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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 ˙ O 2 peak; 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 ˙ O 2 peak 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., (© 2024. The Author(s).)

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., (©Andjela Markovic, Vladimir Kovacevic, Timo B Brakenhoff, Duco Veen, Paul Klaver, Marianna Mitratza, George S Downward, Diederick E Grobbee, Maureen Cronin, Brianna M Goodale, COVID-19 Remote Early Detection (COVID-RED) consortium. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.07.2024.)

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.

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., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

This paper aims to study the accuracy of cardiopulmonary physiological parameters measurement under different exercise intensity in the accompanying (wearable) physiological parameter monitoring system. SensEcho, an accompanying physiological parameter monitoring system, and CORTEX METALYZER 3B, a cardiopulmonary function testing system, were used to simultaneously collect the cardiopulmonary physiological parameters of 28 healthy volunteers (17 males and 11 females) in various exercise states, such as standing, lying down and Bruce treadmill exercise. Bland-Altman analysis, correlation analysis and other methods, from the perspective of group and individual, were used to contrast and analyze the two types of equipment to measure parameters of heart rate and breathing rate. The results of group analysis showed that the heart rate and respiratory rate data box charts collected by the two devices were highly consistent. The heart rate difference was (-0.407 ± 3.380) times/min, and the respiratory rate difference was (-0.560 ± 7.047) times/min. The difference was very small. The Bland-Altman plot of the heart rate and respiratory rate in each experimental stage showed that the proportion of mean ± 2SD was 96.86% and 95.29%, respectively. The results of individual analysis showed that the correlation coefficients of the whole-process heart rate and respiratory rate data were all greater than 0.9. In conclusion, SensEcho, as an accompanying physiological parameter monitoring system, can accurately measure the human heart rate, respiration rate and other key cardiopulmonary physiological parameters under various sports conditions. It can maintain good stability under various sports conditions and meet the requirements of continuous physiological signal collection and analysis application under sports conditions.

A novel quantitative method for coding epochs of active and quiet sleep in infants using respiration is reported. The approach uses the variance of the instantaneous breathing rate within brief epochs of sleep. Variances are normalized within subject by dividing by the 75th percentile variance across epochs. Then, a normalized variance active sleep threshold of 0.29 was determined to produce the highest concordance with a method based on visual inspection of respiratory variability (100% and 90% for quiet and active sleep, respectively). The method was independently validated by comparing to standard polysomnographic state coding (87% and 80% concordance for quiet and active sleep) as well as with behavioral state coding (92% and 78% for quiet and active sleep). Validity was also demonstrated by showing that sleep states identified by the method resulted in the expected state differences in infant heart rate variability and electrocortical activity., (© 2016 Wiley Periodicals, Inc.)

The present study determined whether EEG and/or EMG recordings could be used to reliably define activity states in the Brazilian black and white tegu lizard (Tupinambis merianae) and then examined the interactive effects of temperature and activity states on strategies for matching O2 supply and demand. In a first series of experiments, the rate of oxygen consumption (VO2), breathing frequency (fR), heart rate (fH), and EEG and EMG (neck muscle) activity were measured in different sleep/wake states (sleeping, awake but quiet, alert, or moving). In general, metabolic and cardio-respiratory changes were better indictors of the transition from sleep to wake than were changes in the EEG and EMG. In a second series of experiments, the interactive effects of temperature (17, 27 and 37 °C) and activity states on fR, tidal volume (VT), the fraction of oxygen extracted from the lung per breath (FIO2-FEO2), fH, and the cardiac O2 pulse were quantified to determine the relative roles of each of these variables in accommodating changes in VO2. The increases in oxygen supply to meet temperature- and activity-induced increases in oxygen demand were produced almost exclusively by increases in fH and fR. Regression analysis showed that the effects of temperature and activity state on the relationships between fH, fR and VO2 was to extend a common relationship along a single curve, rather than separate relationships for each metabolic state. For these lizards, the predictive powers of fR and fH were maximized when the effects of changes in temperature, digestive state and activity were pooled. However, the best r(2) values obtained were 0.63 and 0.74 using fR and fH as predictors of metabolic rate, respectively.

We tested the validity of the Hexoskin wearable vest to monitor heart rate (HR), breathing rate (BR), tidal volume (VT), minute ventilation, and hip motion intensity (HMI) in comparison with laboratory standard devices during lying, sitting, standing, and walking. Twenty healthy young volunteers participated in this study. First, participants walked 6 min on a treadmill at speeds of 1, 3, and 4.5 km/h followed by increasing treadmill grades until 80% of their predicted maximal heart rate. Second, lying, sitting, and standing tasks were performed (5 min each) followed by 6 min of treadmill walking at 80% of their ventilatory threshold. Analysis of each individual's mean values under each resting or exercise condition by the 2 measurement systems revealed low coefficient of variation and high intraclass correlation values for HR, BR, and HMI. The Bland-Altman results from HR, BR, and HMI indicated no deviation of the mean value from zero and relatively small variability about the mean. VT and minute ventilation were provided in arbitrary units by the Hexoskin device; however, relative magnitude of change from Hexoskin closely tracked the laboratory standard method. Hexoskin presented low variability, good agreement, and consistency. The Hexoskin wearable vest was a valid and consistent tool to monitor activities typical of daily living such as different body positions (lying, sitting, and standing) and various walking speeds.

In this short article, we present a new method to use a smartphone placed unattached on a subject’s chest in the supine position to obtain heartbeat and breathing signals and estimate heart and breathing rates, simultaneously. We collected 3-axis accelerometer, gyroscope, and magnetometer signals and performed sensor fusion to extract a user’s breathing signal and breathing rate. A hidden Markov model was used to segment the ballistocardiograph/seismocardiograph signals and extract the heart rate. The smartphone application was verified against breathing belt measurements and electrocardiogram measurements. We modified and proposed several suitable signal quality metrics for seismocardiograph signals. The overall results show that the application accurately estimated the breathing and heart rates, achieving a minimum mean percent error of 2.52% for breathing and 2.33% for heart rate. This work is a big step forward for vital sign estimation using inexpensive pervasive devices.

Sleep regularity and chronotype can affect health, performance, and overall well-being. This observational study examines how sleep regularity and chronotype affect sleep quality and cardiorespiratory metrics. Data was collected from 1 January 2019 through 30 December 2019 from over 330 000 Sleep Number smart bed users across the United States who opted into this at-home study. A pressure signal from the smart bed reflected bed presence, movements, heart rate (HR), and breathing rate (BR). Participants (mean age: 55.69 years [SD: 14.0]; 51.2% female) were categorized by chronotype (16.8% early; 62.2% intermediate, 20.9% late) and regularity of sleep timing. Participants who were regular sleepers (66.1%) experienced higher percent restful sleep and lower mean HR and BR compared to the 4.8% categorized as irregular sleepers. Regular early-chronotype participants displayed better sleep and cardiorespiratory parameters compared to those with regular late-chronotypes. Significant variations were noted in sleep duration (Cohen's d = 1.54 and 0.88, respectively) and restful sleep (Cohen's d = 1.46 and 0.82, respectively) between early and late chronotypes, particularly within regular and irregular sleep patterns. This study highlights how sleep regularity and chronotype influence sleep quality and cardiorespiratory metrics. Irrespective of chronotype, sleep regularity demonstrated a substantial effect. Further research is necessary to confirm these findings. [ABSTRACT FROM AUTHOR]

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.

Abnormalities in cardiorespiratory measurements have repeatedly been found in patients with panic disorder (PD) during laboratory-based assessments. However, recordings performed outside laboratory settings are required to test the ecological validity of these findings. Wearable devices, such as sensor-imbedded garments, biopatches, and smartwatches, are promising tools for this purpose. We systematically reviewed the evidence for wearables-based cardiorespiratory assessments in PD by searching for publications on the PubMed, PsycINFO, and Embase databases, from inception to 30 July 2022. After the screening of two-hundred and twenty records, eight studies were included. The limited number of available studies and critical aspects related to the uncertain reliability of wearables-based assessments, especially concerning respiration, prevented us from drawing conclusions about the cardiorespiratory function of patients with PD in daily life. We also present preliminary data on a pilot study conducted on volunteers at the Villa San Benedetto Menni Hospital for evaluating the accuracy of heart rate (HR) and breathing rate (BR) measurements by the wearable Zephyr BioPatch compared with the Quark-b2 stationary testing system. Our exploratory results suggested possible BR and HR misestimation by the wearable Zephyr BioPatch compared with the Quark-b2 system. Challenges of wearables-based cardiorespiratory assessment and possible solutions to improve their reliability and optimize their significant potential for the study of PD pathophysiology are presented. [ABSTRACT FROM AUTHOR]

Vital sign monitoring is fundamental in daily patient care. Wearable technology has become an important tool in personalized medicine; however, there is a tradeoff problem between accuracy and comfort caused by the elastic textile used. Our study sought to examine the accuracy of heart rate (HR) and breathing rate (BR) monitoring as measured by iSmartweaR, a novel wearable and wireless sensor that uses the laser Doppler technique, with special focus on sex and different static postures. A total of 30 male and 23 female patients, including 23 patients with cardiovascular diseases and 30 healthy participants, were recruited. The HR and BR were measured with iSmartweaR and the gold standard method (CardioSoft and MasterScreen™ CPX) simultaneously in three static postures (supine rest, right lateral decubitus, and left lateral decubitus). The mean errors of HR and BR between iSmartweaR and the gold standard method were close to zero (0.55 and 0.71, respectively). The standard deviations of the HR error and BR error were 0.59 and 0.67, respectively. Disease, posture, sex, and measurement time did not cause clinically significant measurement errors. The overall percentage of missing data was 7.01%. The use of iSmartweaR was valid across different sexes and static postures. It is real-time, continuous and manpower-saving, and can be applied in patient care. [ABSTRACT FROM AUTHOR]

Background&Purpose: One of the most important goals of any athlete is optimum performance during competitions, and biofeedback is one of the new and growing ways to improve athletes' performance. This study investigated the effect of biofeedback exercises on some physiological factors and the performance of skilled archers. Method: The present study was a semi-experimental type with pre-test and post-test design and a control group. Twenty four young men with an average age of 22.5 years were purposefully recruited among the participants who attended national ranking archery competitions and randomly assigned to an experimental and a control group, each consisting of 12 participants. After the pre-test (archery performance test), the experimental group first attended 10 sessions of biofeedback training related to heart rate control and breathing control based on the training protocol and then attended 10 sessions of the same biofeedback exercises with skin conduction guidance. Both groups continued their routine archery exercises under the supervision of the researchers during this period. After completing 20 training sessions, the archery performance was taken again as the post-test with the same pretest condition from both groups. Results: The results showed that the heart rate of the participants was higher in tension and stress conditions compared to the resting state (p < 0.05). Also, at the post-test, the experimental group showed a lower heart rate under stress conditions compared to the control group (p < 0.05). Moreover, the analysis of covariance showed that the performance of both groups improved compared to the pre-test, but the experimental group performed better than the control group (p < 0.05). Conclusion: According to the findings of this study, more attention should be given to biofeedback exercises, and it is suggested to emphasize its use along with other training protocols. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We hypothesize that recent (2017) changes in competition rules significantly affected kinematic (mechanical activity) and physiological (cardiopulmonary indices and lactate concentration) profile of the taekwondo combat, which is currently becoming more demanding in terms of exercise intensity and fatigue. Twenty two male and female elite taekwondo athletes were followed up for over 2 years. In total, 258 real tournament combats were included in the analysis (133 in old rules and 125 in new rules). Kinematic and physiological characteristics were recorded using a biomonitor (BioHarness 3; Zephyr Technologies) worn by athletes during tournaments. Blood samples were drawn after each combat for lactate concentration. Our research showed that recent amendments of competition rules were linked to a noticeable shift toward higher kinematic output and, consequently, increased physiological response. Significant increments in kinematic variables (3-8%), heart rate (HR) (1.5-1.8%), energy expenditure (EE) (3-5%), overall physiological load (2-4%), and lactate concentration (~15% immediately after exercise and ~25% in recovery) suggest that new rules are more demanding, although the statistical effect size is only small or moderate. In conclusion, after competition rule changes, there has been a shift in taekwondo combat profile toward greater body movement dynamics, higher intensity, and greater postexercise fatigue. The values of key indices of exercise response (mechanical activity, HR, EE, and lactate concentration) during tournaments are near or exceeding the maximum attained during progressive exercise until exhaustion. Therefore, more focus is needed on taekwondo-specific high-intensity training and post-combat recovery to adapt athletes to increased competition requirements. [ABSTRACT FROM AUTHOR]

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.

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.

Remote sensing of life detection or a non-contact monitor of vital signals is an important application for Ultra-wideband (UWB) radar, such as health monitoring of a vehicle driver. Using the UWB radar to detect physiological signals of a dynamic human, three kind movement features (body motion, breathing, and heartbeat) must be considered generally to be extracted from echo pulses. Usually, moving body echo signal is much larger than other twos, which will cause signal interference and interaction problems. Meanwhile, since moving body causes breathing and heartbeat to act in dynamic spatial position, conventional fixed feature with maximum spectrum or local peak spectrum detection methods are not likely to find those movable physiological active features. Thus, how to reduce physiological feature bias from body motion, and efficiently obtain valuable physiological information are problems. To solve these problems, a novel multi-feature alignment (MFA) two-layer EEMD method is proposed. The proposed method simultaneously detects breathing and heartbeat information from a slightly swinging human (driver). The simulation and experiment results show the proposed method can effectively and reliably evaluate breathing and heart rates in static or/and dynamic body situation, both in laboratory and car. [ABSTRACT FROM AUTHOR]

Ultra-wideband (UWB) radar is an important remote sensing tool of life detection or a non-contact monitor of the vital signals. By processing the received UWB pulse echoes reflected from the body, different signals corresponding to heart activity and breathing, corrupted by body motion and the environment noise, are wanted to be separated clearly. However, the heartbeat signal is so tiny that it is covered by breathing harmonics and clutters. At the same time, since the frequencies of the vital signals are very close, usually around 1 Hz, it is difficult to apply an ordinary frequency filter to separate them apart. This problem induces that the vital signal detection method, usually, only detects the large breath signal, not the heartbeat signal. To solve this problem, a novel method is provided, in this paper, to extract the heartbeat and the breath information simultaneously. The method uses the feature time index with the first valley peak of the energy function of intrinsic mode functions (FVPIEF) calculated by pseudo bi-dimension ensemble empirical mode decomposition method and extracts the vital signals by the ensemble empirical mode decomposition (EEMD). Both simulation and experiment results evidently show that the proposed FVPIEF based two-layer EEMD method is effective for separating the small heartbeat signal from the large breath signal and significantly improves the evaluation of heart and breathing rates in both hold-breathing and breathing conditions. [ABSTRACT FROM AUTHOR]

Highlights • POF-embedded smart textile for breath and heart rates monitoring. • Analytical approach for the sensor operation principle. • Technique for detecting heart and breath rates even when the subject is moving. • Signal processing to mitigate the influence of gait frequency in the sensor response. Abstract In this paper, we present the development of a polymer optical fiber (POF) sensor for simultaneous measurement of breath (BR) and heart rates (HR). The sensor is embedded as a smart textile solution that can be used within the user’s clothes. In addition, a signal processing technique is proposed for obtaining the HR and BR without the influence of body movements and in different positions of the user’s chest. Sensor signal processing and analysis are made in the frequency domain and different filters are applied. Results show errors below 4 beats per minute and 2 breaths per minute for the HR and BR, respectively, even when the user is performing periodic body movements such as the ones induced by the gait. Thus, the proposed POF-based smart textile is a low-cost solution with good accuracy that can be readily applied in the remote monitoring of patients at home without disturbing their daily activities. [ABSTRACT FROM AUTHOR]

Continued developments of sensor technology including hardware miniaturization and increased sensitivity have enabled the development of less intrusive methods to monitor physiological parameters during daily life. In this work, we present methods to recover cardiac and respiratory parameters using accelerometer and gyroscope sensors on the wrist. We demonstrate accurate measurements in a controlled laboratory study where participants (n = 12) held three different positions (standing up, sitting down and lying down) under relaxed and aroused conditions. In particular, we show it is possible to achieve a mean absolute error of 1.27 beats per minute (STD: 3.37) for heart rate and 0.38 breaths per minute (STD: 1.19) for breathing rate when comparing performance with FDA-cleared sensors. Furthermore, we show comparable performance with a state-of-the-art wrist-worn heart rate monitor, and when monitoring heart rate of three individuals during two consecutive nights of in-situ sleep measurements.

We propose and demonstrate the feasibility of using a highly sensitive microbend multimode fiber optic sensor for simultaneous measurement of breathing rate (BR) and heart rate (HR). The sensing system consists of a transceiver, microbend multimode fiber, and a computer. The transceiver is comprised of an optical transmitter, an optical receiver, and circuits for data communication with the computer via Bluetooth. Comparative experiments conducted between the sensor and predicate commercial physiologic devices showed an accuracy of ±2 bpm for both BR and HR measurement. Our preliminary study of simultaneous measurement of BR and HR in a clinical trial conducted on 11 healthy subjects during magnetic resonance imaging (MRI) also showed very good agreement with measurements obtained from conventional MR-compatible devices. [ABSTRACT FROM AUTHOR]

Background Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. Methods We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Results Extracted data are compared with reference heart rates derived from a standard pulsephotoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min-1 (0.3 min-1) and -0.7 bpm (1.7 bpm) (compared to -0.2 min-1 (0.4 min-1) and 42.0 bpm (6.1 bpm) for the nonadaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. Conclusions It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals. [ABSTRACT FROM AUTHOR]

Introduction: A prospectively randomised, controlled animal study was conducted to analyse the influence of vagal injury on acute cardio-respiratory responses to blast injury. Materials and methods: We used a previously described model of blast-fragment combined injuries to divide dogs randomly into three groups: normal control, blast injury with fragment shot at the masseter and blast injury with fragment shot at the neck. The vagal histomorphologic changes were investigated by haematoxylin-eosin staining and immunocytochemical analysis of neuron-specific enolase and glial fibrillary acidic protein. The indices of respiration, heart rate, blood pressure and body temperature were recorded continuously before and after blast exposure. Results: The vagal injury was more severe in the neck-injured than in the face-injured group. However, bradycardia, hypotension and absence of compensatory peripheral vasoconstriction, which are typically seen in animals subjected to blast injury without vagal nerve injuries, were partly inhibited when the vagal nerve was injured. Conclusion: A vagally mediated reflex, such as a cardio-respiratory system defensive reflex that caused shock, was observed immediately after blast pressure wave injury. These observations may have important implications for the emergency management of blast injury cases. [ABSTRACT FROM AUTHOR]

Coping styles represent alternative response patterns in reaction to a stressor. The coping style model provides a set of predictions about correlations between behavioural and neurophysiological reactions to a stressful situation. According to this model, high levels of activity should be correlated with high levels of aggressiveness at the behavioural level, and to high sympathetic reactivity, low parasympathetic reactivity (higher heart rate levels) and low hypothalamus–pituitary–adrenocortical (HPA) axis reactivity (low production of glucocorticoids in response to a stressor). More recent versions of the model, however, are challenging this view and consider the possibility of independent axes of coping style and stress reactivity. The coping style model has mainly been tested on artificially selected or inbred lines in laboratory settings. Such a situation restricts its generalization to a larger number of species and there is a need for studies testing it in the wild under more natural situations. Here, we test the predictions of the coping style model in a wild alpine marmot, Marmota marmota, population. We show that several behavioural (i.e. exploration in an open field, impulsivity and docility) and neurophysiological traits (i.e. heart rate, breathing rate and cortisol production) assumed to represent individual differences in coping style were significantly repeatable over 2–3 years. Not all the correlations between traits predicted by the coping style model were found in marmots, which supports the more recent two-axes model. Furthermore, most correlations were observed at the between-individual level, and the within-individual correlations (i.e. phenotypic plasticity) were weaker. Overall, our results support the prediction of the coping style model, but highlight the fact that the association between traits found in artificial conditions may be weaker in a more natural setting. [ABSTRACT FROM AUTHOR]

Abstract: The study compares the physiological and behavioural responses to diurnal heat of South African indigenous Windsnyer (WS) pigs and imported Large White (LW) pigs in the hot-wet season in South Africa. Rectal temperature, skin surface temperature, breathing rates and heart rate were each recorded three times per day every other day (0800 h, 1200 h, 1600 h) for a period of 105 days in 12 six-week old gilts of each breed. A completely randomised design was used. There were no differences (P > 0.05) in breathing rate and rectal temperature between the pig breeds. Skin surface temperatures and heart rate were higher (P < 0.05) for the LW pigs than WS pigs at all times of the day. Time of the day affected (P < 0.05) all physiological parameters which generally increased to a peak during mid-day before decreasing at 1600 h. The frequency and duration of wallowing, sprawling in slurry and lying in prostrate posture were higher in LW than WS pigs. Indigenous WS pigs had higher (P < 0.05) values for hair length, final hair density and fat thickness than the LW pigs. These findings suggest that WS pigs could be better at thermoregulation than LW pigs. [Copyright &y& Elsevier]

Arousal from sleep is associated with transient and abrupt cardiorespiratory changes, and elevated arousals associated with sleep disorders may trigger adverse cardiovascular sequela. In this paper, we provide the first data in children on cardiorespiratory responses to cortical arousal. Heart rate and ventilatory responses to arousal from stage 2 and rapid eye movement (REM) sleep were investigated in 40 normal, healthy Caucasian children (age: 7.7 ± 2.6 years; body mass index z-score: 0.30 ± 0.8). All children underwent overnight polysomnography studies. Cortical arousals were scored according to standard criteria. Heart rate changes were assessed over 30 s, starting 15 s prior to cortical arousal onset. Breathing rates were quantified three breaths before and after arousal onset. Arousals from stage 2 as well as REM sleep resulted in an R–R interval shortening of about 15%, independent of age and gender. The R–R interval shortening initiated at least 3 s before the cortical arousal onset. The breathing interval immediately after cortical arousal onset was significantly shortened ( P < 0.001). In conclusion, cortical arousals in children are associated with an increase in breathing rate and significant heart rate accelerations, which typically precede the cortical arousal onset. [ABSTRACT FROM AUTHOR]

This study investigated the effect of psychological pressure on physiological responses during the golf putting stroke. Six young adults (four males and two females) participated in the study. The experiment was comprised of a contest that consisted of four sessions, with a dinner prize awarded to the winner. In each session, the subject was instructed to attempt 20, 9-foot putts. Eye, head, and putter motions, as well as heart rate and breathing rate, were objectively recorded during each trial. For all sessions, each successful putt was awarded a score of +2 points. However, as the four sessions progressed, any missed putt was given progressively greater negative scores: -2, -3, -4, and -5 points, respectively. At the end of the experiment, the subject rated the perceived pressure during each session on a scale of 1 to 5, with 1 corresponding to no pressure and 5 corresponding to extreme pressure. Overall, the results demonstrated that the apparently simple act of putting involves a complex interplay among various physiological and neurological control parameters, hence reflecting a myriad of emotions that are magnified under increased psychological pressure. [ABSTRACT FROM AUTHOR]

This paper deals with the assumption that young adults with self-reported multiple chemical sensitivity (sMCS) show a heightened sensitivity of autonomic functions during experimental solvent exposure. Male sMCS-subjects were selected (out of n=274) on the base of a German questionnaire on chemical and environmental sensitivity (CGES). Two independent experiments were carried out, each with 12 sMCS-subjects and 12 age-matched control-subjects. In experiment I two concentrations of the solvents ethyl benzene (10 and 98 ppm) and 2-butanone (10 and 189 ppm) were used. Experiment II investigated 2-propanol (35 and 190 ppm) and 1-octanol (0.1 and 6.4 ppm). The low concentrations correspond nearly to the olfactory thresholds while the high concentrations correspond to the German occupational threshold limit values (MAC). The exposure duration under each condition was 4 h. The sequence of the four exposure conditions was random including intervals of at least 2 days without exposure. During the exposure physiological changes of breathing rate and heart rate were recorded. Two 30 min intervals with a sedentary position of the subjects at the beginning and end of exposure were chosen for analyses. Neither in experiment I nor in experiment II significant specific reactions to the type or level of the exposures were found. The autonomic functions in both experiments revealed alterations within the exposure sessions. The heart rate in experiment II and the breathing rate in both experiments decreased significantly during the analyzed 30 min intervals. Furthermore, in both experiments the heart rates decreased significantly from beginning to end of exposure. Only in experiment I the mean breathing rate of sMCS-subjects was generally higher compared to the control-subjects. Regarding the assumption of a heightened sensitivity of sMCS-subjects the two experiments yielded controversial results. Thus, the hypothesis of stronger responses of autonomic functions of sMCS-subjects provoked by various exposure scenarios remains open. [Copyright &y& Elsevier]

The effects of breathing on heart rate and heart rate variability were assessed in 6-, 8-, and ]0-year-old boys. Rate of breathing affected only heart rate variability, with faster breathing producing more stable heart rate. Replicating previous findings with adults, depth of breathing affected both heart rate and heart rate variability, with deep breathing producing the fastest, most variable heart rate. The absolute effects of the respiratory manipulations on heart rate variability were found to be greater for children than for adults, and there was also a developmental trend of both decreasing heart rate and variability. Implications of these findings for developmental studies using heart rate as a dependent measure are discussed. [ABSTRACT FROM AUTHOR]

Effects of depth and rate of breathing on heart rate (HR) and HR variability were observed in two experiments. Respiration rate (RR) affected only cardiac stability, faster breathing producing more stable cardiac rate. Respiration depth (RD) affected both HR level and variability. Deep breathing produced faster, more variable HR, while shallow breathing had the opposite effects. A third experiment, in which Ss were trained to control HR using respiration, further illustrated the dramatic effects of respiration on cardiac rate. Implications of these results for experiments utilizing HR as a dependent variable and studies of autonomic control were discussed. [ABSTRACT FROM AUTHOR]