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Philosophical Transactions of the Royal... Aug 2021How individuals interact with their environment and respond to changes is a key area of research in evolutionary biology. A physiological parameter that provides an... (Review)
Review
How individuals interact with their environment and respond to changes is a key area of research in evolutionary biology. A physiological parameter that provides an instant proxy for the activation of the automatic nervous system, and can be measured relatively easily, is modulation of heart rate. Over the past four decades, heart rate has been used to assess emotional arousal in non-human animals in a variety of contexts, including social behaviour, animal cognition, animal welfare and animal personality. In this review, I summarize how measuring heart rate has provided new insights into how social animals cope with challenges in their environment. I assess the advantages and limitations of different technologies used to measure heart rate in this context, including wearable heart rate belts and implantable transmitters, and provide an overview of prospective research avenues using established and new technologies, with a special focus on implications for applied research on animal welfare. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.
Topics: Animal Welfare; Animals; Arousal; Emotions; Heart Rate; Social Behavior; Vertebrates
PubMed: 34176323
DOI: 10.1098/rstb.2020.0479 -
Sensors (Basel, Switzerland) Jan 2023Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood...
Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood using short video recordings of the index finger attached to a smartphone built-in camera. Various types of smartphones were used with different operating systems (e.g., iOS, Android) and capabilities. A range of processing algorithms were applied to the red-green-blue (RGB) component signals, including mean intensity calculation, moving average smoothing, and quadratic filtering based on the Savitzky-Golay filter. Two approaches-gradient and local maximum methods-were used to determine the pulse rate, which provided similar results. A fast Fourier transform was applied to the signal to correlate the signal's frequency components with the pulse rate. We resolved the signal into its DC and AC components to calculate the ratio-of-ratios of the AC and DC components of the red and green signals, a method which is often used to estimate the oxygen concentration in blood. A series of measurements were performed on healthy human subjects, producing reliable data that compared favorably to benchmark data obtained by commercial and medically approved oximeters. Furthermore, the effect of the video recording duration on the accuracy of the results was investigated.
Topics: Humans; Smartphone; Heart Rate; Signal Processing, Computer-Assisted; Oximetry; Oxygen
PubMed: 36679533
DOI: 10.3390/s23020737 -
Journal of Physiological Anthropology Aug 2020With the popularization of pulse wave signals by the spread of wearable watch devices incorporating photoplethysmography (PPG) sensors, many studies are reporting the...
With the popularization of pulse wave signals by the spread of wearable watch devices incorporating photoplethysmography (PPG) sensors, many studies are reporting the accuracy of pulse rate variability (PRV) as a surrogate of heart rate variability (HRV). However, the authors are concerned about their research paradigm based on the assumption that PRV is a biomarker that reflects the same biological properties as HRV. Because PPG pulse wave and ECG R wave both reflect the periodic beating of the heart, pulse rate and heart rate should be equal, but it does not guarantee that the respective variabilities are also the same. The process from ECG R wave to PPG pulse wave involves several transformation steps of physical properties, such as those of electromechanical coupling and conversions from force to volume, volume to pressure, pressure impulse to wave, pressure wave to volume, and volume to light intensity. In fact, there is concreate evidence that shows discrepancy between PRV and HRV, such as that demonstrating the presence of PRV in the absence of HRV, differences in PRV with measurement sites, and differing effects of body posture and exercise between them. Our observations in adult patients with an implanted cardiac pacemaker also indicate that fluctuations in R-R intervals, pulse transit time, and pulse intervals are modulated differently by autonomic functions, respiration, and other factors. The authors suggest that it is more appropriate to recognize PRV as a different biomarker than HRV. Although HRV is a major determinant of PRV, PRV is caused by many other sources of variability, which could contain useful biomedical information that is neither error nor noise.
Topics: Aged, 80 and over; Biomarkers; Female; Heart Rate; Humans; Photoplethysmography; Posture; Signal Processing, Computer-Assisted
PubMed: 32811571
DOI: 10.1186/s40101-020-00233-x -
Journal of Biomedical Informatics May 2022Sampling rate impacts the quality of HRV estimates. In the context of the recent research article by Burma et al published in JBI which systematically examined this...
Sampling rate impacts the quality of HRV estimates. In the context of the recent research article by Burma et al published in JBI which systematically examined this matter, I discuss this notion more deeply with practical implications to biomedical informatics. Not all HRV metrics are created equal regarding their sensitivity to sampling rate errors when their health predictive performance is concerned. A combination of several, especially nonlinear HRV metrics can remedy these sampling rate constraints. I present methodology for comprehensive validation of the effect of sampling rate on HRV.
Topics: Benchmarking; Heart Rate; Outcome Assessment, Health Care
PubMed: 35367654
DOI: 10.1016/j.jbi.2022.104061 -
American Journal of Respiratory and... Sep 2022
Topics: Adult; Cardiovascular Diseases; Continuous Positive Airway Pressure; Coronary Artery Disease; Disorders of Excessive Somnolence; Heart Disease Risk Factors; Heart Rate; Humans; Risk Factors; Sleep Apnea, Obstructive; Sleepiness
PubMed: 35675563
DOI: 10.1164/rccm.202206-1050ED -
Sensors (Basel, Switzerland) Sep 2022Heart rate variability is an important physiological parameter in medicine. This parameter is used as an indicator of physiological and psychological well-being and even...
Heart rate variability is an important physiological parameter in medicine. This parameter is used as an indicator of physiological and psychological well-being and even of certain pathologies. Research on biofeedback integrates the fields of biological application (physiological behavior), system modeling, and automated control. This study proposes a new method for modeling and controlling heart rate variability as heart rate acceleration, a model expressed in the frequency domain. The model is obtained from excitation and response signals from heart rate variability, which through the instrumental variables method and the minimization of a cost function delivers a transfer function that represents the physiological phenomenon. This study also proposes the design of an adaptive controller using the reference model. The controller controls heart rate variability based on the light actuators designed here, generating a conditioned reflex that allows individuals to self-regulate their state through biofeedback, synchronizing this action to homeostasis. Modeling is conducted in a target population of middle-aged men who work as firefighters and forest firefighters. This study validates the proposed model, as well as the design of the controllers and actuators, through a simple experiment based on indoor cycling. This experiment has different segments, namely leaving inertia, non-controlled segment, and actively controlled segment.
Topics: Biofeedback, Psychology; Heart Rate; Humans; Male; Middle Aged; Wearable Electronic Devices
PubMed: 36236257
DOI: 10.3390/s22197153 -
Applied Psychophysiology and Biofeedback Dec 2022This paper outlines the early history and contributions our laboratory, along with our close advisors and collaborators, has made to the field of heart rate variability... (Review)
Review
This paper outlines the early history and contributions our laboratory, along with our close advisors and collaborators, has made to the field of heart rate variability and heart rate variability coherence biofeedback. In addition to the many health and wellness benefits of HRV feedback for facilitating skill acquisition of self-regulation techniques for stress reduction and performance enhancement, its applications for increasing social coherence and physiological synchronization among groups is also discussed. Future research directions and applications are also suggested.
Topics: Humans; Heart Rate; Biofeedback, Psychology; Heart
PubMed: 35731454
DOI: 10.1007/s10484-022-09554-2 -
Noninvasive Non-Contact SpO Monitoring Using an Integrated Polarization-Sensing CMOS Imaging Sensor.Sensors (Basel, Switzerland) Oct 2022In the diagnosis and primary health care of an individual, estimation of the pulse rate and blood oxygen saturation (SpO2) is critical. The pulse rate and SpO2 are...
BACKGROUND
In the diagnosis and primary health care of an individual, estimation of the pulse rate and blood oxygen saturation (SpO2) is critical. The pulse rate and SpO2 are determined by methods including photoplethysmography (iPPG), light spectroscopy, and pulse oximetry. These devices need to be compact, non-contact, and noninvasive for real-time health monitoring. Reflection-based iPPG is becoming popular as it allows non-contact estimation of the heart rate and SpO2. Most iPPG methods capture temporal data and form complex computations, and thus real-time measurements and spatial visualization are difficult.
METHOD
In this research work, reflective mode polarized imaging-based iPPG is proposed. For polarization imaging, a custom image sensor with wire grid polarizers on each pixel is designed. Each pixel has a wire grid of varying transmission axes, allowing phase detection of the incoming light. The phase information of the backscattered light from the fingertips of 12 healthy volunteers was recorded in both the resting as well as the excited states. These data were then processed using MATLAB 2021b software.
RESULTS
The phase information provides quantitative information on the reflection from the superficial and deep layers of skin. The ratio of deep to superficial layer backscattered phase information is shown to be directly correlated and linearly increasing with an increase in the SpO2 and heart rate.
CONCLUSIONS
The phase-based measurements help to monitor the changes in the resting and excited state heart rate and SpO2 in real time. Furthermore, the use of the ratio of phase information helps to make the measurements independent of the individual skin traits and thus increases the accuracy of the measurements. The proposed iPPG works in ambient light, relaxing the instrumentation requirement and helping the system to be compact and portable.
Topics: Humans; Oximetry; Photoplethysmography; Monitoring, Physiologic; Heart Rate; Fingers; Oxygen
PubMed: 36298147
DOI: 10.3390/s22207796 -
Schizophrenia Bulletin Jan 2022Patients with psychiatric disorders have an increased risk of cardiovascular pathologies. A bidirectional feedback model between the brain and heart exists widely in... (Comparative Study)
Comparative Study
OBJECTIVES
Patients with psychiatric disorders have an increased risk of cardiovascular pathologies. A bidirectional feedback model between the brain and heart exists widely in both psychotic and nonpsychotic disorders. The aim of this study was to compare heart rate variability (HRV) and pulse wave velocity (PWV) functions between patients with psychotic and nonpsychotic disorders and to investigate whether subgroups defined by HRV and PWV features improve the transdiagnostic psychopathology of psychiatric classification.
METHODS
In total, 3448 consecutive patients who visited psychiatric or psychological health services with psychotic (N = 1839) and nonpsychotic disorders (N = 1609) and were drug-free for at least 2 weeks were selected. HRV and PWV indicators were measured via finger photoplethysmography during a 5-minute period of rest. Canonical variates were generated through HRV and PWV indicators by canonical correlation analysis (CCA).
RESULTS
All HRV indicators but none of the PWV indicators were significantly reduced in the psychotic group relative to those in the nonpsychotic group. After adjusting for age, gender, and body mass index, many indices of HRV were significantly reduced in the psychotic group compared with those in the nonpsychotic group. CCA analysis revealed 2 subgroups defined by distinct and relatively homogeneous patterns along HRV and PWV dimensions and comprising 19.0% (subgroup 1, n = 655) and 80.9% (subgroup 2, n = 2781) of the sample, each with distinctive features of HRV and PWV functions.
CONCLUSIONS
HRV functions are significantly impaired among psychiatric patients, especially in those with psychosis. Our results highlight important subgroups of psychiatric patients that have distinct features of HRV and PWV which transcend current diagnostic boundaries.
Topics: Adult; Autonomic Nervous System; Cardiovascular Diseases; Comorbidity; Female; Heart Rate; Humans; Male; Mental Disorders; Middle Aged; Plethysmography; Psychotic Disorders; Pulse Wave Analysis
PubMed: 34313787
DOI: 10.1093/schbul/sbab080 -
GeroScience Feb 2022The cardiac pacemaker ignites and coordinates the contraction of the whole heart, uninterruptedly, throughout our entire life. Pacemaker rate is constantly tuned by the... (Review)
Review
The cardiac pacemaker ignites and coordinates the contraction of the whole heart, uninterruptedly, throughout our entire life. Pacemaker rate is constantly tuned by the autonomous nervous system to maintain body homeostasis. Sympathetic and parasympathetic terminals act over the pacemaker cells as the accelerator and the brake pedals, increasing or reducing the firing rate of pacemaker cells to match physiological demands. Despite the remarkable reliability of this tissue, the pacemaker is not exempt from the detrimental effects of aging. Mammals experience a natural and continuous decrease in the pacemaker rate throughout the entire lifespan. Why the pacemaker rhythm slows with age is poorly understood. Neural control of the pacemaker is remodeled from birth to adulthood, with strong evidence of age-related dysfunction that leads to a downshift of the pacemaker. Such evidence includes remodeling of pacemaker tissue architecture, alterations in the innervation, changes in the sympathetic acceleration and the parasympathetic deceleration, and alterations in the responsiveness of pacemaker cells to adrenergic and cholinergic modulation. In this review, we revisit the main evidence on the neural control of the pacemaker at the tissue and cellular level and the effects of aging on shaping this neural control.
Topics: Aging; Animals; Heart Rate; Reproducibility of Results; Sinoatrial Node
PubMed: 34292477
DOI: 10.1007/s11357-021-00420-3