Is breathing frequency a potential means for monitoring exercise intensity in people with atrial fibrillation and coronary heart disease when heart rate is mitigated?

PURPOSE: Moderate-intensity aerobic exercise is safe and beneficial in atrial fibrillation (AF) and coronary heart disease (CHD). Irregular or rapid heart rates (HR) in AF and other heart conditions create a challenge to using HR to monitor exercise intensity. The purpose of this study was to assess the potential of breathing frequency (BF) to monitor exercise intensity in people with AF and CHD without AF. METHODS: This observational study included 30 AF participants (19 Male, 70.7 ± 8.7 yrs) and 67 non-AF CHD participants (38 Male, 56.9 ± 11.4 yrs). All performed an incremental maximal exercise test with pulmonary gas exchange. RESULTS: Peak aerobic power in AF ( V ˙ O2peak; 17.8 ± 5.0 ml.kg-1.min-1) was lower than in CHD (26.7 ml.kg-1.min-1) (p < .001). BF responses in AF and CHD were similar (BF peak: AF 34.6 ± 5.4 and CHD 36.5 ± 5.0 breaths.min-1; p = .106); at the 1st ventilatory threshold (BF@VT-1: AF 23.2 ± 4.6; CHD 22.4 ± 4.6 breaths.min-1; p = .240). % V ˙ O2peak at VT-1 were similar in AF and CHD (AF: 59%; CHD: 57%; p = .656). CONCLUSION: With the use of wearable technologies on the rise, that now include BF, this first study provides an encouraging potential for BF to be used in AF and CHD. As the supporting data are based on incremental ramp protocol results, further research is required to assess BF validity to manage exercise intensity during longer bouts of exercise.

Physiological Response to the COVID-19 Vaccine: Insights From a Prospective, Randomized, Single-Blinded, Crossover Trial.

BACKGROUND: Rapid development and implementation of vaccines constituted a crucial step in containing the COVID-19 pandemic. A comprehensive understanding of physiological responses to these vaccines is important to build trust in medicine. OBJECTIVE: This study aims to investigate temporal dynamics before and after COVID-19 vaccination in 4 physiological parameters as well as the duration of menstrual cycle phases. METHODS: In a prospective trial, 17,825 adults in the Netherlands wore a medical device on their wrist for up to 9 months. The device recorded their physiological signals and synchronized with a complementary smartphone app. By means of multilevel quadratic regression, we examined changes in wearable-recorded breathing rate, wrist skin temperature, heart rate, heart rate variability, and objectively assessed the duration of menstrual cycle phases in menstruating participants to assess the effects of COVID-19 vaccination. RESULTS: The recorded physiological signals demonstrated short-term increases in breathing rate and heart rate after COVID-19 vaccination followed by a prompt rebound to baseline levels likely reflecting biological mechanisms accompanying the immune response to vaccination. No sex differences were evident in the measured physiological responses. In menstruating participants, we found a 0.8% decrease in the duration of the menstrual phase following vaccination. CONCLUSIONS: The observed short-term changes suggest that COVID-19 vaccines are not associated with long-term biophysical issues. Taken together, our work provides valuable insights into continuous fluctuations of physiological responses to vaccination and highlights the importance of digital solutions in health care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-021-05241-5.

Evaluation of Lateral Radar Positioning for Vital Sign Monitoring: An Empirical Study.

Vital sign monitoring is dominated by precise but costly contact-based sensors. Contactless devices such as radars provide a promising alternative. In this article, the effects of lateral radar positions on breathing and heartbeat extraction are evaluated based on a sleep study. A lateral radar position is a radar placement from which multiple human body zones are mapped onto different radar range sections. These body zones can be used to extract breathing and heartbeat motions independently from one another via these different range sections. Radars were positioned above the bed as a conventional approach and on a bedside table as well as at the foot end of the bed as lateral positions. These positions were evaluated based on six nights of sleep collected from healthy volunteers with polysomnography (PSG) as a reference system. For breathing extraction, comparable results were observed for all three radar positions. For heartbeat extraction, a higher level of agreement between the radar foot end position and the PSG was found. An example of the distinction between thoracic and abdominal breathing using a lateral radar position is shown. Lateral radar positions could lead to a more detailed analysis of movements along the body, with the potential for diagnostic applications.

On-Road Evaluation of Unobtrusive In-Car Respiration Monitoring.

This paper introduces and evaluates an innovative sensor for unobtrusive in-car respiration monitoring, mounted on the backrest of the driver's seat. The sensor seamlessly integrates into the vehicle, measuring breathing rates continuously without requiring active participation from the driver. The paper proves the feasibility of unobtrusive in-car measurements over long periods of time. Operation of the sensor was investigated over 12 participants sitting in the driver seat. A total of 107 min of driving in diverse conditions with overall coverage rate of 84.45% underscores the sensor potential to reliably capture physiological changes in breathing rate for fatigue and stress detection.

To what degree patient-reported symptoms of central sensitization, kinesiophobia, disability, sleep, and life quality associated with 24-h heart rate variability and actigraphy measurements?

OBJECTIVES: Chronic musculoskeletal pain is associated with decreased parasympathetic and increased sympathetic activity in the autonomic nervous system. The objective of this study was to determine the associations between objective measures of heart rate variability (a measure of autonomic nervous system function), actigraphy (a measure of activity and sleep quality), respiration rates, and subjective patient-reported outcome measures (PROMs) of central sensitization, kinesiophobia, disability, the effect of pain on sleep, and life quality. METHODS: Thirty-eight study subjects were divided into two subgroups, including low symptoms of central sensitization (n = 18) and high symptoms of central sensitization (n = 20), based on patient-reported scores on the Central Sensitization Inventory (CSI). Heart rate variability (HRV) and actigraphy measurements were carried out simultaneously in 24 h measurement during wakefulness and sleep. RESULTS: A decrease in HRV during the first 2 h of sleep was stronger in the low CSI subgroup compared to the high CSI subgroup. Otherwise, all other HRV and actigraphy parameters and subjective measures of central sensitization, disability, kinesiophobia, the effect of pain on sleep, and quality of life showed only little associations. DISCUSSION: The high CSI subgroup reported significantly more severe symptoms of disability, kinesiophobia, sleep, and quality of life compared to the low CSI subgroup. However, there were only small and nonsignificant trend in increased sympathetic nervous system activity and poorer sleep quality on the high central sensitization subgroup. Moreover, very little differences in respiratory rates were found between the groups.

Repeatability, Reproducibility, and Concurrent Validity of a Stethoscope and Health App System for the Quantification of Breath Rate in Healthy Adults: Repeatability and Validity Study.

BACKGROUND: Apps for smartphones that can measure the breathing rate easily can be downloaded. OBJECTIVE: The aim of this study was to demonstrate agreement in measuring breath rates between the stethoscope and Breath Counter health app. METHODS: We performed a repeatability study with 56 healthy volunteers. The patient's demographic data and breathing rates per minute were collected. Breathing rates were measured via two methods: (1) using a stethoscope placed in the upper area of the right lung and (2) a Breath Counter app developed by Vadion on a Samsung Fold smartphone. RESULTS: This study demonstrated high repeatability and validity with respect to the breathing rate parameter of healthy adults using the aforementioned 2 systems. Intrasession repeatability measure using the intraclass correlation coefficient was >0.962, indicating excellent repeatability. Moreover, the intraclass correlation coefficient between methods was 0.793, indicating good repeatability, and coefficients of variation of method errors values were 1.83% with very low values in terms of other repeatability parameters. We found significant correlation coefficients and no systematic differences between the app and stethoscope methods. CONCLUSIONS: The app method may be attractive to individuals who require repeatability in a recreational setting.

Limbic and paralimbic respiratory modulation: From inhibition to enhancement.

OBJECTIVE: Increased understanding of the role of cortical structures in respiratory control may help the understanding of seizure-induced respiratory dysfunction that leads to sudden unexpected death in epilepsy (SUDEP). The aim of this study was to characterize respiratory responses to electrical stimulation (ES), including inhibition and enhancement of respiration. METHODS: We prospectively recruited 19 consecutive patients with intractable epilepsy undergoing stereotactic electroencephalography (EEG) evaluation from June 2015 to June 2018. Inclusion criteria were patients ≥18 years in whom ES was indicated for clinical mapping of ictal onset or eloquent cortex as part of the presurgical evaluation. ES was carried out at 50 Hz, 0.2 msec, and 1-10 mA current intensity. Common brain regions sampled across all patients were amygdala (AMY), hippocampus (HG), anterior cingulate gyrus (CING), orbitofrontal cortex (OrbF), temporal neocortex (TNC), temporal pole (TP), and entorhinal cortex (ERC). Seven hundred fifty-five stimulations were conducted. Quantitative analysis of breathing signal, that is, changes in breathing rate (BR), depth (TV), and minute ventilation (MV), was carried out during ES using the BreathMetrics breathing waveform analysis toolbox. Electrocardiography, arterial oxygen saturation, end-tidal and transcutaneous carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. RESULTS: Electrical stimulation of TP and CING (at lower current strengths <3 mA) increased TV and MV. At >7-10 mA, CING decreased TV and MV. On the other hand, decreased TV and MV occurred with stimulation of mesial temporal structures such as AMY and HG. Breathing changes were dependent on stimulation intensity. Lateral temporal, entorhinal, and orbitofrontal cortices did not affect breathing either way. SIGNIFICANCE: These findings suggest that breathing responses other than apnea can be induced by ES. Identification of two regions-the temporal pole and anterior cingulate gyrus-for enhancement of breathing may be important in paving the way to future development of strategies for prevention of SUDEP.

The development of behavioral and endocrine coping styles in nestlings from urban and rural sites.

Urbanization is increasing globally and altering the stressors that animals face in their everyday lives. Organisms often differ in their coping styles-both behavioral and endocrine-across urban to rural habitats. For example, urban animals are often bolder, more exploratory, and mount stronger glucocorticoid stress responses compared to their rural counterparts. While these coping styles are important in shaping fitness across the urban-to-rural gradient, it remains unclear when these differences arise in the life of organisms. We explore the development of coping styles in European starling nestlings (Sturnus vulgaris), an urban-adapted species. We test whether breathing rate, handling struggle rate, and bag struggle rate differ across sites and find no difference in the behavioral coping styles of nestlings raised in urban versus rural sites. We also explore differences in baseline and stress-induced glucocorticoids, finding that urban nestlings develop a stronger stress response than rural birds before fledging the nest. We find no significant correlations between behavioral and endocrine traits for urban or rural birds, which supports the two-tiered model of coping styles. One possibility is that behavioral and endocrine differences develop at different times over the lives of organisms. Our findings support prior work suggesting that behavioral and endocrine coping mechanisms act independently of one another, and suggests that endocrine coping mechanisms develop in early life and before differences in behavioral coping styles might arise. Future work on the mechanisms leading to early-life differences in coping styles-from genetics to maternal effects to environmental effects-is needed to best predict how urban-adapted organisms cope with environmental change. Studies across a greater number of sites will help disentangle site from urbanization effects.

Repeatability and reproducibility of changes in thoracoabdominal compartmental volumes and breathing pattern during low-, moderate- and heavy-intensity exercise.

PURPOSE: To determine how repeatable thoracoabdominal compartmental contributions to tidal volume (VT) are across different intensities of exercise, and to examine if the pattern of breathing for a given minute ventilation (V̇E) is reproducible between constant-load and ramp exercise tests. METHODS: Ten healthy adults (age: 27 ± 6 yr, peak oxygen uptake: 42 ± 5 mL min-1 kg-1) completed a 25 W·min-1 ramp cycling test to exhaustion and two repetitions of a step cycling test on separate days. VT, breathing rate (BR), and V̇E were assessed using a bi-directional turbine, and thoracic and abdominal contributions to VT were measured using respiratory inductance plethysmography. Repeatability (step vs. step) and reproducibility (step vs. ramp) of responses were assessed using the intra-class correlation coefficient (ICC). RESULTS: The relative compartment contributions to VT during step exercise were highly repeatable for low (ICC = 0.87, p = 0.003), moderate (ICC = 0.89, p = 0.002) and heavy (ICC = 0.93, p = 0.001) exercise. Inter-individual differences in response to higher intensity exercise were observed, as two participants had significant relationships between VT and their percent compartmental contributions to VT, but five others did not. No differences were identified between ramp and step exercise tests for VT (main effect: p = 0.61) or BR (main effect: p = 0.77) at matched V̇E for each intensity, and the pattern of breathing was reproducible for each intensity. CONCLUSION: These findings suggest the way young healthy adults breathe for a given V̇E is repeatable day-to-day and reproducible between different exercise protocols.

High frequency band limits in spectral analysis of heart rate variability in preterm infants.

OBJECTIVES: The current study aims to assess different high-frequency (HF) band power calculations based on different frequency bandwidth values, and compare them with the time domain the root mean square of successive RR differences (RMSSD) value in preterm infants. METHODS: At week 32, electrocardiogram (ECG) and breathing rate (BR) were recorded for 24 h on 30 preterm infants born between 28 and 32 weeks. The recording held in the neonatal intensive care unit without any interruption of routine. RESULTS: The median 24 h BR was 40-78 breaths per minute. The RMSSD was highly and positively correlated with frequency bands that were based on each preterms BR range, or on a constant frequency with band limits of 0.4-2 Hz. CONCLUSIONS: At week 32, HF band Hz limits should be calculated based on each child's breathing rate, generally between 0.4 and 2 Hz.

Performance Evaluation of a Smart Bed Technology against Polysomnography.

The Sleep Number smart bed uses embedded ballistocardiography, together with network connectivity, signal processing, and machine learning, to detect heart rate (HR), breathing rate (BR), and sleep vs. wake states. This study evaluated the performance of the smart bed relative to polysomnography (PSG) in estimating epoch-by-epoch HR, BR, sleep vs. wake, mean overnight HR and BR, and summary sleep variables. Forty-five participants (aged 22-64 years; 55% women) slept one night on the smart bed with standard PSG. Smart bed data were compared to PSG by Bland-Altman analysis and Pearson correlation for epoch-by-epoch HR and epoch-by-epoch BR. Agreement in sleep vs. wake classification was quantified using Cohen's kappa, ROC analysis, sensitivity, specificity, accuracy, and precision. Epoch-by-epoch HR and BR were highly correlated with PSG (HR: r = 0.81, |bias| = 0.23 beats/min; BR: r = 0.71, |bias| = 0.08 breaths/min), as were estimations of mean overnight HR and BR (HR: r = 0.94, |bias| = 0.15 beats/min; BR: r = 0.96, |bias| = 0.09 breaths/min). Calculated agreement for sleep vs. wake detection included kappa (prevalence and bias-adjusted) = 0.74 ± 0.11, AUC = 0.86, sensitivity = 0.94 ± 0.05, specificity = 0.48 ± 0.18, accuracy = 0.86 ± 0.11, and precision = 0.90 ± 0.06. For all-night summary variables, agreement was moderate to strong. Overall, the findings suggest that the Sleep Number smart bed may provide reliable metrics to unobtrusively characterize human sleep under real life-conditions.

Non-Contact Breathing Monitoring Using Sleep Breathing Detection Algorithm (SBDA) Based on UWB Radar Sensors.

Ultra-wideband radar application for sleep breathing monitoring is hampered by the difficulty of obtaining breathing signals for non-stationary subjects. This occurs due to imprecise signal clutter removal and poor body movement removal algorithms for extracting accurate breathing signals. Therefore, this paper proposed a Sleep Breathing Detection Algorithm (SBDA) to address this challenge. First, SBDA introduces the combination of variance feature with Discrete Wavelet Transform (DWT) to tackle the issue of clutter signals. This method used Daubechies wavelets with five levels of decomposition to satisfy the signal-to-noise ratio in the signal. Second, SBDA implements a curve fit based sinusoidal pattern algorithm for detecting periodic motion. The measurement was taken by comparing the R-square value to differentiate between chest and body movements. Last but not least, SBDA applied the Ensemble Empirical Mode Decomposition (EEMD) method for extracting breathing signals before transforming the signal to the frequency domain using Fast Fourier Transform (FFT) to obtain breathing rate. The analysis was conducted on 15 subjects with normal and abnormal ratings for sleep monitoring. All results were compared with two existing methods obtained from previous literature with Polysomnography (PSG) devices. The result found that SBDA effectively monitors breathing using IR-UWB as it has the lowest average percentage error with only 6.12% compared to the other two existing methods from past research implemented in this dataset.

Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning.

Breathing rate is considered one of the fundamental vital signs and a highly informative indicator of physiological state. Given that the monitoring of heart activity is less complex than the monitoring of breathing, a variety of algorithms have been developed to estimate breathing activity from heart activity. However, estimating breathing rate from heart activity outside of laboratory conditions is still a challenge. The challenge is even greater when new wearable devices with novel sensor placements are being used. In this paper, we present a novel algorithm for breathing rate estimation from photoplethysmography (PPG) data acquired from a head-worn virtual reality mask equipped with a PPG sensor placed on the forehead of a subject. The algorithm is based on advanced signal processing and machine learning techniques and includes a novel quality assessment and motion artifacts removal procedure. The proposed algorithm is evaluated and compared to existing approaches from the related work using two separate datasets that contains data from a total of 37 subjects overall. Numerous experiments show that the proposed algorithm outperforms the compared algorithms, achieving a mean absolute error of 1.38 breaths per minute and a Pearson's correlation coefficient of 0.86. These results indicate that reliable estimation of breathing rate is possible based on PPG data acquired from a head-worn device.

Integrating Wearable Sensors and Video to Determine Microlocation-Specific Physiologic and Motion Biometrics-Method Development for Competitive Climbing.

Competitive indoor climbing has increased in popularity at the youth, collegiate, and Olympic levels. A critical aspect for improving performance is characterizing the physiologic response to different climbing strategies (e.g., work/rest patterns, pacing) and techniques (e.g., body position and movement) relative to location on climbing wall with spatially varying characteristics (e.g., wall inclinations, position of foot/hand holds). However, this response is not well understood due to the limited capabilities of climbing-specific measurement and assessment tools. In this study, we developed a novel method to examine time-resolved sensor-based measurements of multiple personal biometrics at different microlocations (finely spaced positions; MLs) along a climbing route. For the ML-specific biometric system (MLBS), we integrated continuous data from wearable biometric sensors and smartphone-based video during climbing, with a customized visualization and analysis system to determine three physiologic parameters (heart rate, breathing rate, ventilation rate) and one body movement parameter (hip acceleration), which are automatically time-matched to the corresponding video frame to determine ML-specific biometrics. Key features include: (1) biometric sensors that are seamlessly embedded in the fabric of an athletic compression shirt, and do not interfere with climbing performance, (2) climbing video, and (3) an interactive graphical user interface to rapidly visualize and analyze the time-matched biometrics and climbing video, determine timing sequence between the biometrics at key events, and calculate summary statistics. To demonstrate the capabilities of MLBS, we examined the relationship between changes in ML-specific climbing characteristics and changes in the physiologic parameters. Our study demonstrates the ability of MLBS to determine multiple time-resolved biometrics at different MLs, in support of developing and assessing different climbing strategies and training methods to help improve performance.

Spontaneous Breathing Rate Variations Linked to Social Exclusion and Emotion Self-assessment.

The emotional reactions to social exclusion can be associated with physiological responses that could allow researchers to estimate the valence and intensity of the ongoing affective state. In this work, respiratory activity was analysed to verify whether breathing rate variations can be considered as predictive factors of subsequent positive and negative affect after inclusion and exclusion in young women. A standard Cyberball task was implemented and manipulated information was provided to the participants to create both conditions. The participants were socially excluded by limiting their participation to 6% of the total number of passes among three teammates and providing negative feedback about them. The results suggest that breathing rate can be a good option to infer subjective feelings during social interactions and a promising feature to incorporate into modern emotion monitoring systems as an alternative to other physiological measures. Furthermore, the interaction between metaemotion and physiology was studied by recording breathing rate while completing the Positive and Negative Affect Schedule, evidencing a breathing rate increase during the emotion self-assessment only after exclusion.

Host personality predicts cuckoo egg rejection in Daurian redstarts Phoenicurus auroreus.

In species that are subject to brood parasitism, individuals often vary in their responses to parasitic eggs, with some rejecting the eggs while others do not. While some factors, such as host age (breeding experience), the degree of egg matching and the level of perceived risk of brood parasitism have been shown to influence host decisions, much of the variation remains unexplained. The host personality hypothesis suggests that personality traits of the host influence its response to parasitic eggs, but few studies have tested this. We investigated the relationship between two personality traits (exploration and neophobia) and a physiological trait (breathing rate) of the host, and egg-rejection behaviour in a population of Daurian redstarts Phoenicurus auroreus in northeast China. We first show that exploratory behaviour and the response to a novel object are repeatable for individual females and strongly covary, indicating distinct personality types. We then show that fast-exploring and less neophobic hosts were more likely to reject parasitic eggs than slow-exploring and more neophobic hosts. Variation in breathing rate-a measure of the stress-response-did not affect rejection behaviour. Our results demonstrate that host personality, along the bold-shy continuum, predicts the responses to parasitic eggs in Daurian redstarts, with bold hosts being more likely to reject parasitic eggs.

Temperatures in Pigs During 3 T MRI Temperatures, Heart Rates, and Breathing Rates of Pigs During RF Power Deposition in a 3 T (128 MHz) Body Coil.

Exposure to radiofrequency (RF) power deposition during magnetic resonance imaging (MRI) induces elevated body-tissue temperatures and may cause changes in heart and breathing rates, disturbing thermoregulation. Eleven temperature sensors were placed in muscle tissue and one sensor in the rectum (measured in 10 cm depth) of 20 free-breathing anesthetized pigs to verify temperature curves during RF exposure. Tissue temperatures and heart and breathing rates were measured before, during, and after RF exposure. Pigs were placed into a 60-cm diameter whole-body resonator of a 3 T MRI system. Nineteen anesthetized pigs were divided into four RF exposure groups: sham (0 W/kg), low-exposure (2.7 W/kg, mean exposure time 56 min), moderate-exposure (4.8 W/kg, mean exposure time 31 min), and high-exposure (4.4 W/kg, mean exposure time 61 min). One pig was exposed to a whole-body specific absorption rate (wbSAR) of 11.4 W/kg (extreme-exposure). Hotspot temperatures, measured by sensor 2, increased by mean 5.0 ± 0.9°C, min 3.9; max 6.3 (low), 7.0 ± 2.3°C, min 4.6; max 9.9 (moderate), and 9.2 ± 4.4°C, min 6.1, max 17.9 (high) compared with 0.3 ± 0.3°C in the sham-exposure group (min 0.1, max 0.6). Four time-temperature curves were identified: sinusoidal, parabolic, plateau, and linear. These curve shapes did not correlate with RF intensity, rectal temperature, breathing rate, or heart rate. In all pigs, rectal temperatures increased (2.1 ± 0.9°C) during and even after RF exposure, while hotspot temperatures decreased after exposure. When rectal temperature increased by 1°C, hotspot temperature increased up to 42.8°C within 37 min (low-exposure) or up to 43.8°C within 24 min (high-exposure). Global wbSAR did not correlate with maximum hotspot. Bioelectromagnetics. 2021;42:37-50. © 2020 The Authors. Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.

Contactless Small-Scale Movement Monitoring System Using Software Defined Radio for Early Diagnosis of COVID-19.

The exponential growth of the novel coronavirus disease (N-COVID-19) has affected millions of people already and it is obvious that this crisis is global. This situation has enforced scientific researchers to gather their efforts to contain the virus. In this pandemic situation, health monitoring and human movements are getting significant consideration in the field of healthcare and as a result, it has emerged as a key area of interest in recent times. This requires a contactless sensing platform for detection of COVID-19 symptoms along with containment of virus spread by limiting and monitoring human movements. In this paper, a platform is proposed for the detection of COVID-19 symptoms like irregular breathing and coughing in addition to monitoring human movements using Software Defined Radio (SDR) technology. This platform uses Channel Frequency Response (CFR) to record the minute changes in Orthogonal Frequency Division Multiplexing (OFDM) subcarriers due to any human motion over the wireless channel. In this initial research, the capabilities of the platform are analyzed by detecting hand movement, coughing, and breathing. This platform faithfully captures normal, slow, and fast breathing at a rate of 20, 10, and 28 breaths per minute respectively using different methods such as zero-cross detection, peak detection, and Fourier transformation. The results show that all three methods successfully record breathing rate. The proposed platform is portable, flexible, and has multifunctional capabilities. This platform can be exploited for other human body movements and health abnormalities by further classification using artificial intelligence.

Portable Micro-Doppler Radar with Quadrature Radar Architecture for Non-Contact Human Breath Detection.

Recently, rapid advances in radio detection and ranging (radar) technology applications have been implemented in various fields. In particular, micro-Doppler radar has been widely developed to perform certain tasks, such as detection of buried victims in natural disaster, drone system detection, and classification of humans and animals. Further, micro-Doppler radar can also be implemented in medical applications for remote monitoring and examination. This paper proposes a human respiration rate detection system using micro-Doppler radar with quadrature architecture in the industrial, scientific, and medical (ISM) frequency of 5.8 GHz. We use a mathematical model of human breathing to further explore any insights into signal processes in the radar. The experimental system is designed using the USRP B200 mini-module as the main component of the radar and the Vivaldi antennas working at 5.8 GHz. The radar system is integrated directly with the GNU Radio Companion software as the processing part. Using a frequency of 5.8 GHz and USRP output power of 0.33 mW, our proposed method was able to detect the respiration rate at a distance of 2 m or less with acceptable error. In addition, the radar system could differentiate different frequency rates for different targets, demonstrating that it is highly sensitive. We also emphasize that the designed radar system can be used as a portable device which offers flexibility to be used anytime and anywhere.

Smart Face Mask with an Integrated Heat Flux Sensor for Fast and Remote People's Healthcare Monitoring.

The COVID-19 pandemic has highlighted a large amount of challenges to address. To combat the spread of the virus, several safety measures, such as wearing face masks, have been taken. Temperature controls at the entrance of public places to prevent the entry of virus carriers have been shown to be inefficient and inaccurate. This paper presents a smart mask that allows to monitor body temperature and breathing rate. Body temperature is measured by a non-invasive dual-heat-flux system, consisting of four sensors separated from each other with an insulating material. Breathing rate is obtained from the temperature changes within the mask, measured with a thermistor located near the nose. The system communicates by means of long-range (LoRa) backscattering, leading to a reduction in average power consumption. It is designed to establish the relative location of the smart mask from the signal received at two LoRa receivers installed inside and outside an access door. Low-cost LoRa transceivers with WiFi capabilities are used in the prototype to collect information and upload it to a server. Accuracy in body temperature measurements is consistent with measurements made with a thermistor located in the armpit. The system allows checking the correct placement of the mask based on the recorded temperatures and the breathing rate measurements. Besides, episodes of cough can be detected by sudden changes in thermistor temperature.