Heart Rate Measurements Research Articles

Prediction of clinical deterioration risk at 8 hours after arrival in emergency department in non‐traumatic patients using trends in modified early warning score level

AbstractBackgroundImproving the quality of medical care in hospitals is a major priority for all departments. The early warning score (EWS) trend is an effective early risk stratification tool that reflects the changes in patient condition and allows better assessment of deterioration risk.ObjectiveThe aim of this study was to investigate whether utilizing the trend of the modified early warning score (MEWS) level within 4 h of a patient's arrival in the emergency department (ED) could identify patients at risk of clinical deterioration at 8 h after arrival in the ED.MethodsWe conducted a retrospective observational study of non‐trauma patients who had at least two vital sign measurements (Glasgow Coma Scale score, heart rate, blood pressure, respiratory rate, and body temperature) within 8 h of arriving in the ED. The primary outcome was patients who had MEWS ≥ 4 at 8 h after arrival in the ED. We performed multivariate logistic regression analysis using age, sex, MEWS level at arrival in the ED, MEWS level within 4 h after arrival in the ED, and MEWS level trend over time.ResultsAmong the 5825 patients, 680 (11.7%) were at risk of deterioration at 8 h after arrival in the ED. To predict the risk of deteriorating conditions (MEWS ≥ 4), utilizing the MEWS level trend within 4 h of arrival in the ED was more effective in identifying patients at risk of deterioration after 8 h of arrival in the ED compared to using a single MEWS value during the ED stay. The corresponding areas under the receiver operating characteristic curve were 0.756 (95% confidence interval (CI) 0.734–0.778) and 0.846 (95% CI 0.827–0.865), respectively (p < 0.01).ConclusionsThe proposed trend‐based predictive model for MEWS levels can alert healthcare personnel regarding patients at increased risk of deterioration (MEWS ≥ 4), potentially reducing mortality rates during ED stays.

IoT-FAR: A multi-sensor fusion approach for IoT-based firefighting activity recognition

Inadequate training poses a significant risk of injury among young firefighters. Although Human Activity Recognition (HAR) algorithms have shown potential in monitoring and evaluating performance, most existing studies focus on daily activities and have difficulty distinguishing complex firefighting tasks. This study introduces the Internet of things (IoT)-based wearable firefighting activity recognition (IoT-FAR) system which employs a multi-modal sensor fusion approach to achieve comprehensive activity recognition during firefighting training. The IoT-FAR comprises five wearable body sensor nodes and a coordinator node. This study explores the significance of features extracted from the surface electromyography, heart rate, and inertial measurement units in firefighting training activity recognition. A hybrid machine learning (HML)-based network is proposed, which integrates three models: one trained with all features (MA), another with upper body features (MU), and a third with lower body features (ML). The proposed HML-SVM-RBF1-RF2 network achieves superior performance, with a mean recall of 93.94%, mean precision of 90.94%, and a mean accuracy rate of 98.29%. Additionally, the study introduces the specialized firefighting training associated activities (SFTAA) dataset, which includes endurance training activities involving self-contained breathing apparatus (SCBA) conducted by eighteen firefighters. This dataset represents preliminary work towards building a comprehensive dataset covering various events and scenarios for tracking firefighter activities. The IoT-FAR system also demonstrates the potential use of misclassified activities as evaluation metrics for assessing firefighter training performance.

Comparison of physiological and clinical reactions to COVID-19 and influenza vaccination

BackgroundPublic reluctance to receive COVID-19 vaccination is associated with safety concerns. By contrast, the seasonal influenza vaccine has been administered for decades with a solid safety record and a high level of public acceptance. We compare the safety profile of the BNT162b2 COVID-19 booster vaccine to that of the seasonal influenza vaccine.MethodsWe study a prospective cohort of 5079 participants in Israel and a retrospective cohort of 250,000 members of MHS selected randomly. We examine reactions to BNT162b2 mRNA COVID-19 booster and to influenza vaccinations. All prospective cohort participants wore a smartwatch and completed a daily digital questionnaire. We compare pre-vaccination and post-vaccination smartwatch heart-rate data, and a stress measure based on heart-rate variability. We also examine adverse events from electronic health records.ResultsIn the prospective cohort, 1905 participants receive the COVID-19 booster vaccine; 899 receive influenza vaccination. Focusing on those who receive both vaccines yields a total of 689 participants in the prospective cohort and 31,297 members in the retrospective cohort. Individuals reporting a more severe reaction after influenza vaccination tend to likewise report a more severe reaction after COVID-19 vaccination. In paired analysis, the increase in both heart rate and stress measure for each participant is higher for COVID-19 than for influenza in the first 2 days after vaccination. No elevated risk of hospitalization due to adverse events is found following either vaccine. Except for Bell’s palsy after influenza vaccination, no elevated risk of adverse events is found.ConclusionsThe more pronounced side effects after COVID-19 vaccination may explain the greater concern associated with it. Nevertheless, our comprehensive analysis supports the safety profile of both vaccines.

Evaluation of 0.1% and 1% atropine eyedrops in cats: A comparative study of tolerance, stability, and efficacy.

Investigate the tolerance, stability, and efficacy of topical 0.1% and 1% atropine in cats. Six cats underwent two trials separated by a 2-week washout period. One drop of artificial tears was placed in one randomly selected eye (control), and one drop of either 0.1% atropine (Trial I) or 1% atropine (Trial II) was placed in the other eye. Immediate adverse effects were recorded for severity (0-3) and duration (seconds). Horizontal pupil diameter (HPD), pupillary light reflexes (PLRs), intraocular pressure (IOP), Schirmer tear test-1 (STT-1), and heart rate (HR) were monitored at baseline then 8 h post-administration. PLRs were assessed for a total of 72 h. Stability was assessed weekly for 1 month in room temperature and refrigerated conditions, evaluating solution clarity, pH, and drug concentrations. Adverse effects had a significantly lower severity score and shorter duration with 0.1% versus 1% atropine (severity 1.2 ± 0.4 vs. 2.5 ± 0.5, p = .010; duration 107.5 ± 53.3 vs. 293.3 ± 106.5 s, p = .009). HPD was significantly greater than baseline measurements as early as 40 min for both atropine formulations. Pupils were non-responsive for a significantly shorter duration with 0.1% versus 1% atropine (median 7 h vs. 47.5 h, p = .031). Compared with control eyes, IOP was significantly elevated by 1% atropine (p = .021) but not 0.1% atropine (p = .502). No significant differences were noted in STT-1 and HR measurements. Both solutions were stable in room temperature and refrigerated conditions for 1 month. Diluted 0.1% atropine was stable and better tolerated by cats, offering a potential alternative to feline patients that experience adverse effects from topical 1% atropine.

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review.

Mental stress and its consequent mental health disorders (MDs) constitute a significant public health issue. With the advent of machine learning (ML), there is potential to harness computational techniques for better understanding and addressing mental stress and MDs. This comprehensive review seeks to elucidate the current ML methodologies used in this domain to pave the way for enhanced detection, prediction, and analysis of mental stress and its subsequent MDs. This review aims to investigate the scope of ML methodologies used in the detection, prediction, and analysis of mental stress and its consequent MDs. Using a rigorous scoping review process with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, this investigation delves into the latest ML algorithms, preprocessing techniques, and data types used in the context of stress and stress-related MDs. A total of 98 peer-reviewed publications were examined for this review. The findings highlight that support vector machine, neural network, and random forest models consistently exhibited superior accuracy and robustness among all ML algorithms examined. Physiological parameters such as heart rate measurements and skin response are prevalently used as stress predictors due to their rich explanatory information concerning stress and stress-related MDs, as well as the relative ease of data acquisition. The application of dimensionality reduction techniques, including mappings, feature selection, filtering, and noise reduction, is frequently observed as a crucial step preceding the training of ML algorithms. The synthesis of this review identified significant research gaps and outlines future directions for the field. These encompass areas such as model interpretability, model personalization, the incorporation of naturalistic settings, and real-time processing capabilities for the detection and prediction of stress and stress-related MDs.

Feasibility study of the use of a wearable vital sign patch in an intensive care unit setting.

Multiple studies and review papers have concluded that early warning systems have a positive effect on clinical outcomes, patient safety and clinical performances. Despite the substantial evidence affirming the efficacy of EWS applications, persistent barriers hinder their seamless integration into clinical practice. Notably, EWS, such as the National Early Warning Score, simplify multifaceted clinical conditions into singular numerical indices, thereby risking the oversight of critical clinical indicators and nuanced fluctuations in patients' health status. Furthermore, the optimal deployment of EWS within clinical contexts remains elusive. Manual assessment of EWS parameters exacts a significant temporal toll on healthcare personnel. Addressing these impediments necessitates innovative approaches. In this regard, wearable medical technologies emerge as promising solutions capable of continual monitoring of hospitalized patients' vital signs. To overcome the barriers of the use of early warning scores, wearable medical technology has the potential to continuously monitor vital signs of hospitalised patients. However, a fundamental inquiry arises regarding the comparability of their reliability to the current used golden standards. This inquiry underscores the imperative for rigorous evaluation and validation of wearable medical technologies to ascertain their efficacy in augmenting extant clinical practices. This prospective, single-center study aimed to evaluate the accuracy of heart rate and respiratory rate measurements obtained from the Vivalink Cardiac patch in comparison to the ECG-based monitoring system utilized at AZ Maria Middelares Hospital in Ghent. Specifically, the study focused on assessing the concordance between the data obtained from the Vivalink Cardiac patch and the established ECG-based monitoring system among a cohort of ten post-surgical intensive care unit (ICU) patients. Of these patients, five were undergoing mechanical ventilation post-surgery, while the remaining five were not. The study proceeded by initially comparing the data recorded by the Vivalink Cardiac patch with that of the ECG-based monitoring system. Subsequently, the data obtained from both the Vivalink Cardiac patch and the ECG-based monitoring system were juxtaposed with the information derived from the ventilation machine, thereby providing a comprehensive analysis of the patch's performance in monitoring vital signs within the ICU setting. For heart rate, the Vivalink Cardiac patch was on average within a 5% error range of the ECG-based monitoring system during 85.11±10.81% of the measured time. For respiratory rate this was during 40.55±17.28% of the measured time. Spearman's correlation coefficient showed a very high correlation of 8 for heart rate and a moderate correlation of for respiratory rate. In comparison with the ventilated respiratory rate (ventilation machine) the Vivalink and ECG-based monitoring system both had a moderate correlation of A very high correlation was found between the heart rate measured by the Vivalink Cardiac patch and that of the ECG-based monitoring system of the hospital. Concerning respiratory rate the correlation between the data from the Vivalink Cardiac patch, the ECG-based monitoring system and the ventilation machine was found to be moderate.

Vital parameter monitoring in harsh environment by the MedSENS in-ear multisensor device

Accurate assessment of vital parameters is essential for diagnosis and triage of critically ill patients, but not always feasible in out-of-hospital settings due to the lack of suitable devices. We performed an extensive validation of a novel prototype in-ear device, which was proposed for the non-invasive, combined measurement of core body temperature (Tc), oxygen saturation (SpO2), and heart rate (HR) in harsh environments. A pilot study with randomized controlled design was conducted in the terraXcube environmental chamber. Participants were subsequently exposed to three 15 min test sessions at the controlled ambient temperatures of 20 °C, 5 °C, and − 10 °C, in randomized order. Vital parameters measured by the prototype were compared with Tc measurements from commercial esophageal (reference) and tympanic (comparator) probes and SpO2 and HR measurements from a finger pulse-oximeter (reference). Performance was assessed in terms of bias and Lin’s correlation coefficient (CCC) with respect to the reference measurements and analyzed with linear mixed models. Twenty-three participants (12 men, mean (SD) age, 35 (9) years) completed the experimental protocol. The mean Tc bias of the prototype ranged between − 0.39 and − 0.80 °C at ambient temperatures of 20 °C and 5 °C, and it reached − 1.38 °C only after 15 min of exposure to − 10 °C. CCC values ranged between 0.07 and 0.25. SpO2 and HR monitoring was feasible, although malfunctioning was observed in one third of the tests. SpO2 and HR bias did not show any significant dependence on environmental conditions, with values ranging from − 1.71 to − 0.52% for SpO2 and 1.12 bpm to 5.30 bpm for HR. High CCC values between 0.81 and 0.97 were observed for HR in all environmental conditions. This novel prototype device for measuring vital parameters in cold environments demonstrated reliability of Tc measurements and feasibility of SpO2 and HR monitoring. Through non-invasive and accurate monitoring of vital parameters from the ear canal our prototype may offer support in triage and treatment of critically ill patients in harsh out-of-hospital conditions.

A Retrospective Observational Study of Continuous Wireless Vital Sign Monitoring via a Medical Grade Wearable Device on Hospitalized Floor Patients.

Background: Continuous vital sign monitoring via wearable technology, combined with algorithm-based notifications, has been utilized for early detection of patient deterioration. In this retrospective observational study, we summarize a large-scale implementation of a continuous monitoring system in medical-surgical units of two hospitals over the course of fifteen (15) months. Methods: An FDA-cleared wireless monitoring device (BioButton®, BioIntelliSense Inc., Golden, CO, USA), was placed on each patient upon admission. The wearable device measures heart rate and respiratory rate at rest, skin temperature, and patient activity levels. High-frequency data (up to 1440 measurements per day) are transmitted to display in exception management software (BioDashboard™, version 2.9, BioIntelliSense Inc.). Algorithmic and rules-based notifications are triggered based on clinical and statistical trending criteria. We present (i) agreement of device readings with bedside charted measurements, (ii) the frequency of notifications, (iii) the occurrence of notifications prior to clinical deterioration events, and (iv) impact on clinical management, including early data on length of stay (LOS). Results: In total, 11,977 patient encounters were monitored at two sites. Bias ±95% limits of agreement were 1.8 ± 12.5 for HR and 0.4 ± 8.0 for RR. The rates of notifications were 0.97 and 0.65 per patient-day at Sites 1 and 2, respectively. Among clinical deteriorations, 73% (66%) had at least one notification within 24 h prior at Site 1 (Site 2). At Site 1, there were 114 cases for which a notification led to a new or changed physician's order. LOS in the first unit monitored by the system exhibited a decreasing trend from 3.07 days to 2.75 days over 12 months. Conclusions: Wearable continuous vital sign monitoring with the BioIntelliSense BioButton® system enables early detection of clinical deterioration.

Lactate threshold evaluation in swimming using a sweat lactate sensor: A prospective study.

Since assessing aerobic capacity is key to enhancing swimming performance, a simple and widely applicable technology should be developed. Therefore, we aimed to noninvasively visualize real-time changes in sweat lactate (sLA) levels during swimming and investigate the relationship between lactate thresholds in sweat (sLT) and blood (bLT). This prospective study included 24 university swimmers (age: 20.7s±1.8years, 58% male) who underwent exercise tests at incremental speeds with or without breaks in a swimming flume to measure heart rate (HR), bLT, and sLT based on sLA levels using a waterproof wearable lactate sensor attached to the dorsal upper arm on two different days. The correlation coefficient and Bland-Altman methods were used to verify the similarities of the sLT with bLT and personal performance. In all tests, dynamic changes in sLA levels were continuously measured and projected onto the wearable device without delay, artifacts, or contamination. Following an initial minimal current response, with increasing speed the sLA levels increased substantially, coinciding with a continuous rise in HR. The speed at sLT strongly correlated with that at bLT (p<0.01 and r=0.824). The Bland-Altman plot showed a strong agreement (mean difference: 0.08±0.1m/s). This prospective study achieved real-time sLA monitoring during swimming, even with vigorous movement. The sLT closely approximated bLT; both were subsequently validated for their relevance to performance.

The cardiovascular exercise response in children with overweight or obesity measured by cardiovascular magnetic resonance imaging.

Overweight and obesity are among the main causes of cardiovascular diseases. Exercise testing can aid in the early detection of subtle cardiac dysfunction not present in rest. We hypothesized that the cardiovascular response to exercise is impaired among children with overweight or obesity, characterized by the inability of the cardiovascular system to adapt to exercise by increasing cardiac volumes and blood pressure. We performed a cardiovascular stress test to investigate whether the cardiovascular exercise response is altered in children with overweight and obesity, as compared to children with a normal weight. A subgroup of the Generation R population-based prospective cohort study, consisting of 41 children with overweight or obesity and 166 children with a normal weight with a mean age of 16 years, performed an isometric exercise. Continuous heart rate and blood pressure were measured during rest, exercise and recovery. Cardiovascular magnetic resonance (CMR) measurements were performed during rest and exercise. Higher BMI was associated with a higher resting systolic and diastolic blood pressure (difference: 0.24 SDS (95% CI 0.10, 0.37) and 0.20 SDS (95% CI 0.06, 0.33)) and lower systolic and diastolic blood pressure increases from rest to peak exercise (-0.11 SDS (95% CI -0.20, -0.03) and -0.07 SDS (95% CI -0.07, -0.01)). BMI was also associated with a slower decrease in systolic and diastolic blood pressure during recovery (p values < 0.05). Higher childhood BMI was associated with lower BSA corrected left ventricular mass, end-diastolic volume and stroke volume (p values < 0.05). There were no associations of childhood BMI with the cardiac response to exercise measured by heart rate and CMR measurements. Childhood BMI is, across the full range, associated with a blunted blood pressure response to static exercise but there were no differences in cardiac response to exercise. Our findings suggest that adiposity may especially affect the vascular exercise reaction without affecting cardiac response.

Abstract Mo131: Time-Restricted Feeding Normalizes Dim Light at Night-Induced Disruption of Cardiovascular Rhythms in Mice

Background: Light input to the suprachiasmatic nucleus entrains circadian rhythms in physiology and behavior to the day-night cycle. Exposure to light at night in people is associated with cardiometabolic disease. Pre-clinical studies show that artificial light at night, including at very low levels, disrupts day-night rhythms in activity, feeding behavior, heart rate, and blood pressure dipping. Hypothesis: Dim light at night (dLAN) disrupts day-night rhythms in feeding behavior to blunt day-night rhythms in autonomic input to the heart and blood pressure dipping. Methods: Mice (n=5-6/sex) in thermoneutral housing were implanted with telemetry probes to record heart rate, blood pressure, and core body temperature. Autonomic input to the heart was assessed by measuring heart rate and subtracting the temperature-dependent changes in the heart rate after pharmacological inhibition of muscarinic and β-adrenergic receptor activation. Mice were housed in 12 h light: 12 h dark cycles (LD, 200 lux: 0 lux) with ad libitum access to food (LD-ALF), subjected to 12 h light: 12 h dLAN cycles (dLAN-ALF; 200 lux: 5 lux) for two weeks, and then feeding was time-restricted (not calorically restricted) to the dLAN cycle (dLAN-RF). Data were extracted from Ponemah and Clocklab, and statistical analysis was done using GraphPad PRISM software. Results: Compared to LD-ALF mice, dLAN-ALF mice showed reduced amplitudes in day-night activity, feeding, heart rate, and blood pressure rhythms, with males more affected than females (p&lt;0.001). dLAN-ALF male and female mice had decreased amplitudes in the day-night rhythms in autonomic input to the heart. In addition, dLAN-ALF male mice had less blood pressure dipping. dLAN-RF normalized autonomic input to the heart and heart rate in male and female mice (p&lt;0.05, p&lt;0.01, respectively). dLAN-RF also improved blood pressure dipping in male mice (p&lt;0.001). dLAN-RF did not normalize activity rhythms. Conclusion: dLAN disrupts day-night rhythms in activity, feeding, heart rate, and blood pressure dipping in mice, with males being more impacted. Time-restricted feeding to the dLAN cycle normalizes autonomic input to the heart and blood pressure dipping. These data suggest that time-restricted feeding counteracts the light-at-night-induced circadian disruption of cardiovascular function.

Privacy-Protected Contactless Sleep Parameters Measurement Using a Defocused Camera.

Sleep monitoring plays a vital role in various scenarios such as hospitals and living-assisted homes, contributing to the prevention of sleep accidents as well as the assessment of sleep health. Contactless camera-based sleep monitoring is promising due to its user-friendly nature and rich visual semantics. However, the privacy concern of video cameras limits their applications in sleep monitoring. In this paper, we explored the opportunity of using a defocused camera that does not allow identification of the monitored subject when measuring sleep-related parameters, as face detection and recognition are impossible on optically blurred images. We proposed a novel privacy-protected sleep parameters measurement framework, including a physiological measurement branch and a semantic analysis branch based on ResNet-18. Four important sleep parameters are measured: heart rate (HR), respiration rate (RR), sleep posture, and movement. The results of HR, RR, and movement have strong correlations with the reference (HR: R = 0.9076; RR: R = 0.9734; Movement: R = 0.9946). The overall mean absolute errors (MAE) for HR and RR are 5.2 bpm and 1.5 bpm respectively. The measurement of HR and RR achieve reliable estimation coverage of 72.1% and 93.6%, respectively. The sleep posture detection achieves an overall accuracy of 94.5%. Experimental results show that the defocused camera is promising for sleep monitoring as it fundamentally eliminates the privacy issue while still allowing the measurement of multiple parameters that are essential for sleep health informatics.

Actigraphy-based sleep and muscle sympathetic nerve activity in humans.

Short and insufficient sleep are prevalent and associated with cardiovascular disease, with the sympathetic nervous system as a suspected mediator. The purpose of the present study was to investigate the association between objective, actigraphy-based total sleep time (TST), sleep efficiency (SE), and cardiovascular and sympathetic regulation in healthy adults. We hypothesized that short TST and low SE would be associated with elevated resting blood pressure, heart rate (HR), and muscle sympathetic nerve activity (MSNA). Participants included 94 individuals [46 males, 48 females, age: 30 ± 15 yr, body mass index (BMI): 26 ± 4 kg/m2]. All participants underwent at least 7 days of at-home, wristwatch actigraphy monitoring (avg: 10 ± 3 days). Seated blood pressures were assessed using brachial blood pressure measurements, followed by a 10-minute supine autonomic testing session consisting of continuous HR (electrocardiogram), beat-by-beat blood pressure (finger plethysmograph), and MSNA (microneurography) monitoring. Partial correlations were used to determine the relationship between sleep and cardiovascular parameters while accounting for the influence of age, sex, and BMI. TST was not associated with MAP (R = -0.105, P = 0.321), HR (R = 0.093, P = 0.383), or MSNA burst frequency (BF; R = -0.168, P = 0.112) and burst incidence (BI; R = -0.162, P = 0.124). Similarly, SE was not associated with MAP (R = -0.088, P = 0.408), HR (R = -0.118, P = 0.263), MSNA BF (R = 0.038, P = 0.723), or MSNA BI (R = 0.079, P = 0.459). In contrast to recent preliminary findings, our results do not support a significant association between actigraphy-based sleep duration or efficiency and measures of resting blood pressure, heart rate, and MSNA.NEW & NOTEWORTHY The present study investigated the independent association between actigraphy-based sleep duration, efficiency, and measures of blood pressure, heart rate, and muscle sympathetic nerve activity (MSNA) in adult males and females. Contrary to our hypothesis, the findings do not support an independent association between habitual sleep and cardiovascular or sympathetic neural activity. However, these findings do not preclude a potential association between these parameters in populations with sleep disorders and/or cardiovascular disease.

Remote Photoplethysmography for Heart Rate and Blood Oxygenation Measurement: A Review

Remote Photoplethysmography for Heart Rate and Blood Oxygenation Measurement: A Review

Effects of traditional and dry bed baths on patients admitted in intensive units: A randomized crossover clinical trial.

The bed bath is an important part of nursing care. There are few studies evaluating the effects of traditional and dry bed baths on patients. This study was performed with the aim of investigating the effect of traditional and dry bed baths given to intensive care unit patients on the patients' hemodynamic parameters, the duration of the bathing procedure and the cost of consumable items. This was a randomized crossover clinical trial and a prospective study. The study was conducted in a General Surgery Intensive Care Unit with 22 intensive care patients aged 18 and over, who had a nursing diagnosis of bathing personal care deficiency. Each patient was given two types of bed baths at an interval of 24 h: a traditional bed bath and a dry bed bath performed with single-use tissues. Immediately before each bath, in the 5th, 10th and 15th minute of bathing, immediately after bathing and 30 min after bathing, body temperature, heart rate, blood pressure, breathing rate and peripheral oxygen saturation measurement changes over time were compared within the group using the Friedman test. The Wilcoxon signed ranks test was used to compare the variables of bathing duration and bathing consumable item costs between the bathing procedures. It was found that at the completion of traditional and dry bed bathing, the participants' body temperature, blood pressure, heart rate and breathing rate parameters were statistically significantly lower than before bathing, whereas peripheral oxygen saturation values showed a significant increase (p < 0.05). It was found that the dry bed bath took a statistically significantly shorter time than the traditional bed bath and that the cost of consumable bathing materials was less (p < 0.05). It was concluded that traditional and dry bed baths given to intensive care patients affected their hemodynamic parameters and that the dry bed bath was superior to the traditional bed bath in that it took less time and that it cost less.

The effects of an employee assistance program on productivity at work, workability, absenteeism, and smartphone measures of heart rate and heart rate variability.

Employee Assistance Programs (EAPs) have been shown to effectively reduce absenteeism, workplace injury rates, and health-related productivity impairments. However, established measures for determining its impact on employee-level productivity have rarely been used, nor have studies employed biological measures of well-being. Drawing on the allostatic load theory, we examine the effects of an EAP on biological measures (heart rate, heart rate variability), established measures of health-related productivity (Workability Index, Health and Work Performance Questionnaire, Workplace Limitations Questionnaire), and absenteeism 4 weeks and 6 months after clients started to receive counseling. We conducted a quasi-experimental study comparing an EAP (n = 73) with a matched control group (n = 134) using propensity score matching. We found that an EAP improves health-related productivity 4 weeks and 6 months after enrolling in counseling, above and beyond changes in the control group. Biological measures changed in the hypothesized directions, but differences between the groups did not reach significance. Absenteeism did not change in the EAP group 6 months after enrolling in counseling. In an exploratory analysis, we found that individuals requiring many sessions in the first 4 weeks showed worse productivity outcomes, demonstrating a negative dose-response relationship. Our study provides an example of how to include biological measures in EAP research. It adds to the scientific evidence of the usefulness of EAP services in restoring employee-level productivity. We calculate that the marginal productivity improvements per employee using the EAP are as much as $15,600 per annum. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Noise Study on the OH1 Wearable Device: Analysis of 11 Hand Movement Artifacts

Wearable devices like the OH1 are increasingly used for real-time health monitoring, particularly for measuring heart rate (BPM). However, their accuracy is often compromised by motion artifacts, introducing significant noise into the measurements. This study specifically addresses the issue of noise generated by the OH1 wearable device during eleven different hand movements. To tackle this problem, we implemented a precise experimental setup involving device calibration, stable testing conditions, and participant training to ensure high consistency in hand movements. Additionally, machine learning algorithms were employed to separate noise from desired hand movement data. Our results indicate that certain hand movements, such as lifting arms and shoulder rotations, produce higher noise levels, while others, like placing hands on the table, generate minimal noise. These findings provide valuable insights for developing effective noise reduction algorithms, ultimately enhancing the accuracy and reliability of BPM measurements from wearable devices.

Analisis Pemasaran Sosial Media Melalui Perkembangan Teknologi Terhadap Produk Smartwatch

Something that is quite significant about smartwatches today is their role in helping users monitor health and fitness, by carrying various superior features ranging from measuring heart rate, measuring oxygen pressure in the blood, footsteps, running distance, GPS features, calculating sleep hours, notifications. cell phone, music settings and answering incoming calls. What is no less interesting about smartwatches is that their internal devices are very modern for users ranging from teenagers to adults. This research was carried out through monitoring social media and conducting research in the research office area located in Ruko Apartment Puncak Bukit Golf No. 1. The influence of using social media is sufficient to function as an effective platform for promoting smartwatch products, which provides direct interaction between sellers and buyers.

Acceptability of heart rate-based remote monitoring of smoking status

IntroductionDigital interventions present a scalable solution to overcome barriers to smoking cessation treatment, and changes in resting heart rate (HR) may offer a viable option for monitoring smoking status remotely. The goal of this study was to explore the acceptability of using smartphone cameras and activity trackers to measure heart rate for use in a smoking cessation intervention. MethodsParticipants (N=410), most of whom identified as female (75.8 %) with mean age 38.3 years (SD 11.4), were recruited via the Smoke Free app. They rated the perceived comfort, convenience, and likelihood of using smartphone cameras and wrist-worn devices for HR monitoring as an objective measure of smoking abstinence. Wilcoxon signed-rank tests and Kruskal-Wallis tests assessed differences in acceptability across device types and whether the participant owned an activity tracker/smartwatch or smartphone. ResultsParticipants reported high levels of acceptability for both HR monitoring methods, with activity trackers/smartwatches rated more favorably in terms of comfort, convenience, and likelihood of use compared to smartphone cameras. Participants indicated a statistically significantly greater likelihood of using the activity tracker/smartwatch over the smartphone camera. Participants viewed the activity tracker/smartwatch as more acceptable than the smartphone camera (87.0% vs 50.0%). ConclusionsHR monitoring via smartphone cameras and wrist-worn devices was deemed acceptable among people interested in quitting smoking. Wrist-worn devices, in particular, were preferred, suggesting their potential as a scalable, user-friendly method for remotely monitoring smoking status. These findings support the need for further exploration and implementation of HR monitoring technology in smoking cessation research and interventions.

May Measurement Month 2021: an analysis of blood pressure screening results from Kenya.

Hypertension is a major contributor to premature death and disability globally. The age-standardized prevalence of hypertension among adults aged 30-79 years is among the highest at 36%. Despite the availability of cost-effective interventions, awareness, treatment, and control rates remain low. To tackle this and raise awareness, the May Measurement Month (MMM) campaign was initiated by the International Society of Hypertension in 2017. This paper summarizes results from the 2021 MMM campaign. Screening was conducted in 22 sites across 7 counties. We aimed to take three blood pressure (BP) readings and corresponding heart rate measurements as per the standardized protocol. Where this was not achievable, at least one reading was taken. Other variables recorded included demographic data, risk factors, comorbidities, and history of COVID-19 infection. A total of 9738 individuals were screened, of whom 57% were female. After multiple imputations, 28.2% were hypertensive, of whom 45.9% were aware and 42.0% were on treatment. Of those on treatment, 50.3% were controlled, translating to control among only 21.1% of the total hypertensive population. Previous COVID-19 vaccinations were associated with lower systolic BP (SBP) and diastolic BP (DBP). Individuals who consumed alcohol one to three times a month had lower diastolic BP after adjustment for age, sex, and anti-hypertensive treatment. Among women, the use of hormonal contraceptives was associated with lower SBP and DBP after adjustment for age, sex, and anti-hypertensive treatment. Hypertension awareness, treatment, and control rates remain low, though trends from previous MMM campaigns in Kenya suggest steady improvement. The associations between COVID-19 vaccination and contraceptive use with lower BP warrant further investigation. Programmes such as MMM provide much needed data to track the progress towards reducing the burden of hypertension.