-
Journal of Physiological Anthropology Feb 2020Recently, attempts have been made to use the pulse rate variability (PRV) as a surrogate for heart rate variability (HRV). PRV, however, may be caused by the...
BACKGROUND
Recently, attempts have been made to use the pulse rate variability (PRV) as a surrogate for heart rate variability (HRV). PRV, however, may be caused by the fluctuations of left ventricular pre-ejection period and pulse transit time besides HRV. We examined whether PRV differs not only from HRV but also depending on the measurement site.
RESULTS
In five healthy subjects, pulse waves were measured simultaneously on both wrists and both forearms together with single-lead electrocardiogram (ECG) in the supine and sitting positions. Although average pulse interval showed no significant difference from average R-R interval in either positions, PRV showed greater power for the low-frequency (LF) and high-frequency (HF) components and lower LF/HF than HRV. The deviations of PRV from HRV in the supine and sitting positions were 13.2% and 7.9% for LF power, 24.5% and 18.3% for HF power, and - 15.0% and - 30.2% for LF/HF, respectively. While the average pulse interval showed 0.8% and 0.5% inter-site variations among the four sites in the supine and sitting positions, respectively, the inter-site variations in PRV were 4.0% and 3.6% for LF power, 3.8% and 4.7% for HF power, and 18.0% and 17.5% for LF/HF, respectively.
CONCLUSIONS
These suggest that PRV shows not only systemic differences from HRV but also considerable inter-site variations.
Topics: Adult; Electrocardiography; Female; Forearm; Heart Rate; Humans; Male; Posture; Pulse Wave Analysis; Signal Processing, Computer-Assisted; Wearable Electronic Devices; Wrist; Young Adult
PubMed: 32085811
DOI: 10.1186/s40101-020-0214-1 -
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 -
Physiological Measurement Oct 2021
Review
Topics: Cardiovascular System; Heart Rate; Photoplethysmography; Pulse
PubMed: 34617518
DOI: 10.1088/1361-6579/ac1dec -
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 -
Medical & Biological Engineering &... Feb 2020Respiratory rate (RR) is an important vital sign which can be difficult to measure accurately and unobtrusively in routine clinical practice. Pulse transit time (PTT),...
Respiratory rate (RR) is an important vital sign which can be difficult to measure accurately and unobtrusively in routine clinical practice. Pulse transit time (PTT), on the other hand, is unobtrusive to collect from electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Using PTT is a novel method to estimate and monitor blood pressure (BP) and RR. This study aimed to estimate continuous RR using PTT with singular spectrum analysis to extract respiratory components. The performance of this method was validated on 17 subjects who carried out spontaneous breathing and controlled deep breathing conditions. Three types of estimated RR parameters (average RR by power spectral density (PSD) (RR), number of breaths (RR), and instantaneous RR (RR)) were compared with the corresponding reference RR. The reference RR was collected using a respiratory belt. Our findings demonstrate that the PTT signal reliably tracked respiratory variation with a root mean square error of 0.84, 1.11, and 0.74 breaths/min for RR, RR, and RR estimations, respectively. Overall, RR estimated by PTT was more accurate than heart/pulse rate interval, QRS area, and PPG amplitude, which were also extracted from ECG and PPG. The results suggest that it may be feasible to use PTT as an estimation of RR and that ECG and PPG may be relied upon for monitoring not only RR but also BP and heart rate. Graphical abstract The Pulse Transit Time (PTT) based Respiratory Rate (RR) estimation with Singular Spectrum Analysis (SSA) provides a superior performance than the method with other respiratory indicators extracted from Electrocardiogram (ECG) or Photoplethysmogram (PPG).
Topics: Adult; Blood Pressure; Electrocardiography; Female; Heart Rate; Humans; Male; Photoplethysmography; Pulse Wave Analysis; Respiratory Rate; Spectrum Analysis
PubMed: 31834610
DOI: 10.1007/s11517-019-02088-6 -
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 -
Medical & Biological Engineering &... Jul 2023Sample entropy is an effective nonlinear index for analyzing pulse rate variability (PRV) signal, but it has problems with a large amount of calculation and time...
Sample entropy is an effective nonlinear index for analyzing pulse rate variability (PRV) signal, but it has problems with a large amount of calculation and time consumption. Therefore, this study proposes a fast sample entropy calculation method to analyze the PRV signal according to the microprocessor process of data updating and the principle of sample entropy. The simulated data and PRV signal are employed as experimental data to verify the accuracy and time consumption of the proposed method. The experimental results on simulated data display that the proposed improved sample entropy can improve the operation rate of the entropy value by a maximum of 47.6 times and an average of 28.6 times and keep the entropy value unchanged. Experimental results on PRV signal display that the proposed improved sample entropy has great potential in the real-time processing of physiological signals, which can increase approximately 35 times.
Topics: Heart Rate; Pulse; Entropy; Signal Processing, Computer-Assisted
PubMed: 36826631
DOI: 10.1007/s11517-022-02766-y -
Annual International Conference of the... Jul 2022Pulse rate variability (PRV) has been proposed as a surrogate for the estimation of Heart Rate Variability (HRV), which is a non-invasive technique used to assess the...
Pulse rate variability (PRV) has been proposed as a surrogate for the estimation of Heart Rate Variability (HRV), which is a non-invasive technique used to assess the cardiac autonomic activity. However, both physiological and technical factors may affect the relationship between HRV and PRV, and there are no standards for the analysis of PRV from photoplethysmographic (PPG) signals. The aim of this study was to determine the best outlier management strategies for PRV analysis. 117 PPG signals with randomly generated PRV information were simulated using Gaussian signals. From these, interbeat intervals were detected and different outlier detection and correction techniques were applied. Time and frequency-domain and non-linear PRV indices were extracted and compared with respect to the gold standard values obtained from the simulated PRV information. The results show that, in good quality PPG signals, there is no need to apply any outlier management technique for the extraction of PRV information. Clinical relevance- Establishing guidelines for PRV mea-surement can lead to more reliable and comparable results, as well as to the increase in the use of this variable for the diagnosis and monitoring of cardiovascular and autonomic conditions.
Topics: Autonomic Nervous System; Heart; Heart Rate; Normal Distribution; Photoplethysmography
PubMed: 36086146
DOI: 10.1109/EMBC48229.2022.9871942 -
Einstein (Sao Paulo, Brazil) 2023The World Health Organization and Centers for Disease Control and Prevention recommend the use of face masks in public. This study aimed to evaluate the effects of face...
OBJECTIVE
The World Health Organization and Centers for Disease Control and Prevention recommend the use of face masks in public. This study aimed to evaluate the effects of face masks on pulse rate and partial blood oxygen saturation in patients without cardiorespiratory disorders.
METHODS
A total of 150 volunteers of both sexes were divided into three groups (n=50) according to age (children, young adults, and older adults). The partial blood oxygen saturation and pulse rate were measured for each volunteer using a digital oximeter while wearing a facial mask and remaining at rest. The masks were removed for two minutes, and partial blood oxygen saturation and pulse rate were remeasured. The materials and types of masks used were recorded. The t -test for paired samples was used to compare the mean values obtained before and after removing the masks.
RESULTS
The most frequently used mask was a two-layered cloth (64.7%). A decrease in pulse rate was observed after removing the face mask in males, particularly in children (p=0.006) and young adults (p=0.034). Partial blood oxygen saturation levels increased in young adult males after mask removal (p=0.01).
CONCLUSION
The two-layer cotton tissue face masks are associated with a higher pulse rate and reduced arterial blood oxygen saturation without associated clinical disorders, mainly in adult men with a lower tolerance to breathing and ear discomfort.
Topics: Male; Child; Female; Young Adult; Humans; Aged; Masks; Heart Rate; Lung; Oxygen
PubMed: 37970950
DOI: 10.31744/einstein_journal/2023AO0349 -
Medical & Biological Engineering &... Oct 2023Remote photoplethysmography (rPPG) enables contact-free monitoring of the pulse rate by using a color camera. The fundamental limitation is that motion artifacts and...
Remote photoplethysmography (rPPG) enables contact-free monitoring of the pulse rate by using a color camera. The fundamental limitation is that motion artifacts and changes in ambient light conditions greatly affect the accuracy of pulse-rate monitoring. We propose use of a high-speed camera and a motion suppression algorithm with high computational efficiency. This system incorporates a number of major improvements including reproduction of pulse wave details, high-precision pulse-rate monitoring of moving subjects, and excellent scene scalability. A series of quantization methods were used to evaluate the effect of different frame rates and different algorithms in pulse-rate monitoring of moving subjects. The experimental results show that use of 180-fps video and a Plane-Orthogonal-to-Skin (POS) algorithm can produce high-precision pulse-rate monitoring results with mean absolute error can be less than 5 bpm and the relative accuracy reaching 94.5%. Thus, it has significant potential to improve personal health care and intelligent health monitoring.
Topics: Humans; Heart Rate; Pulse; Skin; Photoplethysmography; Motion; Algorithms; Signal Processing, Computer-Assisted
PubMed: 37474842
DOI: 10.1007/s11517-023-02884-1