-
Physiological Measurement Aug 2020Heart rate variability has been largely used for the assessment of cardiac autonomic activity, due to the direct relationship between cardiac rhythm and the activity of... (Review)
Review
Heart rate variability has been largely used for the assessment of cardiac autonomic activity, due to the direct relationship between cardiac rhythm and the activity of the sympathetic and parasympathetic nervous system. In recent years, another technique, pulse rate variability, has been used for assessing heart rate variability information from pulse wave signals, especially from photoplethysmography, a non-invasive, non-intrusive, optical technique that measures the blood volume in tissue. The relationship, however, between pulse rate variability and heart rate variability is not entirely understood, and the effects of cardiovascular changes in pulse rate variability have not been thoroughly elucidated. In this review, a comprehensive summary of the applications in which pulse rate variability has been used, with a special focus on cardiovascular health, and of the studies that have compared heart rate variability and pulse rate variability is presented. It was found that the relationship between heart rate variability and pulse rate variability is not entirely understood yet, and that pulse rate variability might be influenced not only due to technical aspects but also by physiological factors that might affect the measurements obtained from pulse-to-pulse time series extracted from pulse waves. Hence, pulse rate variability must not be considered as a valid surrogate of heart rate variability in all scenarios, and care must be taken when using pulse rate variability instead of heart rate variability. Specifically, the way pulse rate variability is affected by cardiovascular changes does not necessarily reflect the same information as heart rate variability, and might contain further valuable information. More research regarding the relationship between cardiovascular changes and pulse rate variability should be performed to evaluate if pulse rate variability might be useful for the assessment of not only cardiac autonomic activity but also for the analysis of mechanical and vascular autonomic responses to these changes.
Topics: Autonomic Nervous System; Cardiovascular System; Heart Rate; Humans; Parasympathetic Nervous System; Photoplethysmography
PubMed: 32498055
DOI: 10.1088/1361-6579/ab998c -
Annual International Conference of the... Jul 2023The worldwide adoption of telehealth services may benefit people who otherwise would not be able to access mental health support. In this paper, we present a novel...
The worldwide adoption of telehealth services may benefit people who otherwise would not be able to access mental health support. In this paper, we present a novel algorithm to obtain reliable pulse and respiration signals from non-contact facial image sequence analysis. The proposed algorithm involved a skin pixel extraction method in the image processing part and signal reconstruction using the spectral information of RGB signal in the signal processing part. The algorithm was tested on 15 healthy subjects in a laboratory setting. The results show that the proposed algorithm can accurately monitor respiration rate (RR), pulse rate (PR), and pulse rate variability (PRV) in rest conditions.Clinical Relevance- The main achievement of this study is enabling non-contact PR and RR signal extraction from facial image sequences, which has potential for future use and support for psychiatrists in telepsychiatry.
Topics: Humans; Heart Rate; Pulse; Photoplethysmography; Psychiatry; Telemedicine
PubMed: 38083147
DOI: 10.1109/EMBC40787.2023.10340913 -
Economics and Human Biology Aug 2022A growing literature identifies associations between subjective and biometric indicators of wellbeing. These associations, together with the ability of subjective...
A growing literature identifies associations between subjective and biometric indicators of wellbeing. These associations, together with the ability of subjective wellbeing metrics to predict health and behavioral outcomes, have spawned increasing interest in wellbeing as an important concept in its own right. However, some social scientists continue to question the usefulness of wellbeing metrics. We contribute to this literature in three ways. First, we introduce a biometric measure of wellbeing - pulse - that hs been little used. Using nationally representative data on 165,000 individuals from the Health Survey for England and Scottish Health Surveys we show that its correlates are similar in a number of ways to those for happiness, and that it is highly correlated with wellbeing metrics, as well as self-assessed health. Second, we examine the determinants of pulse rates in mid-life (age 42) among the 9000 members of the National Child Development Study, a birth cohort born in a single week in 1958 in Britain. Third, we track the impact of pulse measured in mid-life (age 42) on health and labor market outcomes at age 50 in 2008 and age 55 in 2013. The probability of working at age 55 is negatively impacted by pulse rate a decade earlier. The pulse rate has an impact over and above chronic pain measured at age 42. General health at 55 is lower the higher the pulse rate at age 42, while those with higher pulse rates at 42 also express lower life satisfaction and more pessimism about the future at age 50. Taken together, these results suggest social scientists can learn a great deal by adding pulse rates to the metrics they use when evaluating people's wellbeing.
Topics: Adult; Biometry; Child; Happiness; Heart Rate; Humans; Middle Aged; Quality of Life; Surveys and Questionnaires
PubMed: 35461029
DOI: 10.1016/j.ehb.2022.101141 -
Acta Paediatrica (Oslo, Norway : 1992) Jun 2022Heart rate (HR) is the most important parameter to evaluate newborns' clinical condition and to guide intervention during resuscitation at birth. The present study aims...
AIM
Heart rate (HR) is the most important parameter to evaluate newborns' clinical condition and to guide intervention during resuscitation at birth. The present study aims to compare the accuracy of NeoBeat dry-electrode ECG for HR measurement with conventional ECG and pulse oximetry (PO).
METHODS
Newborns with a gestational age ≥32 weeks and/or birth weight ≥1.5 kg were included when HR evaluation was needed. HR was simultaneously measured for 10 min with NeoBeat, PO and conventional ECG.
RESULTS
A total of 18 infants were included (median (IQR) gestational age 39 (36-39) weeks and birth weight 3 150 (2 288-3 859) grams). Mean (SD) duration until NeoBeat obtained a reliable signal was 2.5 (9.0) s versus 58.5 (171.0) s for PO. Mean difference between NeoBeat and ECG was 1.74 bpm (LoA -4.987-8.459 and correlation coefficient 0.98). Paired HR measurements over 30-s intervals revealed no significant difference between NeoBeat and ECG. The positive predictive value of a detected HR <100 bpm by NeoBeat compared with ECG was 54.84%, negative predictive value 99.99%, sensitivity 94.44%, specificity 99.99% and accuracy 99.85%.
CONCLUSIONS
HR measurement with NeoBeat dry-electrode ECG at birth is reliable and accurate.
Topics: Adult; Birth Weight; Electrocardiography; Electrodes; Female; Heart Rate; Humans; Infant; Infant, Newborn; Oximetry
PubMed: 34981852
DOI: 10.1111/apa.16242 -
PloS One 2022Vital signs follow circadian patterns in both healthy volunteers and critically ill patients, which seem to be influenced by disease severity in the latter. In this...
RATIONALE
Vital signs follow circadian patterns in both healthy volunteers and critically ill patients, which seem to be influenced by disease severity in the latter. In this study we explored the existence of circadian patterns in heart rate, respiratory rate and skin temperature of hospitalized COVID-19 patients, and aimed to explore differences in circadian rhythm amplitude during patient deterioration.
METHODS
We performed a retrospective study of COVID-19 patients admitted to the general ward of a tertiary hospital between April 2020 and March 2021. Patients were continuously monitored using a wireless sensor and fingertip pulse oximeter. Data was divided into three cohorts: patients who recovered, patients who developed respiratory insufficiency and patients who died. For each cohort, a population mean cosinor model was fitted to detect rhythmicity. To assess changes in amplitude, a mixed-effect cosinor model was fitted.
RESULTS
A total of 429 patients were monitored. Rhythmicity was observed in heartrate for the recovery cohort (p<0.001), respiratory insufficiency cohort (p<0.001 and mortality cohort (p = 0.002). Respiratory rate showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.18 and p = 0.51). Skin temperature also showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.22 and p = 0.12). For respiratory insufficiency, only the amplitude of heart rate circadian pattern increased slightly the day before (1.2 (99%CI 0.16-2.2, p = 0.002)). In the mortality cohort, the amplitude of heart rate decreased (-1.5 (99%CI -2.6- -0.42, p<0.001)) and respiratory rate amplitude increased (0.72 (99%CI 0.27-1.3, p = 0.002) the days before death.
CONCLUSION
A circadian rhythm is present in heart rate of COVID-19 patients admitted to the general ward. For respiratory rate and skin temperature, rhythmicity was only found in patients who recover, but not in patients developing respiratory insufficiency or death. We found no consistent changes in circadian rhythm amplitude accompanying patient deterioration.
Topics: COVID-19; Circadian Rhythm; Heart Rate; Humans; Respiratory Insufficiency; Respiratory Rate; Retrospective Studies; Skin Temperature
PubMed: 35797369
DOI: 10.1371/journal.pone.0268065 -
Minerva Medica Oct 2022Isolated systolic hypertension in the young (ISHY) remains a challenging problem, partly due to the differences in central aortic pressure observed in studies... (Review)
Review
Isolated systolic hypertension in the young (ISHY) remains a challenging problem, partly due to the differences in central aortic pressure observed in studies investigating ISHY. The fundamental relationship between heart rate and central aortic pressure, and more precisely, the relationship between heart rate and amplification of central aortic pressure in the periphery, underpins the assessment and, as a consequence, the treatment of ISHY. Physiology warrants that an increase in heart rate would lead to increased amplification of the pressure pulse between the aorta and the brachial artery. Heart rate generally decreases with age, in particular over the first two decades of life. Thus, a higher heart rate in the young would result in higher pulse pressure amplification, and therefore an elevated brachial systolic pressure would not necessarily translate to elevated aortic systolic pressure. However, elevated heart rate is not a consistent feature in ISHY, and studies have shown that ISHY can present with either high or low central aortic systolic pressure. In this brief review, we summarize the physiological aspects underlying the relationship between heart rate and central aortic blood pressure and its amplification in the brachial artery, how this relationship changes with age, and examine the implications of these effects on the assessment and treatment of ISHY.
Topics: Humans; Arterial Pressure; Heart Rate; Isolated Systolic Hypertension
PubMed: 34333956
DOI: 10.23736/S0026-4806.21.07631-X -
Psychosomatic Medicine Sep 2023Heart rate is a transdiagnostic correlate of affective states and the stress diathesis model of health. Although most psychophysiological research has been conducted in...
OBJECTIVE
Heart rate is a transdiagnostic correlate of affective states and the stress diathesis model of health. Although most psychophysiological research has been conducted in laboratory environments, recent technological advances have provided the opportunity to index pulse rate dynamics in real-world environments with commercially available mobile health and wearable photoplethysmography (PPG) sensors that allow for improved ecologically validity of psychophysiological research. Unfortunately, adoption of wearable devices is unevenly distributed across important demographic characteristics, including socioeconomic status, education, and age, making it difficult to collect pulse rate dynamics in diverse populations. Therefore, there is a need to democratize mobile health PPG research by harnessing more widely adopted smartphone-based PPG to both promote inclusivity and examine whether smartphone-based PPG can predict concurrent affective states.
METHODS
In the current preregistered study with open data and code, we examined the covariation of smartphone-based PPG and self-reported stress and anxiety during an online variant of the Trier Social Stress Test, as well as prospective relationships between PPG and future perceptions of stress and anxiety in a sample of 102 university students.
RESULTS
Smartphone-based PPG significantly covaries with self-reported stress and anxiety during acute digital social stressors. PPG pulse rate was significantly associated with concurrent self-reported stress and anxiety ( b = 0.44, p = .018) as well as prospective stress and anxiety at the subsequent time points, although the strength of this association diminished the farther away pulse rate got from self-reported stress and anxiety (lag 1 model: b = 0.42, p = .024; lag 2 model: b = 0.38, p = .044).
CONCLUSIONS
These findings indicate that PPG provides a proximal measure of the physiological correlates of stress and anxiety. Smartphone-based PPG can be used as an inclusive method for diverse populations to index pulse rate in remote digital study designs.
Topics: Humans; Heart Rate; Photoplethysmography; Smartphone; Prospective Studies; Anxiety
PubMed: 37409791
DOI: 10.1097/PSY.0000000000001178 -
Applied Psychophysiology and Biofeedback Sep 2022Pulse rate variability is a physiological parameter that has been extensively studied and correlated with many physical ailments. However, the phase relationship between...
Pulse rate variability is a physiological parameter that has been extensively studied and correlated with many physical ailments. However, the phase relationship between inter-beat interval, IBI, and breathing has very rarely been studied. Develop a technique by which the phase relationship between IBI and breathing can be accurately and efficiently extracted from photoplethysmography (PPG) data. A program based on Lock-in Amplifier technology was written in Python to implement a novel technique, Dynamic Phase Extraction. It was tested using a breath pacer and a PPG sensor on 6 subjects who followed a breath pacer at varied breathing rates. The data were then analyzed using both traditional methods and the novel technique (Dynamic Phase Extraction) utilizing a breath pacer. Pulse data was extracted using a PPG sensor. Dynamic Phase Extraction (DPE) gave the magnitudes of the variation in IBI associated with breathing [Formula: see text] measured with photoplethysmography during paced breathing (with premature ventricular contractions, abnormal arrhythmias, and other artifacts edited out). [Formula: see text] correlated well with two standard measures of pulse rate variability: the Standard Deviation of the inter-beat interval (SDNN) (ρ = 0.911) and with the integrated value of the Power Spectral Density between 0.04 and 0.15 Hz (Low Frequency Power or LF Power) (ρ = 0.885). These correlations were comparable to the correlation between the SDNN and the LF Power (ρ = 0.877). In addition to the magnitude [Formula: see text], Dynamic Phase Extraction also gave the phase between the breath pacer and the changes in the inter-beat interval (IBI) due to respiratory sinus arrythmia (RSA), and correlated well with the phase extracted using a Fourier transform (ρ = 0.857). Dynamic Phase Extraction can extract both the phase between the breath pacer and the changes in IBI due to the respiratory sinus arrhythmia component of pulse rate variability ([Formula: see text], but is limited by needing a breath pacer.
Topics: Electrocardiography; Heart Rate; Humans; Photoplethysmography; Respiratory Rate; Respiratory Sinus Arrhythmia; Signal Processing, Computer-Assisted
PubMed: 35704121
DOI: 10.1007/s10484-022-09549-z -
PeerJ 2022Heart rate and heart rate variability have enabled insight into a myriad of psychophysiological phenomena. There is now an influx of research attempting using these...
Heart rate and heart rate variability have enabled insight into a myriad of psychophysiological phenomena. There is now an influx of research attempting using these metrics within both laboratory settings (typically derived through electrocardiography or pulse oximetry) and ecologically-rich contexts ( wearable photoplethysmography, , smartwatches). However, these signals can be prone to artifacts and a low signal to noise ratio, which traditionally are detected and removed through visual inspection. Here, we developed an open-source Python package, RapidHRV, dedicated to the preprocessing, analysis, and visualization of heart rate and heart rate variability. Each of these modules can be executed with one line of code and includes automated cleaning. In simulated data, RapidHRV demonstrated excellent recovery of heart rate across most levels of noise (>=10 dB) and moderate-to-excellent recovery of heart rate variability even at relatively low signal to noise ratios (>=20 dB) and sampling rates (>=20 Hz). Validation in real datasets shows good-to-excellent recovery of heart rate and heart rate variability in electrocardiography and finger photoplethysmography recordings. Validation in wrist photoplethysmography demonstrated RapidHRV estimations were sensitive to heart rate and its variability under low motion conditions, but estimates were less stable under higher movement settings.
Topics: Heart Rate; Algorithms; Electrocardiography; Wrist; Photoplethysmography
PubMed: 35345583
DOI: 10.7717/peerj.13147 -
Hypertension Research : Official... Apr 2023
Topics: Humans; Cardiovascular Diseases; Natriuretic Peptide, Brain; Heart Rate; Risk Factors; Hypertension; Blood Pressure; Heart Disease Risk Factors
PubMed: 36697875
DOI: 10.1038/s41440-023-01186-1