the RR measured using radar and capnometry (concordance correlation coefficient [CCC] 0.925 [0.919–0.926]; upper and lower limits of agreement [LOA], − 2.21 and 3.90 breaths/min). The HR measured using radar was also in close agreement with the value measured using electrocardiography (CCC 0.749 [0.738–0.760]; upper and lower LOA, − 12.78 and 15.04 beats/min). Linear mixed effect models showed that the sitting position and an HR < 70 bpm were associated with an increase in the absolute biases of the HR, whereas the sitting position and an RR < 18 breaths/min were associated with an increase in the absolute biases of the RR. The IR-UWB radar sensor with embedded processors and software can measure the RR and HR in real time with high precision. The sitting position and a low RR or HR were associated with the accuracy of RR and HR measurement, respectively, using IR-UWB radar.

scholarly journals Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 83
Author(s):  
Hongqiang Xu ◽  
Malikeh P. Ebrahim ◽  
Kareeb Hasan ◽  
Fatemeh Heydari ◽  
Paul Howley ◽  
...  
Keyword(s):  
Heart Rate ◽  
Signal Processing ◽  
Respiration Rate ◽  
Body Position ◽  
Random Noise ◽  
Vital Signs ◽  
Ultra Wideband ◽  
Spectrum Estimation ◽  
Respiration Activity ◽  
Uwb Radar

Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing: (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.

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