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Introduction: In all Neonatal Resuscitation Program (NRP) scenarios, Heart Rate (HR) counting is essential to assess the response to resuscitation. Undue delay in initiating Positive Pressure Ventilation (PPV) due to the time taken in HR counting may increase the risk of hypoxic injury and infant mortality. Aim: To observe whether omitting the HR counting step in the First Golden Minute (FGM) and early initiation of PPV affects outcomes. Materials and Methods: The present Randomised Controlled Trial (RCT) was conducted in the Special Newborn Care Unit (SNCU), GSVM Medical College, Kanpur, Uttar Pradesh, India, from September 2020 to March 2022. A total of 67 newborns were included, with 34 in the control group (group 1) and 33 in the intervention group (group 2). In the control group, neonatal resuscitation was performed according to Facility-based Newborn Care (FBNC) guidelines, while in the intervention group, only the HR counting step was omitted from the FGM. Both groups of newborns were assessed for outcomes including normal baby, baby developing Hypoxic Ischaemic Encephalopathy (HIE) stage I, II and III, and death. Data was compiled and analysed using percentages for categorical variables. Continuous variables were analysed using mean and standard deviation of Z score and Student’s t-test. A p-value less than 0.05 was considered statistically significant. Results: The mean gestational age was 38.3±5.8 weeks in group 1 and 37.9±6.1 weeks in group 2. Gender distribution was almost equal, with 19 (56%) female newborns in group 1 and 17 (52%) female newborns in group 2. The mean total time from birth to the end of PPV (in seconds) was significantly lower in group 2 (63.47±7.09) compared to group 1 (78.18±8.36), with a p-value of

Nowadays, many people are forced to accelerate their rhythms because of frenetic life and work. Both private and professional lives intertwine, and finding the time for other activities is challenging. Time is one of the goods that has been lost or is difficult to obtain anyway. This experimental and prospective study aims to evaluate the heart rate cycle of medical doctors during their life/work routine. Thanks to technology, it is possible to monitor these parameters constantly. The results of this study are derived from a literature analysis and a trial carried out on three professionals regarding their work-related heart rate (Apple Watch®). The main limitation is represented by the sample; it is certainly small and does not provide significant results. This study represents the first step for a trial that can be carried out on a large scale; this preliminary study provides information about the heart rate cycle. [ABSTRACT FROM AUTHOR]

Objective: Myocardial infarction (MI) results in mental health consequences, including depression and post-traumatic stress disorder (PTSD). The risk and protective factors of such mental consequences are not fully understood. This study examined the relation between MI severity and future mental health consequences and the moderating role of vagal nerve activity. Methods: In a reanalysis of data from the Myocardial Infarction-Stress Prevention Intervention (MI-SPRINT) study, 154 post-MI patients participated. MI severity was measured by the Killip Scale and by troponin levels. Depression and PTSD symptoms were assessed with valid questionnaires, both at 3 and 12 months. Vagal nerve activity was indexed by the heart rate variability (HRV) parameter of the root-mean square of successive R-R differences (RMSSD). Following multivariate analyses, the association between MI severity and distress was examined in patients with low and high HRV (RMSSD = 30 ms). Results: In the full sample, the Killip index predicted post-MI distress only at 3 months, while troponin predicted distress at 3- and 12-months post-MI. However, HRV moderated the effects of the Killip classification; Killip significantly predicted symptoms of depression and PTSD at 3- and 12-months post-MI, but only in patients with low HRV. Such moderation was absent for troponin. Conclusion: MI severity (Killip classification) predicted post-MI depression and PTSD symptoms, but only in patients with low HRV, suggesting that the vagal nerve is a partial protective (moderating) factor in the relation between Killip score and post-MI distress. [ABSTRACT FROM AUTHOR]

Copyright of Enfermería en Cardiologia is the property of Asociacion Espanola de Enfermeria en Cardiologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Foundation: the recovery heart rate in physical efforts is a relevant indicator for health and sports professionals. Objective: to relate the acute recovery of the heart rate in a submaximal functional fitness session with the maximum oxygen consumption in physically active subjects. Methods: descriptive study with a quantitative approach with a convenience sample made up of 14 men (age 21.32±4.36 years; body mass 71.42±14.68 kg; height 1.75±0.17 m; BMI 23 01±3.61 kg/m2) and 5 women (age 22.81±3.48 years; body mass 65.82±8.45 kg; height 1.56±0.21 m; BMI 21.54± 1.35 kg/m2), they performed a maximal and incremental cardiorespiratory test (Course-Navette) and the WOD Pukie (150 burpees in the shortest possible time) on two days separated by 48 hours. Maximum heart rate, session heart rate, and recovery heart rate (1, 2, and 3 minutes) were recorded. The Shapiro-Wilk normality test and the Pearson correlation coefficient (95% confidence and a p-value of 0.05) were applied. Results: the maximum oxygen consumption was not significantly related in men (p>0.05), in the case of women it was positive with the recovery heart rate in all periods, but with significance in 1 minute (r = 0 .81; p<0.05) and 3 minutes (r = 0.93; p<0.01). Conclusions: maximal oxygen consumption was positively and significantly related to recovery heart rate in a functional fitness session in physically active women. [ABSTRACT FROM AUTHOR]

Wrist-worn devices are popular for heart rate monitoring, including use of photoplethysmography. The Apple Watch series 4 can identify atrial fibrillation. We describe a case of identification re-entrant supraventricular tachycardia not identified by outpatient rhythm monitoring, however, was identified by the Apple Watch series 4, which lead to electrophysiology study and successful ablation of atrioventricular nodal re-entrant tachycardia.

Atrial fibrillation (AF) is a major cause of morbidity and mortality globally, and much of this is driven by challenges in its timely diagnosis and treatment. Existing and emerging mobile technologies have been used to successfully identify AF in a variety of clinical and community settings, and while these technologies offer great promise for revolutionizing AF detection and screening, several major barriers may impede their effectiveness. The unclear clinical significance of device-detected AF, potential challenges in integrating patient-generated data into existing healthcare systems and clinical workflows, harm resulting from potential false positives, and identifying the appropriate scope of population-based screening efforts are all potential concerns that warrant further investigation. It is crucial for stakeholders such as healthcare providers, researchers, funding agencies, insurers, and engineers to actively work together in fulfilling the tremendous potential of mobile technologies to improve AF identification and management on a population level.

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should therefore be a key component of the biologist's toolkit. But, classic chaos-detection tools are highly sensitive to measurement noise and break down for common edge cases, making it difficult to detect chaos in domains, like biology, where measurements are noisy. However, newer tools promise to overcome these limitations. Here, we combine several such tools into an automated processing pipeline, and show that our pipeline can detect the presence (or absence) of chaos in noisy recordings, even for difficult edge cases. As a first-pass application of our pipeline, we show that heart rate variability is not chaotic as some have proposed, and instead reflects a stochastic process in both health and disease. Our tool is easy-to-use and freely available.

Nowadays, many people are forced to accelerate their rhythms because of frenetic life and work. Both private and professional lives intertwine, and finding the time for other activities is challenging. Time is one of the goods that has been lost or is difficult to obtain anyway. This experimental and prospective study aims to evaluate the heart rate cycle of medical doctors during their life/work routine. Thanks to technology, it is possible to monitor these parameters constantly. The results of this study are derived from a literature analysis and a trial carried out on three professionals regarding their work-related heart rate (Apple Watch®). The main limitation is represented by the sample; it is certainly small and does not provide significant results. This study represents the first step for a trial that can be carried out on a large scale; this preliminary study provides information about the heart rate cycle.

Objective: Myocardial infarction (MI) results in mental health consequences, including depression and post-traumatic stress disorder (PTSD). The risk and protective factors of such mental consequences are not fully understood. This study examined the relation between MI severity and future mental health consequences and the moderating role of vagal nerve activity. Methods: In a reanalysis of data from the Myocardial Infarction-Stress Prevention Intervention (MI-SPRINT) study, 154 post-MI patients participated. MI severity was measured by the Killip Scale and by troponin levels. Depression and PTSD symptoms were assessed with valid questionnaires, both at 3 and 12 months. Vagal nerve activity was indexed by the heart rate variability (HRV) parameter of the root-mean square of successive R-R differences (RMSSD). Following multivariate analyses, the association between MI severity and distress was examined in patients with low and high HRV (RMSSD = 30 ms). Results: In the full sample, the Killip index predicted post-MI distress only at 3 months, while troponin predicted distress at 3- and 12-months post-MI. However, HRV moderated the effects of the Killip classification; Killip significantly predicted symptoms of depression and PTSD at 3- and 12-months post-MI, but only in patients with low HRV. Such moderation was absent for troponin. Conclusion: MI severity (Killip classification) predicted post-MI depression and PTSD symptoms, but only in patients with low HRV, suggesting that the vagal nerve is a partial protective (moderating) factor in the relation between Killip score and post-MI distress.

Several unobtrusive sensors have been tested in studies to capture physiological reactions to stress in workplace settings. Lab studies tend to focus on assessing sensors during a specific computer task, while in situ studies tend to offer a generalized view of sensors' efficacy for workplace stress monitoring, without discriminating different tasks. Given the variation in workplace computer activities, this study investigates the efficacy of unobtrusive sensors for stress measurement across a variety of tasks. We present a comparison of five physiological measurements obtained in a lab experiment, where participants completed six different computer tasks, while we measured their stress levels using a chest-band (ECG, respiration), a wristband (PPG and EDA), and an emerging thermal imaging method (perinasal perspiration). We found that thermal imaging can detect increased stress for most participants across all tasks, while wrist and chest sensors were less generalizable across tasks and participants. We summarize the costs and benefits of each sensor stream, and show how some computer use scenarios present usability and reliability challenges for stress monitoring with certain physiological sensors. We provide recommendations for researchers and system builders for measuring stress with physiological sensors during workplace computer use.

BackgroundModerate-vigorous physical activity (MVPA) offers extensive health benefits but is neglected by many. As a result, a wide body of research investigating physical activity behavior change has been conducted. As many of these studies transition from paper-based methods of MVPA data collection to fitness trackers, a series of challenges arise in extracting insights from these new data.ObjectiveThe objective of this research was to develop a framework for preprocessing and extracting MVPA trends from wearable fitness tracker data to support MVPA behavior change studies.MethodsUsing heart rate data collected from fitness trackers, we propose Physical Activity Trend eXtraction (PATX), a framework that imputes missing data, recalculates personalized target heart zones, and extracts MVPA trends. We tested our framework on a dataset of 123 college study participants observed across 2 academic years (18 months) using Fitbit Charge HRs. To demonstrate the value of our frameworks' output in supporting MVPA behavior change studies, we applied it to 2 case studies.ResultsAmong the 123 participants analyzed, PATX labeled 41 participants as experiencing a significant increase in MVPA and 44 participants who experienced a significant decrease in MVPA, with significance defined as P

Abstract Objective: The aim of this study was to analyze which equation best estimates maximal heart rate (HRmax) for the pediatric population according to body mass. Data source: We performed a meta-analysis (PROSPERO No. CRD42020190196) of cross-sectional studies that aimed to validate or develop HRmax equations and that had children and adolescents as samples. The search was conducted in Scopus, Science Direct, Web of Science, PubMed, and Biblioteca Virtual em Saúde with the descriptors “prediction or equation,” “maximal heart rate,” “maximum heart rate,” “determination of heart rate,” children, and adolescent. The TRIPOD Statement tool was used to assess the methodological quality and the relevant data were extracted for analysis. The meta-analysis was conducted in the Comprehensive Meta-Analysis, adopting p

Objective: The aim of this study was to analyze which equation best estimates maximal heart rate (HRmax) for the pediatric population according to body mass. Data source: We performed a meta-analysis (PROSPERO No. CRD42020190196) of cross-sectional studies that aimed to validate or develop HRmax equations and that had children and adolescents as samples. The search was conducted in Scopus, Science Direct, Web of Science, PubMed, and Biblioteca Virtual em Saúde with the descriptors “prediction or equation,” “maximal heart rate,” “maximum heart rate,” “determination of heart rate,” children, and adolescent. The TRIPOD Statement tool was used to assess the methodological quality and the relevant data were extracted for analysis. The meta-analysis was conducted in the Comprehensive Meta- Analysis, adopting p<0.05 and a 95% confidence interval (CI). Data synthesis: In total, 11 studies were selected, of which 3 developed predictive equations, 10 performed external validity of the preexisting models, and 1 incremented values related to equations already developed. The results of the methodological quality analysis showed a moderate rating in most studies. The 164 + (0.270 x HRres) – (0.155 x body mass) + (1.1 x METs) + (0.258 x body fat percent) (r=0.500, 95%CI 0.426–0.567, p<0.001) and 166.7+ (0.46 x HRres) + (1.16 x maturation) (r=0.540, 95%CI 0.313–0.708, p<0.001) equations presented stronger correlations with measured HRmax in nonobese adolescents. The predictive model developed by 208 – (0.7 x age) showed a greater accuracy among the possible models for analysis (SDM=-0.183, 95%CI -0.787 to -0.422, p=0.554). No specific predictive equation was found for obese adolescents. Conclusions: Future research should explore new possibilities for developing predictive equations for this population as a tool to control exercise intensity in the therapeutic management of childhood and adolescent obesity. [ABSTRACT FROM AUTHOR]

Backgroung: The literature provides support for several different method by which it is possible to quantify, prescribe and control the aerobic workload. Objective: To compare physiological and the affective response among training methods prescribed by VO2 reserve, HR reserve, and rating of perceived exertion (RPE) selfadjusted. Methods: 27 participants were submitted to two trail sessions. In the 1st, a maximum treadmill effort test was performed to determine the VO2max. In the 2nd, the participants were randomly divided into 3 situations of 5 min, with 5 min interval among the situations. In situation 1 (C1), the participants ran at the velocity correspondent to 65% of the VO2 reserve; in situation 2 (C2), participants ran at 60% to 65% of HR reserve and in situation 3 (C3), the participants selfadjustment the velocity by a RPE scale, in a moderate effort (RPE 3-4). The level of body activation and the affective response were obtained pre and post-stimulus administered. An ANOVA was performed and the magnitude of the differences established, with a significance level of p ≤ 0.05. Results: There were no significant differences for velocity in the three situations (p = 0.458). The responses of HR induced by C1 and C3 were significantly higher vs. C2 (p = 0.027 and p = 0.043). The RPE did not show significant differences among the situations (p = 0.118). Finally, the level of activation and sensation perceived activity did not differ significantly (p = 0.168). Conclusion: It was concluded that the exercise responses from the HR reserve were significantly lower when compared to the VO2reserve and RPE. All prescription models provided similar affective responses. [ABSTRACT FROM AUTHOR]

Vital signs are critical in assessing the severity and prognosis of infections, for example, COVID-19, influenza, sepsis, and pneumonia. This study aimed to evaluate a new method for rapid camera-based non-contact measurement of heart rate, blood oxygen saturation, respiratory rate, and blood pressure. Consecutive adult patients attending a hospital emergency department for suspected COVID-19 infection were invited to participate. Vital signs measured with a new camera-based method were compared to the corresponding standard reference methods. The camera device observed the patient's face for 30 s from ∼1 m. Between 1 April and 1 October 2020, 214 subjects were included in the trial, 131 female (61%) and 83 male (39%). The mean age was 44 years (range 18–81 years). The new camera-based device's vital signs measurements were, on average, very close to the gold standard but the random variation was larger than the reference methods. The principle of contactless measurement of blood pressure, pulse, respiratory rate, and oxygen saturation works, which is very promising. However, technical improvements to the equipment used in this study to reduce its random variability is required before clinical implementation. This will likely be a game changer once this is sorted out. Universal Trial Number (UTN) U1111-1251-4114 and the ClinicalTrials.gov Identifier NCT04383457. [ABSTRACT FROM AUTHOR]

ABSTRACT Stroke is one of the leading causes of mortality and disability worldwide. Autonomic dysfunction after ischemic stroke is frequently associated with cardiac complications and high mortality. The brain-heart axis is a good model for understanding autonomic interaction between the autonomic central network and the cardiovascular system. Heart rate variability (HRV) analysis is a non-invasive approach for understanding cardiac autonomic regulation. In stroke patients, HRV parameters are altered in the acute and chronic stages of the disease, having a prognostic value. In this literature review we summarize the main concepts about the autonomic nervous system and HRV as autonomic biomarkers in ischemic stroke.

Background: High blood pressure (BP) is a major risk factor for cardiovascular disease (CVD). Consumption of dark chocolate, which is high in flavonoids that may reduce CVD risk, is an attractive intervention to reduce to BP. Additionally, the use of mobile health (mHealth) technologies (eg, telehealth, smartphones, and wearable devices) can improve outcomes in patients with CVD. Objective: The purpose of this study was to investigate the impact of dark chocolate intake on BP, subject use of mHealth, and integration of mHealth into a clinical trial. Methods: The COCOA-BP (ChOcolate COnsumption And Blood Pressure) study was a prospective, single-center, pre-/postintervention study that enrolled 62 healthy volunteers. The study consisted of 3 phases: smartwatch/smart BP monitor familiarization and washout from chocolate (week 1); control (week 2); and intervention (weeks 3 and 4). During the intervention phase, subjects consumed 50 g of dark chocolate per day. The primary endpoint was change in resting systolic BP between the intervention and control phases. Additional endpoints included device accuracy and correlation with physical activity. Results: Mean resting systolic BP was 116.4 mm Hg before chocolate intake among 62 participants (mean age 37 years; 61% female). After chocolate intake, mean resting systolic BP was 116.0 mm Hg (difference –0.4; P = .69). These findings suggest that 2 weeks of dark chocolate intake did not reduce resting systolic BP. There was poor agreement between mHealth device and standard (nurse-performed) measurements. Conclusion: In this study, short-term dark chocolate intake did not seem to reduce BP. mHealth technology shows great potential for use in clinical studies, but challenges related to device accuracy and compliance need to be addressed.

Introduction: In clinical practice, fetal heart rate monitoring is performed intermittently using Doppler ultrasound, typically for 30 minutes. In case of a non-reassuring heart rate pattern, monitoring is usually prolonged. Noninvasive fetal electrocardiography may be more suitable for prolonged monitoring due to improved patient comfort and signal quality. This study evaluates the performance and patient experience of four noninvasive electrocardiography devices to assess candidate devices for prolonged noninvasive fetal heart rate monitoring., Material and Methods: Non-critically sick women with a singleton pregnancy from 24 weeks of gestation were eligible for inclusion. Fetal heart rate monitoring was performed during standard care with a Doppler ultrasound device (Philips Avalon-FM30) alone or with this Doppler ultrasound device simultaneously with one of four noninvasive electrocardiography devices (Nemo Fetal Monitoring System, Philips Avalon-Beltless, Demcon Dipha-16 and Dräger Infinity-M300). Performance was evaluated by: success rate, positive percent agreement, bias, 95% limits of agreement, regression line, root mean square error and visual agreement using FIGO guidelines. Patient experience was captured using a self-made questionnaire., Results: A total of 10 women were included per device. For fetal heart rate, Nemo performed best (success rate: 99.4%, positive percent agreement: 94.2%, root mean square error 5.1 BPM, bias: 0.5 BPM, 95% limits of agreement: -9.7 - 10.7 BPM, regression line: y = -0.1x + 11.1) and the cardiotocography tracings obtained simultaneously by Nemo and Avalon-FM30 received the same FIGO classification. Comparable results were found with the Avalon-Beltless from 36 weeks of gestation, whereas the Dipha-16 and Infinity-M300 performed significantly worse. The Avalon-Beltless, Nemo and Infinity-M300 closely matched the performance of the Avalon-FM30 for maternal heart rate, whereas the performance of the Dipha-16 deviated more. Patient experience scores were higher for the noninvasive electrocardiography devices., Conclusions: Both Nemo and Avalon-Beltless are suitable devices for (prolonged) noninvasive fetal heart rate monitoring, taking their intended use into account. But outside its intended use limit of 36 weeks' gestation, the Avalon-Beltless performs less well, comparable to the Dipha-16 and Infinity-M300, making them currently unsuitable for (prolonged) noninvasive fetal heart rate monitoring. Noninvasive electrocardiography devices appear to be preferred due to greater comfort and mobility., (© 2024 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)

Abstract Aim: Spinal cord injury (SCI) is associated with changes in cardiac autonomic control, that can be evaluated by heart rate variability (HRV), for which the electrocardiogram (ECG) is the gold standard. However, the use of ECG is limited to laboratory environments, and new tools are needed for this purpose and that can be applied in the routine monitoring of individuals with SCI. The present study aimed to investigate the validity of the Polar V800 heart rate monitor in assessing the cardiac autonomic control of individuals with SCI. Methods: Nineteen adult men with SCI (paraplegia n = 10; 44.5 ± 8.5 years and tetraplegia n = 9; 34.4 ± 7.5 years) participated in this cross-sectional study. The participants remained in the sitting position at rest for 10 min for the acquisition of the ECG and Polar V800 signals. The last 5-min window was used to count the beat-by-beat R-R interval series and then calculate the HRV indices (linear methods in the time and frequency domains). The study subgroups were compared, and the validity of the measurements generated with a heart rate monitor was determined using the intraclass correlation coefficient (ICC2,1) and Bland-Altman graphs. Results: Agreement analyses for the R-R intervals, SDNN, rMSSD, PNN50, SD1, LF, HF, and LF: HF ratio tended to show reliability ranging from acceptable to excellent (ICC = 0.579-0.990; P = 0.043-0.001) and acceptably narrow limits of agreement within both the group with tetraplegia and the group with paraplegia. Conclusion: The Polar V800 heart rate monitor is a valid instrument for assessing HRV in individuals with paraplegia and tetraplegia.

Heart rate variability (HRV) is an important physiological measure of the capacity for neurogenic homeostatic regulation, and an indirect measure of emotional processing. We aimed to investigate whether HRV parameters are altered in people with chronic low back pain when compared to healthy controls. We searched on PubMed, Scopus, CINAHL, Web of Science, Cochrane Library, and PsycINFO from inception to January 2018. The inclusion criteria were: patients with non-specific chronic low back pain, absence of radiculopathy, age from 18 to 65 years, and comparison with healthy controls. Data extraction was performed by two independent review authors. The methodological quality of the studies was assessed using the appraisal tool for cross-sectional studies. After screening 2,873 potential articles, two studies met the inclusion criteria. Studies were composed of 153 patients with chronic low back pain and 62 healthy controls. An electrocardiogram was used to record HRV and linear methods (time and frequency) were used to analyze the results. The main findings indicate that patients with chronic low back pain have a significant reduction in HRV, with sympathetic predominance compared to healthy controls. There is limited evidence suggesting that chronic low back pain patients presented a lower vagal activity evidenced by HRV, when compared to healthy controls. The results of this systematic review should be interpreted with caution due to the restricted number of included studies, small sample sizes and different protocols used to measure HRV. The limited evidence about HRV alterations in low back pain also suggests the need of future studies to investigate if HRV parameters can be a useful measure in chronic pain samples or even if it can be used as an outcome in clinical trials aiming to investigate the effectiveness of interventions based on emotion regulation. [ABSTRACT FROM AUTHOR]

Objective: the aim of this study was to verify the reproducibility index of the frequency meter with GPS technology with recording speed of 1Hz in acyclic displacement and intermittent intensity, performed by soccer referees. Materials and methods: it was characterized by a field study with a quantitative trait involving 14 men, aged 20.42 ± 2.78 years, from a barracks in the city of Rio de Janeiro. Polar heart rate monitor with 1Hz GPS model V800 was used. The protocol used was adapted from the FIFA test protocol for soccer referees, so that 10 “shots” of 75m in 15s were accomplished by 25m in 20 of recovery. Testing and retest were applied with 7 days interval and identical protocols: heating, ambiance (4 “shots” following the model of the protocol above) and then the test. Since the circuit covered in the test protocol was 1000 m. Results: a mean of 1002.5 ± 17.12 m was obtained in the test and in the test 1010.83 ± 32.88 m, the coefficients of variation were respectively 1% and 3%. The difference was not significant between the test and the retest (P-value> 0.05), and the intraclass correlation coefficient indicated a moderate association between the measures. Conclusion: therefore, it is suggested that it is acceptable to use a frequency gauge with a recording speed of 1Hz to monitor displacements of soccer referees in acyclic displacement and intermittent intensity. [ABSTRACT FROM AUTHOR]

The potential of microwave Doppler radar in non-contact vital sign detection is significant; however, prevailing radar-based heart rate (HR) and heart rate variability (HRV) monitoring technologies often necessitate data lengths surpassing 10 s, leading to increased detection latency and inaccurate HRV estimates. To address this problem, this paper introduces a novel network integrating a frequency representation module and a residual in residual module for the precise estimation and tracking of HR from concise time series, followed by HRV monitoring. The network adeptly transforms radar signals from the time domain to the frequency domain, yielding high-resolution spectrum representation within specified frequency intervals. This significantly reduces latency and improves HRV estimation accuracy by using data that are only 4 s in length. This study uses simulation data, Frequency-Modulated Continuous-Wave radar-measured data, and Continuous-Wave radar data to validate the model. Experimental results show that despite the shortened data length, the average heart rate measurement accuracy of the algorithm remains above 95% with no loss of estimation accuracy. This study contributes an efficient heart rate variability estimation algorithm to the domain of non-contact vital sign detection, offering significant practical application value.

Objective . Although inter-beat intervals (IBI) and the derived heart rate variability (HRV) can be acquired through consumer-grade photoplethysmography (PPG) wristbands and have been applied in a variety of physiological and psychophysiological conditions, their accuracy is still unsatisfactory. Approach. In this study, 30 healthy participants concurrently wore two wristbands (E4 and Honor 5) and a gold-standard electrocardiogram (ECG) device under four conditions: resting, deep breathing with a frequency of 0.17 Hz and 0.1 Hz, and mental stress tasks. To quantitatively validate the accuracy of IBI acquired from PPG wristbands, this study proposed to apply an information-based similarity (IBS) approach to quantify the pattern similarity of the underlying dynamical temporal structures embedded in IBI time series simultaneously recorded using PPG wristbands and the ECG system. The occurrence frequency of basic patterns and their rankings were analyzed to calculate the IBS distance from gold-standard IBI, and to further calculate the signal-to-noise ratio (SNR) of the wristband IBI time series. Main results. The accuracies of both HRV and mental state classification were not satisfactory due to the low SNR in the wristband IBI. However, by rejecting data segments of SNR < 25, the Pearson correlation coefficients between the wristbands' HRV and the gold-standard HRV were increased from 0.542 ± 0.235 to 0.922 ± 0.120 for E4 and from 0.596 ± 0.227 to 0.859 ± 0.145 for Honor 5. The average accuracy of four-class mental state classification increased from 77.3% to 81.9% for E4 and from 79.3% to 83.3% for Honor 5. Significance. Consumer-grade PPG wristbands are acceptable for HR and HRV monitoring when removing low SNR segments. The proposed method can be applied for quantifying the accuracies of IBI and HRV indices acquired via any non-ECG system., (© 2024 Institute of Physics and Engineering in Medicine.)

Introduction: Perinatal asphyxia, a condition that results from compromised placental or pulmonary gas exchange during the birth process, is rare but can lead to serious neonatal and long-term consequences. The visual analysis of cardiotocography (CTG) is designed to avoid perinatal asphyxia, but its interpretation can be difficult. Our aim was to test the impact of an e-learning training program for interpreting CTG on the rate of avoidable perinatal asphyxia at term., Method: We conducted a retrospective multicenter before-after study comparing two periods, before and after the implementation of e-learning training program from July 1, 2016 to December 31, 2016, in CTG interpretation for midwives and obstetricians in five maternity hospitals in the Paris area, France. The training involved theoretical aspects such as fetal physiology and heart rhythm abnormalities, followed by practical exercises using real case studies to enhance skills in interpreting CTG. We included all term births that occurred between the "before" period (July 1 to December 31, 2014) and the "after period (January 1 to June 30, 2017). We excluded multiple pregnancies, antenatal detection of congenital abnormalities, breech births and all scheduled caesarean sections. Perinatal asphyxia cases were analyzed by a pair of experts consisting of midwives and obstetricians, and avoidability of perinatal asphyxia was estimated. The main criterion was the prevalence of avoidable perinatal asphyxia., Results: The e-learning program was performed by 83 % of the obstetrician-gynecologists and 65 % of the midwives working in the delivery rooms of the five centers. The prevalence of perinatal asphyxia was 0.45 % (29/7902 births) before the training and 0.54 % (35/7722) after. The rate of perinatal asphyxia rated as avoidable was 0.30 % of live births before the training and 0.28 % after (p = 0.870). The main causes of perinatal asphyxia deemed avoidable were delay in reactions to severe CTG anomalies and errors in the analysis and interpretation of the CTG. These causes did not differ between the two periods., Conclusion: One session of e-learning training to analyze CTG was not associated with a reduction in avoidable perinatal asphyxia. Other types of e-learning, repeated and implemented over a longer period should be evaluated., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024. Published by Elsevier Masson SAS.)

Monitoring the fetal heartbeat underpins assessment of fetal wellbeing in labour. Although commonly employed in clinical practice, shortcomings remain. A recent review of clinical practice guidelines highlights the variation in definitions of the fetal heart rate that will lead to differences in interpretation. Will intrapartum care be improved by greater consensus around clinical practice guidelines through rationalisation or refinement of guidelines, or will the future see this technique replaced by more accurate forms of fetal monitoring?, (© 2023 Royal Australian and New Zealand College of Obstetricians and Gynaecologists.)

Copyright of Arquivos de Neuro-Psiquiatria is the property of Thieme Medical Publishing Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite the prophylactic medicine achievements through the past decade, tobacco smoking remains one of the main risk factors of appearance and progression of diseases, which are accompanied by the high population mortality. Aim: development of the new approaches of complications prediction, prophylaxis and treatment in patients with high and very high total cardiovascular risk, which are based on the heart rhythm turbulence evaluation. Materials and Methods: 603 patients were chosen for the research. All patients were divided into tree groups. The first – patients with IHD without concomitant risk factors, such as smoking, obesity, metabolic syndrome. The second – patients, who smoke for more than 2 years (people with very high cardiovascular risk by SCORE scale). The third group – patients with metabolic syndrome without IHD or hypertension (patients with high cardiovascular risk). Control group included 149 patients. Holter monitoring of the heart rhythm was performed in patients with high and very high cardiovascular risk by the SCORE scale with myocardial infarction to study the specifications of the heart rhythm turbulence. Plasma calcium and magnesium levels were measured to establish the correlation between appearance and progression of ventricular arrhythmia and increase of the heart rhythm turbulence phenomenon. Results. The prevalence of ventricular and supraventricular arrhythmia is reliably higher among the smokers than among healthy persons. The highest percentage of the ventricular extrasystoles both the early appearing extrasystoles and the group extrasystoles is observed among smokers. Among healthy people every fourth person has deviations in heart rhythm turbulence indices, and every seventeenth has significant deviations and high risk of cardiac sudden death. Smokers have reliable decrease of calcium and increase of magnesium plasma levels. People with heart rhythm turbulence, metabolic syndrome and hypertension have reliable increased in calcium plasma concentration compared with people with metabolic syndrome but without hypertension. Conclusions. 1) Smoking contributes to increase the polytopic extrasystoles prevalence. 2) Smokers have higher acceleration and deceleration levels of the heart rhythm turbulence. 3) Changes of calcium and magnesium plasma levels in smokers do not cause the ventricular extrasystole. 4) Studying of the heart rhythm turbulence is available marker of fatal arrhythmias occurrence predicting.

Commercial photoplethysmography (PPG) sensors rely on the measurement of continuous-wave diffuse reflection signals (CW-DRS) to monitor heart rate. Using Monte Carlo modeling of light propagation in skin, we quantitatively evaluate the dependence of continuous-wave photoplethysmography (CW-PPG) in commercial wearables on source-detector distance (SDD). Specifically, when SDD increases from 0.5 mm to 3.3 mm, CW-PPG signal increases by roughly 846% for non-obese (NOB) skin and roughly 683% for morbidly obese (MOB) skin. Ultimately, we introduce the concept of time-of-flight PPG (TOF-PPG) which can significantly improve heart rate signals. Our model shows that the optimized TOF-PPG improves heart rate monitoring experiences by roughly 47.9% in NOB and 93.2% in MOB when SDD = 3.3 mm is at green light. Moving forward, these results will provide a valuable source for hypothesis generation in the scientific community to improve heart rate monitoring.

Heart rate is a key vital sign that can be used to understand an individual's health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system's accuracy in sensing two users' heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity.

Heart rate variability (HRV) is a measurement of the fluctuation of time between each heartbeat and reflects the function of the autonomic nervous system. HRV is an important indicator for both physical and mental status and for broad-scope diseases. In this review, we discuss how wearable devices can be used to monitor HRV, and we compare the HRV monitoring function among different devices. In addition, we have reviewed the recent progress in HRV tracking with wearable devices and its value in health monitoring and disease diagnosis. Although many challenges remain, we believe HRV tracking with wearable devices is a promising tool that can be used to improve personal health.

Previous studies have shown a correlation between resting heart rate (HR) measured by wearable devices and serum free thyroxine concentration in patients with thyroid dysfunction. We have developed a machine learning (ML)-assisted system that uses HR data collected from wearable devices to predict the occurrence of thyrotoxicosis in patients. HR monitoring data were collected using a wearable device for a period of 4 months in 175 patients with thyroid dysfunction. During this period, 3 or 4 thyroid function tests (TFTs) were performed on each patient at intervals of at least one month. The HR data collected during the 10 days prior to each TFT were paired with the corresponding TFT results, resulting in a total of 662 pairs of data. Our ML-assisted system predicted thyrotoxicosis of a patient at a given time point based on HR data and their HR-TFT data pair at another time point. Our ML-assisted system divided the 662 cases into either thyrotoxicosis and non-thyrotoxicosis and the performance was calculated based on the TFT results. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of our system for predicting thyrotoxicosis were 86.14%, 85.92%, 52.41%, and 97.18%, respectively. When subclinical thyrotoxicosis was excluded from the analysis, the sensitivity, specificity, PPV, and NPV of our system for predicting thyrotoxicosis were 86.14%, 98.28%, 94.57%, and 95.32%, respectively. Our ML-assisted system used the change in mean, relative standard deviation, skewness, and kurtosis of HR while sleeping, and the Jensen-Shannon divergence of sleep HR and TFT distribution as major parameters for predicting thyrotoxicosis. Our ML-assisted system has demonstrated reasonably accurate predictions of thyrotoxicosis in patients with thyroid dysfunction, and the accuracy could be further improved by gathering more data. This predictive system has the potential to monitor the thyroid function status of patients with thyroid dysfunction by collecting heart rate data, and to determine the optimal timing for blood tests and treatment intervention., (© 2023. The Author(s).)

Background: Health care professionals, particularly those in surgical settings, face high stress levels, impacting their well-being. Traditional monitoring methods, like using Holter electrocardiogram monitors, are impractical in the operating room, limiting the assessment of physicians' health. Wrist-worn heart rate monitors, like the Apple Watch, offer promise but are restricted in surgeries due to sterility issues., Objective: This study aims to assess the feasibility and accuracy of using an upper arm-worn Apple Watch for heart rate monitoring during robotic-assisted surgeries, comparing its performance with that of a wrist-worn device to establish a reliable alternative monitoring site., Methods: This study used 2 identical Apple Watch Series 8 devices to monitor the heart rate of surgeons during robotic-assisted surgery. Heart rate data were collected from the wrist-worn and the upper arm-worn devices. Statistical analyses included calculating the mean difference and SD of difference between the 2 devices, constructing Bland-Altman plots, assessing accuracy based on mean absolute error and mean absolute percentage error, and calculating the intraclass correlation coefficient., Results: The mean absolute errors for the whole group and for participants A, B, C, and D were 3.63, 3.58, 2.70, 3.93, and 4.28, respectively, and the mean absolute percentage errors were 3.58%, 3.34%, 2.42%, 4.58%, and 4.00%, respectively. Bland-Altman plots and scatter plots showed no systematic error when comparing the heart rate measurements obtained from the upper arm-worn and the wrist-worn Apple Watches. The intraclass correlation coefficients for participants A, B, C, and D were 0.559, 0.651, 0.508, and 0.563, respectively, with a significance level of P<.001, indicating moderate reliability., Conclusions: The findings of this study suggest that the upper arm is a viable alternative site for monitoring heart rate during surgery using an Apple Watch. The agreement and reliability between the measurements obtained from the upper arm-worn and the wrist-worn devices were good, with no systematic error and a high level of accuracy. These findings have important implications for improving data collection and management of the physical and mental demands of operating room staff during surgery, where wearing a watch on the wrist may not be feasible., (©Kazunosuke Yamada, Yasuaki Enokida, Ryuji Kato, Jun Imaizumi, Takahiro Takada, Hitoshi Ojima. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 01.11.2023.)

Copyright of Physiotherapy Canada is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Disorders of the autonomic nervous system are more com-mon in neurology practice than previously recognized in dia-gnostic conclusions. Besides the primary involvement of the autonomic nervous system, there are sympathetic or parasympathetic (especial-ly vagal) dysfunctions as-sociated with other dis-eases of the central or peripheral nervous system. The aim of this paper is to provide a short overview of the clinical symp-tomatology of autonomic dysfunctions, the examination methods of the autonomic nervous system, especial-ly those available and applicable in clinical neurology practice, and furthemore, the clinical pictures of generalized and localized autonomic dysfunctions. The most important autonomic examinations focus on the cardiovascular system, as-ses-s--ing both heart rate and blood pres-sure changes in appropriately selected autonomic tests. The cardiovascular autonomic reflex tests and the heart rate variability as-ses-sment are the most com-monly used dia-gnostic tools. The examination methods of the autonomic regulations in other systems of the human body are described in this paper in a brief overview. The latter part of this article is dedicated to selected dis-eases and clinical symp-tomatology, among generalized (systematic) disorders of the autonomic nervous system, diabetic autonomic polyneuropathy and autonomic polyneuropathies of other causes which are discus-sed in greater detail. This is fol-lowed by an overview of autonomic disturbances and dysfunctions of central origin that may constitute either major or minor symp-toms of neurological dis-eases. The paper further describes clinical features of localized autonomic disturbances. A simple dia-gnostic scheme for basic evaluation of the autonomic functions in clinical neurology practice is proposed at the end of this paper. [ABSTRACT FROM AUTHOR]

The use of smart watches like the Apple watch and other wearable electronic devices by the general public has been increasing dramatically. Until their accuracy for detecting dysrhythmias has been well-established, however, it would not be appropriate to rely on them solely to rule-in or rule-out pathology. Nonetheless, unusual findings from these devices should be followed up with more conventional investigations, and this approach may prove highly beneficial to patients and treating clinicians alike. This case demonstrates a diagnosis of atrial flutter that was suspected based on the Apple watch and iPhone Health app findings. [ABSTRACT FROM AUTHOR]

Heart rate (HR) is a crucial physiological signal that can be used to monitor health and fitness. Traditional methods for measuring HR require wearable devices, which can be inconvenient or uncomfortable, especially during sleep and meditation. Noncontact HR detection methods employing microwave radar can be a promising alternative. However, the existing approaches in the literature usually use high-gain antennas and require the sensor to face the user's chest or back, making them difficult to integrate into a portable device and unsuitable for sleep and meditation tracking applications. This study presents a novel approach for noncontact HR detection using a miniaturized Soli radar chip embedded in a portable device (Google Nest Hub). The chip has a [Formula: see text] dimension and can be easily integrated into various devices. The proposed approach utilizes advanced signal processing and machine learning techniques to extract HRs from radar signals. The approach is validated on a sleep dataset (62 users, 498 h) and a meditation dataset (114 users, 1131 min). The approach achieves a mean absolute error (MAE) of 1.69 bpm and a mean absolute percentage error (MAPE) of [Formula: see text] on the sleep dataset. On the meditation dataset, the approach achieves an MAE of 1.05 bpm and a MAPE of [Formula: see text]. The recall rates for the two datasets are [Formula: see text] and [Formula: see text], respectively. This study represents the first application of the noncontact HR detection technology to sleep and meditation tracking, offering a promising alternative to wearable devices for HR monitoring during sleep and meditation., (© 2023. Springer Nature Limited.)

Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential alternatives to Electrocardiography (ECG) for heart rate monitoring. Wearable SCG and GCG devices based on lightweight accelerometers and gyroscopes are particularly appealing for continuous, long-term monitoring of heart rate and its variability (HRV). Heartbeat detection in cardio-mechanical signals is usually performed with the support of a concurrent ECG lead, which, however, limits their applicability in standalone cardio-mechanical monitoring applications. The complex and variable morphology of SCG and GCG signals makes the ECG-free heartbeat detection task quite challenging; therefore, only a few methods have been proposed. Very recently, a template matching method based on normalized cross-correlation (NCC) has been demonstrated to provide very accurate detection of heartbeats and estimation of inter-beat intervals in SCG and GCG signals of pathological subjects. In this study, the accuracy of HRV indices obtained with this template matching method is evaluated by comparison with ECG. Tests were performed on two public datasets of SCG and GCG signals from healthy and pathological subjects. Linear regression, correlation, and Bland-Altman analyses were carried out to evaluate the agreement of 24 HRV indices obtained from SCG and GCG signals with those obtained from ECG signals, simultaneously acquired from the same subjects. The results of this study show that the NCC-based template matching method allowed estimating HRV indices from SCG and GCG signals of healthy subjects with acceptable accuracy. On healthy subjects, the relative errors on time-domain indices ranged from 0.25% to 15%, on frequency-domain indices ranged from 10% to 20%, and on non-linear indices were within 8%. The estimates obtained on signals from pathological subjects were affected by larger errors. Overall, GCG provided slightly better performances as compared to SCG, both on healthy and pathological subjects. These findings provide, for the first time, clear evidence that monitoring HRV via SCG and GCG sensors without concurrent ECG is feasible with the NCC-based template matching method for heartbeat detection.

In order to make the teaching and training of aerobics more standardized, it is necessary to use scientific means to detect and monitor the movement standardization in teaching and training and the change of human heart rate in the training process, but at present, there are some difficulties in both detection and monitoring, Therefore, this paper proposes to use the advantages of convolutional neural network to solve the current aerobics teaching problems of motion detection and heart rate monitoring. In the process of operation, the complete aerobics video needs to be divided into several different images, the standardized action image background needs to be eliminated, and then the visual error caused by the difficult action image needs to be corrected. On the premise of image processing, the convolutional neural network is used to pre train the image, and the skeleton map of the human body is constructed in the computer. In the process of practical operation, the use of convolutional neural network for heart rate monitoring has many advantages. It can not only save the time of contact with the human body, but also integrate various information of the time dimension, reducing a lot of computing steps, saving a lot of computing resources for practical work, and promoting the improvement of system output signal quality to a certain extent. The result of the experiment also proves that the convolutional neural network can improve the accuracy of students' movement detection and heart rate change monitoring in aerobics teaching and training., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interests., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Motivation : The advancement of preventive medicine and, subsequently, telemedicine drives the need for noninvasive and remote measurements in patients' natural environments. Heart rate (HR) measurements are particularly promising and extensively researched due to their quick assessment and comprehensive representation of patients' conditions. However, in scenarios such as endurance training or emergencies, where HR measurement was not anticipated and direct access to victims is limited, no method enables obtaining HR results that are suitable even for triage. Methods : This paper presents the possibility of remotely measuring of human HR from a series of in-flight videos using videoplethysmography (VPG) along with skin detection, human pose estimation and image stabilization methods. An unmanned aerial vehicle (UAV) equipped with a camera captured ten segments of video footage featuring volunteers engaged in free walking and running activities in natural sunlight. The human pose was determined using the OpenPose algorithm, and subsequently, skin areas on the face and forearms were identified and tracked in consecutive frames. Ultimately, HR was estimated using several VPG methods: the green channel (G), green-red difference (GR), excess green (ExG), independent component analysis (ICA), and a plane orthogonal to the skin (POS). Results : When compared to simultaneous readings from a reference ECG-based wearable recorder, the root-mean-squared error ranged from 17.7 (G) to 27.7 (POS), with errors of less than 3.5 bpm achieved for the G and GR methods. Conclusions : These results demonstrate the acceptable accuracy of touchless human pulse measurement with the accompanying UAV-mounted camera. The method bridges the gap between HR-transmitting wearables and emergency HR recorders, and it has the potential to be advantageous in training or rescue scenarios in mountain, water, disaster, or battlefield settings.

Introduction: Fetal heart rate (FHR) monitoring is routine in intrapartum care worldwide and one of the most common obstetrical procedures. Intrapartum FHR monitoring helps assess fetal wellbeing and interpretation of the FHR help form decisions for clinical management and intervention. It relies on the observers' subjective assessments, with variation in interpretations leading to variations in intrapartum care. The purpose of this systematic review was to summarize and evaluate extant inter- and intrarater reliability research on the human interpretation of intrapartum FHR monitoring., Material and Methods: We searched for the terms "fetal heart rate monitoring," "interpretation agreement" and related concepts on Embase, Medline, Maternity and Infant Care Database and CINAHL. The last search was made on January 31, 2022. The protocol for the study was prospectively registered in PROSPERO (CRD42021260937). Studies that assess inter- and intrarater reliability and agreement of health professionals' intrapartum FHR monitoring were included and studies including other assessment of fetal wellbeing excluded. We extracted data in reviewer pairs using quality appraisal tool for studies of diagnostic reliability (QAREL) forms. The data retrieved from the studies are presented as narrative synthesis and in additional tables., Results: Forty-nine articles concerning continuous FHR monitoring were included in the study. For interrater reliability and agreement, in total 577 raters assessed 6315 CTG tracings. There was considerable heterogeneity in quality and measures across the included articles. We found higher reliability and agreement for the basic FHR features than for overall classification and higher agreement for intrarater reliability and agreement than for their interrater counterparts., Conclusions: There is great variation in reliability and agreement measures for continuous intrapartum FHR monitoring, implying that intrapartum CTG should be used with caution for clinical decision making given its questionable reliability. We found few high-quality studies and noted methodological concerns in the studies. We recommend a more standardized approach to future reliability studies on FHR monitoring., (© 2023 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)