scholarly journals Motion-Tolerant Non-Contact Heart-Rate Measurements from Radar Sensor Fusion

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1774
Author(s):  
Yu Rong ◽  
Arindam Dutta ◽  
Alex Chiriyath ◽  
Daniel W. Bliss
Keyword(s):  
Heart Rate ◽  
Vital Sign ◽  
Human Subjects ◽  
Body Movement ◽  
Processing Technique ◽  
Ultra Wideband ◽  
Signal Processing Technique ◽  
Active Motion ◽  
Microwave Radar ◽  
Radar Measurements

Microwave radar technology is very attractive for ubiquitous short-range health monitoring due to its non-contact, see-through, privacy-preserving and safe features compared to the competing remote technologies such as optics. The possibility of radar-based approaches for breathing and cardiac sensing was demonstrated a few decades ago. However, investigation regarding the robustness of radar-based vital-sign monitoring (VSM) is not available in the current radar literature. In this paper, we aim to close this gap by presenting an extensive experimental study of vital-sign radar approach. We consider diversity in test subjects, fitness levels, poses/postures, and, more importantly, random body movement (RBM) in the study. We discuss some new insights that lead to robust radar heart-rate (HR) measurements. A novel active motion cancellation signal-processing technique is introduced, exploiting dual ultra-wideband (UWB) radar system for motion-tolerant HR measurements. Additionally, we propose a spectral pruning routine to enhance HR estimation performance. We validate the proposed method theoretically and experimentally. Totally, we record and analyze about 3500 seconds of radar measurements from multiple human subjects.

EXPRESS: The effect of low frequency equalisation on preference and sensorimotor synchronisation in music

2021 ◽  
pp. 174702182110371
Author(s):  
Scott Beveridge ◽  
Estefanía Cano ◽  
Steffen A. Herff
Keyword(s):  
Body Movement ◽  
Low Frequency ◽  
Empirical Support ◽  
Processing Technique ◽  
Original Version ◽  
Upper Body ◽  
Signal Processing Technique ◽  
Band Energy ◽  
Sensorimotor Synchronisation ◽  
Specific Frequency

Equalisation, a signal processing technique commonly used to shape the sound of music, is defined as the adjustment of the energy in specific frequency components of a signal. In this work we investigate the effects of equalisation on preference and sensorimotor synchronisation in music. Twenty-one participants engaged in a goal-directed upper body movement in synchrony with stimuli equalised in three low-frequency sub-bands (0 - 50 Hz, 50 - 100 Hz, 100 - 200 Hz). To quantify the effect of equalisation, music features including spectral flux, pulse clarity, and beat confidence were extracted from seven differently equalised versions of music tracks - one original and six manipulated versions for each music track. These music tracks were then used in a movement synchronisation task. Bayesian mixed effects models revealed different synchronisation behaviours in response to the three sub-bands considered. Boosting energy in the 100 - 200 Hz sub-band reduced synchronisation performance irrespective of the sub-band energy of the original version. An energy boost in the 0 - 50 Hz band resulted in increased synchronisation performance only when the sub-band energy of the original version was high. An energy boost in the 50 - 100 Hz band increased synchronisation performance only when the sub-band energy of the original version was low. Boosting the energy in any of the three subbands increased preference regardless of the energy of the original version. Our results provide empirical support for the importance of low-frequency information for sensorimotor synchronisation and suggest that the effect of equalisation on preference and synchronisation are largely independent of one another.

Methods and Algorithms for Technical Vision in Radar Introscopy

2019 ◽  
pp. 373-391
Author(s):  
Oleg Sytnik ◽  
Vladimir Kartashov
Keyword(s):  
Signal Processing ◽  
Processing Technique ◽  
Ultra Wideband ◽  
Radar Signal ◽  
Signal Spectrum ◽  
Signal Processing Technique ◽  
Distinctive Features ◽  
Technical Vision ◽  
Probing Signal ◽  
Radio Vision

Optimization of technical characteristics of radio vision systems is considered in the radars with ultra-wideband sounding signals. Highly noisy conditions, in which such systems operate, determine the requirements that should be met by the signals being studied. The presence of the multiplicative noise makes it difficult to design optimal algorithms of echo-signal processing. Consideration is being given to the problem of discriminating objects hidden under upper layers of the ground at depths comparable to the probing pulse duration. Based upon the cepstrum and textural analysis, a subsurface radar signal processing technique has been suggested. It is shown that, however the shape of the probing signal spectrum might be, the responses from point targets in the cepstrum images of subsurface ground layers make up the texture whose distinctive features enable objects to be detected and identified.

A COVID-19 Non-contact Screening System Based on XGBoost and Logistic Regression (Preprint)

2021 ◽  
Author(s):  
Chunheng Shang ◽  
Yixian Qiao ◽  
Xiwen Liao ◽  
Xiaoning Yuan ◽  
Qin Cheng ◽  
...  
Keyword(s):  
Heart Rate ◽  
Logistic Regression ◽  
Body Movement ◽  
Recall Rate ◽  
Machine Learning Algorithms ◽  
Ultra Wideband ◽  
Monitoring Data ◽  
Screening System ◽  
Contact Screening ◽  
Radar Monitoring

BACKGROUND COVID-19 is a new infectious disease with high infectivity. At present, body temperature detection is the main method for primary screening, but this single detection method has poor accuracy and is easy to miss detection. OBJECTIVE The objective of our study was to propose a non-contact, high-precision COVID-19 screening system. METHODS We used impulse-radio ultra-wideband (IR-UWB) radar to detect the respiration, heart rate, body movement, sleep quality, and various other physiological indicators. We collected 140 radar monitoring data from 23 COVID-19 patients in Wuhan Tongji Hospital, and compared them with 144 radar monitoring data of healthy controls. Then XGBoost and logistic regression(XGBoost+LR) algorithm was used to classify the data of patients and healthy people; feature selection was performed by SHAP value; using ten-fold cross-validation, XGBoost+LR algorithm was compared with five other classic classification algorithms, and the classification performance was evaluated by precision, recall, and the area under the ROC curve( AUC ). RESULTS The XGBoost+LR algorithm demonstrate excellent discrimination (precision=99.1 %, recall rate = 94.1 %, AUC=98.7 %), which is superior to several other single machine learning algorithms. In addition, the SHAP value indicate that number of apnea during REM(‘ REMSATims’) and mean heart rate(‘meanHR’) are important features for classification. CONCLUSIONS The COVID-19 non-contact screening system based on XGBoost+LR algorithm can accurately predict COVID-19 patients and can be applied in isolation wards to effectively help medical staff.

scholarly journals HEAR: Approach for Heartbeat Monitoring with Body Movement Compensation by IR-UWB Radar

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3077 ◽  
Author(s):  
Wenfeng Yin ◽  
Xiuzhu Yang ◽  
Lei Li ◽  
Lin Zhang ◽  
Nattapong Kitsuwan ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Movement ◽  
Large Body ◽  
Ultra Wideband ◽  
Heart Rate Variability Analysis ◽  
Mean Deviation ◽  
Fast Time ◽  
Heart Rates ◽  
Mode Decomposition ◽  
Wideband Radar

Further applications of impulse radio ultra-wideband radar in mobile health are hindered by the difficulty in extracting such vital signals as heartbeats from moving targets. Although the empirical mode decomposition based method is applied in recovering waveforms of heartbeats and estimating heart rates, the instantaneous heart rate is not achievable. This paper proposes a Heartbeat Estimation And Recovery (HEAR) approach to expand the application to mobile scenarios and extract instantaneous heartbeats. Firstly, the HEAR approach acquires vital signals by mapping maximum echo amplitudes to the fast time delay and compensating large body movements. Secondly, HEAR adopts the variational nonlinear chirp mode decomposition in extracting instantaneous frequencies of heartbeats. Thirdly, HEAR extends the clutter removal method based on the wavelet decomposition with a two-parameter exponential threshold. Compared to heart rates simultaneously collected by electrocardiograms (ECG), HEAR achieves a minimum error rate 4.6% in moving state and 2.25% in resting state. The Bland–Altman analysis verifies the consistency of beat-to-beat intervals in ECG and extracted heartbeat signals with the mean deviation smaller than 0.1 s. It indicates that HEAR is practical in offering clinical diagnoses such as the heart rate variability analysis in mobile monitoring.

scholarly journals A Remote Sensor System Based on TDLAS Technique for Ammonia Leakage Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2448
Author(s):  
Hongbin Lu ◽  
Chuantao Zheng ◽  
Lei Zhang ◽  
Zhiwei Liu ◽  
Fang Song ◽  
...  
Keyword(s):  
Signal Processing ◽  
Limit Of Detection ◽  
Processing Technique ◽  
Tunable Diode Laser ◽  
Sensor System ◽  
Signal Processing Technique ◽  
Suppression Effect ◽  
Output Wavelength ◽  
Deviation Analysis ◽  
Remote Sensor

The development of an efficient, portable, real-time, and high-precision ammonia (NH3) remote sensor system is of great significance for environmental protection and citizens’ health. We developed a NH3 remote sensor system based on tunable diode laser absorption spectroscopy (TDLAS) technique to measure the NH3 leakage. In order to eliminate the interference of water vapor on NH3 detection, the wavelength-locked wavelength modulation spectroscopy technique was adopted to stabilize the output wavelength of the laser at 6612.7 cm−1, which significantly increased the sampling frequency of the sensor system. To solve the problem in that the light intensity received by the detector keeps changing, the 2f/1f signal processing technique was adopted. The practical application results proved that the 2f/1f signal processing technique had a satisfactory suppression effect on the signal fluctuation caused by distance changing. Using Allan deviation analysis, we determined the stability and limit of detection (LoD). The system could reach a LoD of 16.6 ppm·m at an average time of 2.8 s, and a LoD of 0.5 ppm·m at an optimum averaging time of 778.4 s. Finally, the measurement result of simulated ammonia leakage verified that the ammonia remote sensor system could meet the need for ammonia leakage detection in the industrial production process.

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