Effect of measurement duration on accuracy of pulse-counting

Automated Heart Rate Detection in Seismocardiograms Using Electrocardiogram-Based Algorithms-A Feasibility Study

In recent decades, much work has been implemented in heart rate (HR) analysis using electrocardiographic (ECG) signals. We propose that algorithms developed to calculate HR based on detected R-peaks using ECG can be applied to seismocardiographic (SCG) signals, as they utilize common knowledge regarding heart rhythm and its underlying physiology. We implemented the experimental framework with methods developed for ECG signal processing and peak detection to be applied and evaluated on SCGs. Furthermore, we assessed and chose the best from all combinations of 15 peak detection and 6 preprocessing methods from the literature on the CEBS dataset available on Physionet. We then collected experimental data in the lab experiment to measure the applicability of the best-selected technique to the real-world data; the abovementioned method showed high precision for signals recorded during sitting rest (HR difference between SCG and ECG: 0.12 ± 0.35 bpm) and a moderate precision for signals recorded with interfering physical activity-reading out a book loud (HR difference between SCG and ECG: 6.45 ± 3.01 bpm) when compared to the results derived from the state-of-the-art photoplethysmographic (PPG) methods described in the literature. The study shows that computationally simple preprocessing and peak detection techniques initially developed for ECG could be utilized as the basis for HR detection on SCG, although they can be further improved.

Susceptibility to peer influence in adolescents: Associations between psychophysiology and behavior

The current study investigated in-the-moment links between adolescents' autonomic nervous system activity and susceptibility to three types of peer influence (indirect, direct, continuing) on two types of behavior (antisocial, prosocial). The sample included 144 racially ethnically diverse adolescents (46% male, 53% female, 1% other; M age  = 16.02 years). We assessed susceptibility to peer influence behaviorally using the Public Goods Game (PGG) while measuring adolescents' mean heart rate (MHR) and pre-ejection period (PEP). Three key findings emerged from bivariate dual latent change score modeling: (1) adolescents whose MHR increased more as they transitioned from playing the PGG alone (pre-influence) to playing while simply observed by peers (indirect influence) displayed more prosocial behavior; (2) adolescents whose PEP activity increased more (greater PEP activity = shorter PEP latency) as they transitioned from indirect influence to being encouraged by peers to engage in antisocial behavior (direct influence) engaged in more antisocial behavior; and (3) adolescents whose PEP activity decreased less as they transitioned from direct influence on prosocial behavior to playing the PGG alone again (continuing influence) displayed more continuing prosocial behavior (marginal effect). The discussion focuses on the role of psychophysiology in understanding adolescents' susceptibility to peer influence.

Integrated Biosignal Analysis to Provide Biomarkers for Recognizing Time Perception Difficulties

Background

Time perception refers to the capability to recognize the passage of time. The cerebellum is located at the back of the brain, underlying the occipital and temporal lobes. Dyschronometria is a cerebellar dysfunction, in which a person cannot precisely estimate the amount of time that has passed. Cardiac indicators such as heart rate (HR) variability have been associated with mental function in healthy individuals. Moreover, time perception has been previously studied concerning cardiac signs. Human time perception is influenced by various factors such as attention and drowsiness. An electroencephalogram (EEG) is a suitable modality for evaluating cortical reactions due to its affordability and usefulness. Because EEG has a high sequential outcome, it offers valuable data to explore variability in psychological situations. An electrocardiogram (ECG) records electrical signals from the heart to examine various heart conditions. The electromyography (EMG) technique detects electrical impulses produced by muscles.

Methods

EEG, ECG, and EMG are integrated during time perception. This study evaluated the human body's time perception through the neurological, cardiovascular, and muscular systems using a simple neurofeedback exercise after time perception tasks. The three biosignals which are EEG, ECG, and EMG were investigated to use them as biomarkers for recognizing time perception difficulty as the main goal of the study. Five healthy college students with no health issues participated, and their EEG, ECG, and EMG were recorded while relaxing and performing a time wall estimation task and neurofeedback training. Previous research has shown the relationship between EEG frequency bands and the frontal center during time perception. Investigating the connection between ECG, EEG, and EMG under time perception conditions is significant.

Results

The results show that ECG (HR), EEG (Delta wave), and EMG (root mean square) are critical features in time perception difficulties.

Conclusion

The ability and outcomes of multiple biomarkers might allow for improved diagnosis and monitoring of the progress of any treatment applications such as biofeedback training. Furthermore, those biomarkers could be used as useful for evaluating and treating dyschronometria.

The baroreceptor reflex brought to life outside the classroom - an e-learning based asynchronous laboratory class using a non-supervised modified Active Standing Test

BACKGROUND

E-learning based laboratory classes can replace or enhance in-classroom laboratories. They typically offer temporal flexibility, self-determined learning speed, repeatability and do not require supervision or face-to-face contact. The aim of this feasibility study was to investigate whether the established in-classroom laboratory class on the baroreceptor reflex (BRR) can be transformed into a new e-learning based asynchronous laboratory class for untrained, non-supervised students without medical equipment. The BRR is a fundamental cardiovascular process which is regularly visualized in physiology during in-classroom laboratories by a student-performed Active Standing Test (AST). During this voluntary provocation of orthostatic stress, the BRR reliably causes a solid rise in heart rate (HR) and a stabilization or even increase in blood pressure (BP).

METHODS

The conventional AST was modified by omission of BP measurements which would require medical devices and was embedded into a framework of interactive digital material allowing independent student performance. With specific adaptions, this instrument was implemented to 1st and 2nd year curricula of human medicine, dental medicine, midwifery and pharmacy. An audience response system was used to collect the students' data on HR, epidemiology, technical problems, satisfaction and orthostatic symptoms. As primary outcome, we investigated the students' correct performance of the modified AST regarding textbook conformity of the HR data. Secondary outcomes included technical feasibility, the students' satisfaction and consistency of HR data within predefined subgroups (e.g., gender, curricula). Descriptive statistics are reported.

RESULTS

The class was completed by 217 students (mean age: 23 ± 8 [SD], 81% female, 19% male). Mean reported rise of HR during standing was ~ 20 bpm (~ 30%) which is highly concordant to textbooks. Reported feasibility (~ 80% negated any technical issues) and students' satisfaction (4.4 on 5-point Likert-scale) were high. The HR data were consistent within the subgroups.

CONCLUSION

This study demonstrates that the highly relevant BRR can be successfully addressed in an e-learning based asynchronous laboratory class implementing a non-supervised AST restricted to HR measurements embedded in digital material. The robust HR response and the adjustable complexity allow an application to different healthcare-related curricula. This class, therefore, provides a broad audience access to a fundamental concept of cardiovascular physiology.

Heart Rate Changes Before, During, and After Treadmill Walking Exercise in Normal Dogs

In dogs, changes in heart rate (HR) can reflect conditioning, fear, anticipation, and pain; however, these are not routinely assessed in veterinary rehabilitation patients. Knowing the expected HR changes during rehabilitation exercises can guide protocols and can optimize post-operative therapy. The primary objectives of the study were to assess HR in dogs undergoing treadmill exercise (TE) during the walk and to compare the three collection techniques of HR, namely, auscultation, a HR monitor (HR MONITOR), and a Holter monitor (HOLTER). We hypothesized that the HR would increase by 20% during TE, that HR taken after TE would not be the same as the HR during TE, and that all methods of measurement would have good agreement. HR was recorded in all methods simultaneously, in eight adult healthy large breed dogs during rest (REST), immediately before TE (PRE), during TE (WALK), and 15 and 60 s after TE (POST-15, POST-60). Statistical analyses included Spearman and Pearson correlations, Bland-Altman analyses, and a repeated measures ANOVA with Sidak's post-hoc test (significant at value of p < 0.05). Increased HR was reflected in TE during WALK, and elevations in HR during WALK were not reflected in POST timepoints. Auscultation was also not possible during WALK. Significant moderate-to-strong correlations existed among all monitoring options at each of the timepoints (rho range = 0.5-0.9, p < 0.05). There were no correlations between peak HR and age or weight. The main limitation of this study is that only healthy and large breed dogs were used. Both monitors captured the increase in HR during exercise and could guide TE regimens to minimize patient risk of injury and to maximize training effectiveness.

Investigating the Effects of Brainstem Neuronal Adaptation on Cardiovascular Homeostasis

Central coordination of cardiovascular function is accomplished, in part, by the baroreceptor reflex, a multi-input multi-output physiological control system that regulates the activity of the parasympathetic and sympathetic nervous systems via interactions among multiple brainstem nuclei. Recent single-cell analyses within the brain revealed that individual neurons within and across brain nuclei exhibit distinct transcriptional states contributing to neuronal function. Such transcriptional heterogeneity complicates the task of understanding how neurons within and across brain nuclei organize and function to process multiple inputs and coordinate cardiovascular functions within the larger context of the baroreceptor reflex. However, prior analysis of brainstem neurons revealed that single-neuron transcriptional heterogeneity reflects an adaptive response to synaptic inputs and that neurons organize into distinct subtypes with respect to synaptic inputs received. Based on these results, we hypothesize that adaptation of neuronal subtypes support robust biological function through graded cellular responses. We test this hypothesis by examining the functional impact of neuronal adaptation on parasympathetic activity within the context of short-term baroreceptor reflex regulation. In this work, we extend existing quantitative closed-loop models of the baroreceptor reflex by incorporating into the model distinct input-driven neuronal subtypes and neuroanatomical groups that modulate parasympathetic activity. We then use this extended model to investigate, via simulation, the functional role of neuronal adaptation under conditions of health and systolic heart failure. Simulation results suggest that parasympathetic activity can be modulated appropriately by the coordination of distinct neuronal subtypes to maintain normal cardiovascular functions under systolic heart failure conditions. Moreover, differing degrees of adaptation of these neuronal subtypes contribute to cardiovascular behaviors corresponding to distinct clinical phenotypes of heart failure, such as exercise intolerance. Further, our results suggest that an imbalance between sympathetic and parasympathetic activity regulating ventricular contractility contributes to exercise intolerance in systolic heart failure patients, and restoring this balance can improve the short-term cardiovascular performance of these patients.

Evaluation of a Tap-Based Smartphone App for Heart Rate Assessment During Asphyxia in a Porcine Model of Neonatal Resuscitation

Objectives: Heart rate (HR) is the most significant parameter to assess a newborn's clinical status at birth. Recently, novel technologies including smartphone applications have been suggested for HR assessment during neonatal resuscitation. The aim of this study was to evaluate the accuracy, speed, and precision of the NeoTapLifeSupport (NeoTapLS) smartphone application using a digital stethoscope (DS) for HR assessment during neonatal resuscitation. Design: Newborn piglets (n = 20, 1-3 days, 1.7-2.4 kg) were anesthetized, intubated, mechanically ventilated, and subjected to 30 min of hypoxia, followed by asphyxia. Asphyxia was induced by clamping the endotracheal tube and disconnecting the ventilator, until asystole was confirmed by zero carotid blood flow (CBF). Setting: Experimental setting. Subjects: Asphyxia-induced newborn piglets. Interventions: During asphyxia, HR assessments were performed with a DS using the NeoTapLS smartphone application, and compared to 6-s method (6 s), and 10-s method (10 s). Measurements and Main Results: Accuracy of obtained HRs was compared to CBF and electrocardiogram and assessment time using NeoTapLS, 6 s, and 10 s were also measured. The mean(SD) HR with the NeoTapLS was 68(26), compared to CBF with 68(27) bpm, 6 s with 68(27), and 10 s with 66(26) bpm during asphyxia. Bland-Altman analysis revealed no difference between HR using the NeoTapLS, 6 s, 10 s, compared to CBF HR, with NeoTapLS showing the smallest difference between 95% limits of agreement. The median (IQR) time required to obtain a HR using the NeoTapLS was 3(2-4) s, compared to 6(6-7), and 10(10-11) s for 6 and 10 s, respectively. Conclusions: Our data suggests that the NeoTapLS is accurate, fast, and precise during neonatal asphyxia to assess heart rate.

Association between Resting Heart Rate and Colorectal Cancer: Results from a Case-Controlled Study

Previous studies evaluating associations between resting heart rate (RHR) and cancer-related mortality/prognosis have yielded conflicting results. We investigated whether elevations in RHR are associated with colorectal cancer (CRC). We conducted a case-controlled study involving 1241 CRC patients and 5909 cancer-free controls from the Korean National Health and Nutrition Examination Survey. After propensity score (PS) matching, 1207 CRC patients and 1207 matched controls were analyzed. Associations between RHR and CRC, colon, and rectal cancer were analyzed in appropriate patient subgroups using multiple and conditional logistic regression. Receiver operating characteristics analysis yielded the optimal RHR cut-point to predict CRC. RHR was significantly higher in CRC, colon, and rectal cancer patients than in controls (72.7 bpm in CRC, 72.8 bpm in colon cancer, 72.3 bpm in rectal cancer, and 68.7 bpm in controls; all p < 0.001). Analysis of data prior to PS matching yielded the following odds ratios (ORs) per RHR increment for CRC, colon, and rectal cancer: 1.043 (95% confidence intervals (CIs): 1.036–1.049), 1.045 (95% CI: 1.037–1.053), and 1.040 (95% CI: 1.030–1.051), respectively, in unadjusted models, and 1.043 (95% CI: 1.034–1.051), 1.046 (95% CI: 1.037–1.055), and 1.040 (95% CI: 1.027–1.052), respectively, in multivariable adjusted models. Patients with CRC, colon, and rectal cancer have a significantly higher RHR compared to cancer-free controls.

Measurement error and timing of predictor values for multivariable risk prediction models are poorly reported

OBJECTIVE

Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use.

METHODS

A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error, and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risks.

RESULTS

Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorized as high risk of error; however, this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured.

CONCLUSION

Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions.

Resting heart rate, heart rate reserve, and metabolic syndrome in professional firefighters: A cross-sectional study

BACKGROUND

Little is known about the associations of resting heart rate (RHR) and heart rate reserve (HRR) with metabolic syndrome (MetS) in firefighters.

METHODS

For each of 288 professional firefighters, HRR was calculated as the difference between measured RHR and estimated maximum HR. For comparison, VO₂ max based on a treadmill test was included. MetS was defined according to the NCEP/ATP III criteria.

RESULTS

The prevalence of MetS was 14.2%. The average of RHR was 61.5 beat/min. Only 5.8% of the firefighters had RHR of ≥80 beat/min. Between the firefighters in the lowest and highest quintiles, the prevalence ratios (95% confidence intervals) for MetS were 1.88 (0.71-4.94), 5.90 (1.74-20.02), and 8.03 (1.86-34.75) for RHR, HRR, and VO₂ max, respectively. Both HRR and VO₂ max, but not RHR, were significantly associated with MetS and its most component risk factors in middle-aged firefighters.

CONCLUSIONS

HRR, a simple cardiovascular fitness measure, was inversely associated with MetS among middle-aged professional firefighters.

How Well Are Pulses Measured? Practice-Based Evidence from an Observational Study of Acutely Ill Medical Patients During Hospital Admission

BACKGROUND

Although taking a radial pulse is considered to be an essential clinical skill, there have been few reports on how well it is measured in clinical practice, and how its accuracy and precision are influenced by rate, rhythm, and blood pressure.

METHODS

This study is a retrospective quality audit carried out as part of a larger ongoing prospective observational trial. The radial pulse rates recorded by 2 research nurses were compared with the electrocardiogram (ECG) heart rates measured on acutely ill medical patients during their admission to a resource-poor hospital in sub-Saharan Africa.

RESULTS

There were 619 ECGs performed on 231 patients while they were in the hospital. The median interval between measuring the vital signs and obtaining an ECG was 12.6 minutes (mean 62.3, SD 104.3 minutes). The correlation coefficient between the pulse rate recorded and ECG heart rate was 0.54. The bias between the pulse rate and the ECG heart rate was 1.34, SD 13.51 beats per minute (ie, limits of agreement 26.5 beats per minute). Bias and variance were not influenced by blood and pulse pressure. However, tachycardia increased the variance and was the only independent predictor of a pulse deficit (odds ratio 2.32; 95% confidence interval, 1.53-3.51; chi-squared 17.21; P < .0001).

CONCLUSION

Practice-based evidence shows that in acutely ill patients, there is a poor correlation between the radial pulse and the ECG heart rate, and that tachycardia increases the variance and is the only independent predictor of a pulse deficit.

Cross-validation of Peak Oxygen Consumption Prediction Models From OMNI Perceived Exertion

This study cross-validated statistical models for prediction of peak oxygen consumption using ratings of perceived exertion from the Adult OMNI Cycle Scale of Perceived Exertion. 74 participants (men: n=36; women: n=38) completed a graded cycle exercise test. Ratings of perceived exertion for the overall body, legs, and chest/breathing were recorded each test stage and entered into previously developed 3-stage peak oxygen consumption prediction models. There were no significant differences (p>0.05) between measured and predicted peak oxygen consumption from ratings of perceived exertion for the overall body, legs, and chest/breathing within men (mean±standard deviation: 3.16±0.52 vs. 2.92±0.33 vs. 2.90±0.29 vs. 2.90±0.26 L·min(-1)) and women (2.17±0.29 vs. 2.02±0.22 vs. 2.03±0.19 vs. 2.01±0.19 L·min(-1)) participants. Previously developed statistical models for prediction of peak oxygen consumption based on subpeak OMNI ratings of perceived exertion responses were similar to measured peak oxygen consumption in a separate group of participants. These findings provide practical implications for the use of the original statistical models in standard health-fitness settings.