UNASSIGNED: Advancements in medical technologies have led to the development of contact-free methods of haemodynamic monitoring such as remote photoplethysmography (rPPG). rPPG uses video cameras to interpret variations in skin colour related to blood flow, which are analysed to generate vital signs readings. rPPG potentially ameliorates problems like fretfulness and fragile skin contact associated with conventional probes in children. While rPPG has been validated in adults, no prior validation has been performed in children.
UNASSIGNED: A two-phased prospective cross-sectional single-centre study was conducted from January to April 2023 to evaluate the feasibility, acceptability, and accuracy of obtaining heart rate (HR), respiratory rate (RR) and oxygen saturation (SpO2) using rPPG in children, compared to the current standard of care. In Phase 1, we recruited patients ≤16 years from the neonatal and paediatric wards. We excluded preterm neonates with gestational age <35 weeks and newborns <24 hours old. The rPPG webcam was positioned 30 cm from the face. After 1 minute of facial scanning, readings generated were compared with pulse oximetry for HR and SpO2, and manual counting for RR. Correlation and Bland-Altman analyses were performed. In Phase 2, we focused on the population in whom there was potential correlation between rPPG and the actual vital signs.
UNASSIGNED: Ten neonates and 28 children aged 5 to 16 years were recruited for Phase 1 (765 datapoints). All patients were haemodynamically stable and normothermic. Patients and caregivers showed high acceptability to rPPG. rPPG values were clinically discrepant for children <10 years. For those ≥10 years, moderate correlation was observed for HR, with Spearman\'s correlation coefficient (Rs) of 0.50 [95% confidence intervals (CI): 0.42, 0.57]. We performed Phase 2 on 23 patients aged 12 to 16 years (559 datapoints). Strong correlation was observed for HR with Rs=0.82 (95% CI: 0.78, 0.85). There was weak correlation for SpO2 and RR (Rs=-0.25 and -0.02, respectively).
UNASSIGNED: Our study showed that rPPG is acceptable and feasible for neonates and children aged 5 to 16 years, and HR values in older children aged 12 to 16 years correlated well with the current standard. The rPPG algorithms need to be further refined for younger children, and for obtaining RR and SpO2 in all children. If successful, rPPG will provide a viable contact-free alternative for assessing paediatric vital signs, with potential use in remote monitoring and telemedicine.

In recent decade, wearable digital devices have shown potentials for the discovery of novel biomarkers of humans\' physiology and behavior. Heart rate (HR) and respiration rate (RR) are most crucial bio-signals in humans\' digital phenotyping research. HR is a continuous and non-invasive proxy to autonomic nervous system and ample evidence pinpoints the critical role of respiratory modulation of cardiac function. In the present study, we recorded longitudinal (7 days, 4.63 ± 1.52) HR and RR of 89 freely behaving human subjects (Female: 39, age 57.28 ± 5.67, Male: 50, age 58.48 ± 6.32) and analyzed their dynamics using linear models and information theoretic measures. While HR\'s linear and nonlinear characteristics were expressed within the plane of the HR-RR directed flow of information (HR→RR - RR→HR), their dynamics were determined by its RR→HR axis. More importantly, RR→HR quantified the effect of alcohol consumption on individuals\' cardiorespiratory function independent of their consumed amount of alcohol, thereby signifying the presence of this habit in their daily life activities. The present findings provided evidence for the critical role of the respiratory modulation of HR, which was previously only studied in non-human animals. These results can contribute to humans\' phenotyping research by presenting RR→HR as a digital diagnosis/prognosis marker of humans\' cardiorespiratory pathology.

BACKGROUND: Twenty-four-hour heart rate (HR) integrates multiple physiological and psychological systems related to health and well-being, and can be continuously monitored in high temporal resolution over several days with wearable HR monitors. Using HR data from two independent datasets of cancer patients and their caregivers, we aimed to identify dyadic and individual patterns of 24 h HR variation and assess their relationship to demographic, environmental, psychological, and clinical variables of interest.
METHODS: a novel regularized approach to high-dimensional canonical correlation analysis (CCA) was used to identify factors reflecting dyadic and individual variation in the 24 h (circadian) HR trajectories of 430 people in 215 dyads, then regression analysis was used to relate these patterns to explanatory variables.
RESULTS: Four distinct factors of dyadic covariation in circadian HR were found, contributing approximately 7% to overall circadian HR variation. These factors, along with non-dyadic factors reflecting individual variation exhibited diverse and statistically robust patterns of association with explanatory variables of interest.
CONCLUSIONS: Both dyadic and individual anomalies are present in the 24 h HR patterns of cancer patients and their caregivers. These patterns are largely synchronous, and their presence robustly associates with multiple explanatory variables. One notable finding is that higher mood scores in cancer patients correspond to an earlier HR nadir in the morning and higher HR during the afternoon.

UNASSIGNED: Resting heart rate (HR) and heart rate variability (HRV) have been linked with cognition in the general population and in older individuals. The knowledge of this aspect of heart-brain relationship is relatively absent in older individuals with early Alzheimer\'s disease (AD) pathology. This study explores relationships of the HR, HRV, and cognition in cognitively healthy individuals with pathological amyloid/tau ratio (CH-PATs) in cerebral spinal fluid (CSF) compared to those with normal ratio (CH-NATs).
UNASSIGNED: We examined therelationshipsbetween1) resting HR and Mini-Mental State Examination (MMSE); 2) resting HR and brain processing during Stroop interference; and 3) resting vagally mediated HRV (vmHRV) and task switching performance.
UNASSIGNED: Our studies showed that compared to CH-NATs, those CH-PATs with higher resting HR presented with lower MMSE, and less brain activation during interference processing. In addition, resting vmHRV was significantly correlated with task switching accuracy in CH-NATs, but not in CH-PATs.
UNASSIGNED: Thesethreedifferenttestsindicatedysfunctionalheart-brainconnections in CH-PATs, suggesting a potential cardio-cerebral dysfunctional integration.

A new method for accurately estimating heart rates based on a single photoplethysmography (PPG) signal and accelerations is proposed in this study, considering motion artifacts due to subjects\' hand motions and walking. The method comprises two sub-algorithms: pre-quality checking and motion artifact removal (MAR) via Hankel decomposition. PPGs and accelerations were collected using a wearable device equipped with a PPG sensor patch and a 3-axis accelerometer. The motion artifacts caused by hand movements and walking were effectively mitigated by the two aforementioned sub-algorithms. The first sub-algorithm utilized a new quality-assessment criterion to identify highly noise-contaminated PPG signals and exclude them from subsequent processing. The second sub-algorithm employed the Hankel matrix and singular value decomposition (SVD) to effectively identify, decompose, and remove motion artifacts. Experimental data collected during hand-moving and walking were considered for evaluation. The performance of the proposed algorithms was assessed using the datasets from the IEEE Signal Processing Cup 2015. The obtained results demonstrated an average error of merely 0.7345 ± 8.1129 beats per minute (bpm) and a mean absolute error of 1.86 bpm for walking, making it the second most accurate method to date that employs a single PPG and a 3-axis accelerometer. The proposed method also achieved the best accuracy of 3.78 bpm in mean absolute errors among all previously reported studies for hand-moving scenarios.

Environmental pollutants exposure might disrupt cardiac function, but evidence about the associations of per- and polyfluoroalkyl substances (PFASs) exposure and cardiac conduction system remains sparse. To explore the associations between serum PFASs exposure and electrocardiogram (ECG) parameters changes in adults, we recruited 1229 participants (mean age: 55.1 years) from communities of Guangzhou, China. 13 serum PFASs with detection rate > 85% were analyzed finally. We selected 6 ECG parameters [heart rate (HR), PR interval, QRS duration, Bazett heart rate-corrected QT interval (QTc), QRS electric axis and RV5 + SV1 voltage] as outcomes. Generalized linear models (GLMs) and Bayesian kernel machine regression (BKMR) model were conducted to explore the associations of individual and joint PFASs exposure and ECG parameters changes, respectively. We detected significant associations of PFASs exposure with decreased HR, QRS duration, but with increased PR interval. For example, at the 95th percentile of 6:2 Cl-PFESA, HR and QRS duration were - 6.98 [95% confidence interval (CI): - 9.07, - 4.90] and - 6.54(95% CI: -9.05, -4.03) lower, but PR interval was 7.35 (95% CI: 3.52, 11.17) longer than those at the 25th percentile. Similarly, significant joint associations were observed in HR, PR interval and QRS duration when analyzed by BKMR model.

Purpose: To improve the accuracy of cerebral blood flow (CBF) measurement in mice by accounting for the anesthesia effects. Methods: The dependence of CBF on anesthesia dose and time was investigated by simultaneously measuring respiration rate (RR) and heart rate (HR) under four different anesthetic regimens. Quantitative CBF was measured by a phase-contrast (PC) MRI technique. RR was evaluated with a mouse monitoring system (MouseOX) while HR was determined using an ultrashort-TE MRI sequence. CBF, RR, and HR were recorded dynamically with a temporal resolution of 1 min in a total of 19 mice. Linear regression models were used to investigate the relationships among CBF, anesthesia dose, RR, and HR. Results: CBF, RR, and HR all showed a significant dependence on anesthesia dose (p < 0.0001). However, the dose in itself was insufficient to account for the variations in physiological parameters, in that they showed a time-dependent change even for a constant dose. RR and HR together can explain 52.6% of the variations in CBF measurements, which is greater than the amount of variance explained by anesthesia dose (32.4%). Based on the multi-parametric regression results, a model was proposed to correct the anesthesia effects in mouse CBF measurements, specifically C B F c o r r e c t e d = C B F + 0.58 R R - 0.41 H R - 32.66 D o s e . We also reported awake-state CBF in mice to be 142.0 ± 8.8 mL/100 g/min, which is consistent with the model-predicted value. Conclusion: The accuracy of CBF measurement in mice can be improved by using a correction model that accounts for respiration rate, heart rate, and anesthesia dose.

Objective. The imaging photoplethysmography (IPPG), which is applied to heart rate measurement, is susceptible to interference caused by illumination variations during photography. To improve the accuracy, robustness, and real-time performance of IPPG, a new method combined with modified ensemble empirical mode decomposition (EEMD) and fast independent component analysis (FastICA) was proposed.Approach. On the modified EEMD, to reduce the error caused by the residual white noise of the algorithm, it was characterized by recurrently updating zero-mean white noise for ensemble averaging based on the standard deviation of the input signal. On the modified FastICA, its constructed nonlinear function was superseded by Huber\'s approximation function to improve the robustness and running speed.Main results. Comparison experiments were conducted between the MAHNOB-HCI database and own collected data. In the hybrid natural light and computer screen light scenario, the mean absolute error (MAE) of heart rate amounted to 0.93 beats per minute and the correlation coefficientrreached 0.85. In the experiments of MAHNOB-HCI database, the MAE amounted to 6.03 beats per minute and the correlation coefficientrreached 0.75. Furthermore, the modified method decreased the running time by approximately ten times compared to the original algorithms.Significance. Various experimental results demonstrated that the proposed method significantly improves the accuracy, timeliness, and interference resistance.

Introduction: Autonomic nervous system (ANS) function quantified by heart rate variability (HRV) was associated with long-term prognosis, but it was rarely used in the evaluation of patients with heart failure, especially those with cardiac resynchronization therapy-defibrillator (CRT-D) implantation. This study aimed to describe the changes in ANS function among patients who underwent CRT-D with remote home monitoring function, and explore predictive value of HRV for ventricular tachyarrhythmias (VTAs) and all-cause mortality. Method: Patients who underwent CRT-D implantation were included. Device-measured all-day HR, night-time HR, and HRV (measured by the standard deviation of the atrial-atrial sensed intervals) were used to quantify ANS function. Multivariate Cox proportional hazards models were fitted to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) of VTAs or all-cause mortality in relation to ANS function at baseline and 6 months post-implantation. The cutoff value was determined using restrictive cubic splines. Multivariable logistic regression was further established to determine factors influencing postoperative HRV. Results: A total of 170 patients treated with CRT-D were eligible for analysis. During a median follow-up period of 50.8 months, 61 patients died and 69 patients experienced at least one spontaneous episode of VTAs. At 6 months after CRT implantation, 114 patients showed improvement in HRV, increasing from 66.4 ± 19.4 ms to 76.7 ± 21.2 ms. The postoperative HRV was associated with both all-cause mortality (HRs: 0.983; 95% CI: 0.968 to 0.998, p = 0.012) and VTAs (HRs: 0.973; 95% CI: 0.954 to 0.993, p = 0.008), and the relative risk would significantly increase when the postoperative HRV lower than 75 ms. After adjusting for basic ANS function and possible influencing factors, patients without diabetes (p = 0.018) and with higher daily physical activity (p = 0.041) could maintain higher postoperative HRV after CRT implantation. Conclusion: More than two-thirds of heart failure patients showed improvement in ANS function following CRT treatment. However, patients with diabetes and low daily physical activity levels have difficulty maintaining a higher postoperative HRV, which is associated with a worse clinical outcome.

BACKGROUND: The imaging photoplethysmography (iPPG) method is a non-invasive, non-contact measurement method that uses a camera to detect physiological indicators. On the other hand, wearing a mask has become essential today when COVID-19 is rampant, which has become a new challenge for heart rate (HR) estimation from facial videos recorded by a camera.
OBJECTIVE: The aim is to propose an iPPG-based method that can accurately estimate HR with or without a mask.
METHODS: First, the facial regions of interest (ROI) were divided into two sub-ROIs, and the original signal was obtained through spatial averaging with different weights according to the result of judging whether wearing a mask or not, and the CDF, which emphasizes the main component signal, was combined with the improved POS suitable for real-time HR estimation to obtain the noise-removed BVP signal.
RESULTS: For self-collected data while wearing a mask, MAE, RMSE, and ACC were 1.09 bpm, 1.44 bpm, and 99.08%, respectively.
CONCLUSIONS: Experimental results show that the proposed framework can estimate HR stably in real-time in both cases of wearing a mask or not. This study expands the application range of HR estimation based on facial videos and has very practical value in real-time HR estimation in daily life.