Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients.
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ABSTRACT:
SUBMITTER: Hoog Antink C
PROVIDER: S-EPMC8047026 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The non-invasiveness of photoplethysmographic (PPG) acquisition systems, together with their cost-effectiveness and easiness of connection with IoT technologies, is opening up to the possibility of their widespread use. For this reason, the study of the reliability of PPG and pulse rate variability (PRV) signal quality has become of great scientific, technological, and commercial interest. In this field, sensor location has been demonstrated to play a crucial role. The goal of this study was to investigate PPG and PRV signal quality acquired from two body locations: finger and wrist. We simultaneously acquired the PPG and electrocardiographic (ECG) signals from sixteen healthy subjects (aged 28.5 ± 3.5, seven females) who followed an experimental protocol of affective stimulation through visual stimuli. Statistical tests demonstrated that PPG signals acquired from the wrist and the finger presented different signal quality indexes (kurtosis and Shannon entropy), with higher values for the wrist-PPG. Then we propose to apply the cross-mapping (CM) approach as a new method to quantify the PRV signal quality. We found that the performance achieved using the two sites was significantly different in all the experimental sessions (p < 0.01), and the PRV dynamics acquired from the finger were the most similar to heart rate variability (HRV) dynamics.
| S-EPMC7309104 | biostudies-literature
Project description:Heart rate (HR) and HR variability (HRV) infer readiness to perform exercise in athletic populations. Technological advancements have facilitated HR and HRV quantification via photoplethysmography (PPG). This study evaluated the validity of WHOOP's PPG-derived HR and HRV against electrocardiogram-derived (ECG) measures. HR and HRV were assessed via WHOOP and ECG over 15 opportunities. WHOOP-derived pulse-to-pulse (PP) intervals were edited with WHOOP's proprietary filter, in addition to various filter strengths via Kubios HRV software. HR and HRV (Ln RMSSD) were quantified for each filter strength. Agreement was assessed via bias and limits of agreement (LOA), and contextualised using smallest worthwhile change (SWC) and coefficient of variation (CV). Regardless of filter strength, bias (≤0.39 ± 0.38%) and LOA (≤1.56%) in HR were lower than the CV (10-11%) and SWC (5-5.5%) for this parameter. For Ln RMSSD, bias (1.66 ± 1.80%) and LOA (±5.93%) were lowest for a 200 ms filter and WHOOP's proprietary filter, which approached or exceeded the CV (3-13%) and SWC (1.5-6.5%) for this parameter. Acceptable agreement was found between WHOOP- and ECG-derived HR. Bias and LOA in Ln RMSSD approached or exceeded the SWC/CV for this variable and should be interpreted against its own level of bias precision.
| S-EPMC8160717 | biostudies-literature
Project description:To the best of our knowledge, there is no annotated database of PPG signals recorded by smartphone publicly available. This article introduces Brno University of Technology Smartphone PPG Database (BUT PPG) which is an original database created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology, for the purpose of evaluating photoplethysmographic (PPG) signal quality and estimation of heart rate (HR). The data comprises 48 10-second recordings of PPGs and associated electrocardiographic (ECG) signals used for determination of reference HR. The data were collected from 12 subjects (6 female, 6 male) aged between 21 and 61. PPG data were collected by smartphone Xiaomi Mi9 with sampling frequency of 30 Hz. Reference ECG signals were recorded using a mobile ECG recorder (Bittium Faros 360) with a sampling frequency of 1,000 Hz. Each PPG signal includes annotation of quality created manually by biomedical experts and reference HR. PPG signal quality is indicated binary: 1 indicates good quality for HR estimation, 0 indicates signals where HR cannot be detected reliably, and thus, these signals are unsuitable for further analysis. As the only available database containing PPG signals recorded by smartphone, BUT PPG is a unique tool for the development of smart, user-friendly, cheap, on-the-spot, self-home-monitoring of heart rate with the potential of widespread using.
| S-EPMC8440059 | biostudies-literature
Project description:In France, new cancer cases keep on increasing with around 150 000 deaths yearly. Cancer therapy research is constantly evolving. Indeed, several studies explore new treatments or their combination with conventional cancer treatments. But, at the same time, complementary and alternative medicines, as osteopathy, remain little explored upon their role in the combination with conventional therapy.
Several studies showed indirect interaction between vagus nerve and cancer. Firstly, vagus nerve regulates homeostasis and immunity by reducing systemic inflammation while maintaining local inflammation and antitumor effects. Secondly, vagus nerve stimulation increases Heart Rate Variability (HRV). Moreover, a higher HRV is associated with an improvement of vital prognosis in cancer patients. Vagus nerve could be stimulated by noninvasive osteopathic manipulations.
This prospective, monocentric and randomized study is a collaboration between the Centre Hospitalier d’Avignon and the Institut de Formation en Ostéopathie du Grand Avignon. It focuses on using noninvasive osteopathic mobilizations to stimulate vagus nerve. Indeed, this study aims to evaluate effects of vagus nerve osteopathic stimulations on HRV in patients with lung cancer, colorectal cancer, Non Hodgkin Lymphoma or Multiple Myeloma. More specifically, this study will tell us whether vagus nerve noninvasive osteopathic stimulations induce increase of HRV associated with a decrease of systemic inflammation and an improvement of patient’s quality of life.
| 2364606 | ecrin-mdr-crc
Project description:OBJECTIVE:Heart rate variability (HRV) characterizes changes in autonomic nervous system function and varies with posttraumatic stress disorder (PTSD). In this study we developed a classifier based on heart rate (HR) and HRV measures, and improved classifier performance using a novel HR-based window segmentation. APPROACH:Single-channel ECG data were collected from 23 subjects with current PTSD, and 25 control subjects with no history of PTSD over 24?h. RR intervals were derived from these data, cleaned, and used to calculate HR and HRV metrics. These metrics were used as features in a logistic regression classifier. Performance was assessed via repeated random sub-sampling validation. To reduce noise and activity-related effects, we calculated features from five non-overlapping ten-minute quiescent segments of RR intervals defined by lowest HR, as well as random ten-minute segments as a control. MAIN RESULTS:Using a combination of the four most predictive features derived from quiescent segments we achieved a median area under the receiver operating curve (AUC) of 0.86 on out-of-sample test set data. This was significantly higher than the AUC using 24?h of data (0.72) or random segments (0.67). SIGNIFICANCE:These results demonstrate our segmentation approach improves the classification of PTSD from HR and HRV measures, and suggest the potential for tracking PTSD illness severity via objective physiological monitoring. Future studies should prospectively evaluate if classifier output changes significantly with worsening or effective treatment of PTSD.
| S-EPMC5530587 | biostudies-literature
Project description:BackgroundGreater variability in the estimated glomerular filtration rate (eGFR) is associated with higher mortality in patients with chronic kidney disease (CKD). Heart failure (HF) is common in CKD and may increase variability through changes in hemodynamic and volume regulation. We sought to determine if patients with vs without HF have higher kidney function variability in CKD, and to define the association with mortality.Methods and resultsPatients undergoing coronary angiography from 2003 to 2013 with an eGFR of less than 60 mL/min/1.73 m2 were evaluated from the Duke Databank for Cardiovascular Disease. Variability in the eGFR, measured as the coefficient of variation (CV) of residuals from the regression of eGFR vs time, was calculated spanning 3 months to 2 years after catheterization. Mortality was assessed 2 to 7 years after catheterization. Patients were grouped into 3 HF phenotypes: HF with reduced ejection fraction, HF with preserved ejection, and no HF. Regression was used to evaluate associations between HF phenotypes and variability in the eGFR and between variability in the eGFR and mortality rate with stratification by HF phenotype. Among 3767 participants, the median eGFR at baseline was 45 mL/min/1.73 m2 (interquartile range 33-53 mL/min/1.73 m2), and longitudinal measures of eGFR over 21 months had within-patient residual variability (CV) of 14% (9%-20%). In adjusted analyses, variability in the eGFR was greater in those with HF with preserved ejection (n = 695, CV difference 0.98%, 95% confidence interval 0.14%-1.81%) or HF with reduced ejection fraction (n = 800, CV difference 2.51%, 95% confidence interval 1.66%-3.37%) relative to no HF (n = 2272). In 3068 participants eligible for mortality analysis, the presence of HF and greater variability in the eGFR were each associated independently with higher mortality, but there was no evidence of interaction between variability in the eGFR and any HF phenotype (all P for interaction ≥.49).ConclusionsVariability in the eGFR is greater in patients with HF and associated with mortality. Prediction algorithms and classification schemes should consider not only static, but also dynamic eGFR variability in HF and CKD prognostication.
| S-EPMC9258722 | biostudies-literature
Project description:The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).
| S-EPMC5491979 | biostudies-literature
Project description:BACKGROUND:Heart rate variability (HRV), or variation in beat-to-beat intervals of the heart, is a quantitative measure of autonomic regulation of the cardiovascular system. Low HRV derived from electrocardiogram (ECG) recordings is reported to be related to physical frailty in older adults. Recent advances in wearable technology offer opportunities to more easily integrate monitoring of HRV into regular clinical geriatric health assessments. However, signals obtained from ECG versus wearable photoplethysmography (PPG) devices are different, and a critical first step preceding their widespread use is to determine whether HRV metrics derived from PPG devices also relate to older adults' physical function. OBJECTIVE:This study aimed to investigate associations between HRV measured with a wrist-worn PPG device, the Empatica E4 sensor, and validated clinical measures of both objective and self-reported physical function in a cohort of older adults living independently within a continuing care senior housing community. Our primary hypothesis was that lower HRV would be associated with lower physical function. In addition, we expected that HRV would explain a significant proportion of variance in measures of physical health status. METHODS:We evaluated 77 participants from an ongoing study of older adults aged between 65 and 95 years. The assessments encompassed a thorough examination of domains typically included in a geriatric health evaluation. We collected HRV data with the Empatica E4 device and examined bivariate correlations between HRV quantified with the triangular index (HRV TI) and 3 widely used and validated measures of physical functioning-the Short Physical Performance Battery (SPPB), Timed Up and Go (TUG), and Medical Outcomes Study Short Form 36 (SF-36) physical composite scores. We further investigated the additional predictive power of HRV TI on physical health status, as characterized by SF-36 physical composite scores and Cumulative Illness Rating Scale for Geriatrics (CIRS-G) scores, using generalized estimating equation regression analyses with backward elimination. RESULTS:We observed significant associations of HRV TI with SPPB (n=52; Spearman ?=0.41; P=.003), TUG (n=51; ?=-0.40; P=.004), SF-36 physical composite scores (n=49; ?=0.37; P=.009), and CIRS-G scores (n=52, ?=-0.43; P=.001). In addition, the HRV TI explained a significant proportion of variance in SF-36 physical composite scores (R2=0.28 vs 0.11 without HRV) and CIRS-G scores (R2=0.33 vs 0.17 without HRV). CONCLUSIONS:The HRV TI measured with a relatively novel wrist-worn PPG device was related to both objective (SPPB and TUG) and self-reported (SF-36 physical composite) measures of physical function. In addition, the HRV TI explained additional variance in self-reported physical function and cumulative illness severity beyond traditionally measured aspects of physical health. Future steps include longitudinal tracking of changes in both HRV and physical function, which will add important insights regarding the predictive value of HRV as a biomarker of physical health in older adults.
| S-EPMC6913722 | biostudies-literature
Project description:AimsThe prognostic significance of renal function variability has not been fully elucidated in heart failure (HF). This multicentre, prospective cohort study aimed to evaluate the usefulness of visit-to-visit variability in estimated glomerular filtration rate (eGFR) for predicting patients' outcomes in a real-world HF population.MethodsA total of 564 patients who had survived HF hospitalization were randomly assigned with a 2:1 ratio to derivation and validation cohorts, and they were then followed after discharge. Using the data for 6 months after discharge, each patient's visit-to-visit eGFR variability (EGV) was estimated. In the derivation cohort, Cox regression analyses were performed to assess the association of EGV with a subsequent composite event (death and HF hospitalization). In the validation cohort, the predictive performance was compared among Cox regression models with EGV, those with B-type natriuretic peptide (BNP) and those with eGFR.ResultsIn the derivation cohort (376 patients), median age, left ventricular ejection fraction (LVEF), BNP and eGFR at discharge were 72 years, 53.3%, 134.8 pg/mL and 58.7 mL/min/1.73 m2 , respectively. During a median follow-up of 2.2 years, higher EGV was associated with an increased risk of the composite event (adjusted hazard ratio [per standard deviation increase in log-transformed EGV], 1.5; 95% confidence interval, 1.1-2.0). A similar finding was observed in a stratified analysis by LVEF. In the validation cohort (188 patients), better model fit, discrimination, reclassification and calibration were observed for EGV than for 6-month averaged BNP or eGFR for predicting the composite event when added to HF risk prediction models. Adding EGV to models with BNP or eGFR improved model discrimination and reclassification.ConclusionsEGV predicts HF outcomes regardless of LVEF. Risk prediction models with EGV have good performance in real-world HF patients. The study findings highlight the clinical importance of observing visit-to-visit fluctuations in renal function in this population.
| S-EPMC8712897 | biostudies-literature
Project description:The association between physical fitness and cognitive performance has been widely investigated in the literature. However, the neurophysiological mechanisms underlying this relationship are not yet clear. Here, we aim to evaluate the interactions between executive function measures, heart rate variability (HRV), and physical fitness in the context of the neurovisceral integration (NVI) theory. Twenty-eight healthy elderly subjects (>60 years) were submitted to evaluation of executive performance with three computerized tests: the N-back test measured working memory capacity, the Stroop Color test evaluated inhibitory control and selective attention, and the Wisconsin Card Sorting Test (WCST) evaluated abstract reasoning and cognitive flexibility. We also used the Physical Testing Battery for the Elderly to measure aerobic capacity, dynamic balance, upper body flexibility, and handgrip strength. Our results confirm the relationship between executive function and physical fitness, particularly between working memory, cardiorespiratory fitness, and dynamic balance. We also demonstrate an association between executive performance and HRV in older people, corroborating previous results from other groups obtained in young adults. However, our regression models did not indicate that HRV mediates the relationship between cognition and physical fitness in the elderly, suggesting that age-related degeneration of autonomic control can affect aspects of NVI in this population.
| S-EPMC7068733 | biostudies-literature