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The Journal of Emergency Medicine Dec 2022
Topics: Humans; Triage; Heart Rate; Emergency Service, Hospital; Oximetry; Patients
PubMed: 36517132
DOI: 10.1016/j.jemermed.2022.09.037 -
Computer Methods and Programs in... May 2022Pulse Rate Variability (PRV) has been widely used as a surrogate of Heart Rate Variability (HRV). However, there are several technical aspects that may affect the...
Effects of using different algorithms and fiducial points for the detection of interbeat intervals, and different sampling rates on the assessment of pulse rate variability from photoplethysmography.
OBJECTIVE
Pulse Rate Variability (PRV) has been widely used as a surrogate of Heart Rate Variability (HRV). However, there are several technical aspects that may affect the extraction of PRV information from pulse wave signals such as the photoplethysmogram (PPG). The aim of this study was to evaluate the effects of changing the algorithm and fiducial points used for determining inter-beat intervals (IBIs), as well as the PPG sampling rate, from simulated PPG signals with known PRV content.
METHODS
PPG signals were simulated using a proposed model, in which PRV information can be modelled. Two independent experiments were performed. First, 5 IBIs detection algorithms and 8 fiducial points were used for assessing PRV information from the simulated PPG signals, and time-domain and Poincaré plot indices were extracted and compared to the expected values according to the simulated PRV. The best combination of algorithms and fiducial points were determined for each index, using factorial designs. Then, using one of the best combinations, PPG signals were simulated with varying sampling rates. PRV indices were extracted and compared to the expected values using Student t-tests or Mann-Whitney U-tests.
RESULTS
From the first experiment, it was observed that AVNN and SD2 indices behaved similarly, and there was no significant influence of the fiducial points used. For other indices, there were several combinations that behaved similarly well, mostly based on the detection of the valleys of the PPG signal. There were differences according to the quality of the PPG signal. From the second experiment, it was observed that, for all indices but SDNN, the higher the sampling rate the better. AVNN and SD2 showed no statistical differences even at the lowest evaluated sampling rate (32 Hz), while RMSSD, pNN50, S, SD1 and SD1/SD2 showed good performance at sampling rates as low as 128 Hz.
CONCLUSION
The best combination of IBIs detection algorithms and fiducial points differs according to the application, but those based on the detection of the valleys of the PPG signal tend to show a better performance. The sampling rate of PPG signals for PRV analysis could be lowered to around 128 Hz, although it could be further lowered according to the application.
SIGNIFICANCE
The standardisation of PRV analysis could increase the reliability of this signal and allow for the comparison of results obtained from different studies. The obtained results allow for a first approach to establish guidelines for two important aspects in PRV analysis from PPG signals, i.e. the way the IBIs are segmented from PPG signals, and the sampling rate that should be used for these analyses. Moreover, a model for simulating PPG signals with PRV information has been proposed, which allows for the establishing of these guidelines while controlling for other variables, such as the quality of the PPG signal.
Topics: Algorithms; Electrocardiography; Heart Rate; Humans; Photoplethysmography; Reproducibility of Results; Signal Processing, Computer-Assisted; Syndactyly
PubMed: 35255373
DOI: 10.1016/j.cmpb.2022.106724 -
Annual International Conference of the... Nov 2021The COVID-19 pandemic is a global health crisis. Mental health is critical in such uncertain situations, particularly when people are required to significantly restrict...
The COVID-19 pandemic is a global health crisis. Mental health is critical in such uncertain situations, particularly when people are required to significantly restrict their movements and change their lifestyles. Under these conditions, many countries have turned to telemedicine to strengthen and expand mental health services. Our research group previously developed a mental illness screening system based on heart rate variability (HRV) analysis, enabling an objective and easy mental health self-check. This screening system cannot be used for telemedicine because it uses electrocardiography (ECG) and contact photoplethysmography (PPG), that are not widely available outside of a clinical setting. The purpose of this study is to enable the extension of the aforementioned system to telemedicine by the application of non-contact PPG using an RGB webcam, also called imaging- photoplethysmography (iPPG). The iPPG measurement errors occur due to changes in the relative position between the camera and the target, and due to changes in light. Conventionally, in image processing, the pixel value of the entire face region is used. We propose skin pixel extraction to eliminate blinks, eye movements, and changes in light and shadow. In signal processing, the green channel signal is conventionally used as a pulse wave owing to the absorption characteristics of blood flow. Taking advantage of the fact that the red and blue channels contain noise, we propose a signal reconstruction method for removing noise and strengthening the signal in the pulse rate variability (PRV) frequency band by weighting the three signals of the RGB camera. We conducted an experiment with 13 healthy subjects, and showed that the PRV index and pulse rate (PR) errors estimated by the proposed method were smaller than those of the conventional method. The correlation coefficients between estimated values by the proposed method and reference values of LF, HF, and PR were 0.86, 0.69, and 0.96, respectively.
Topics: COVID-19; Heart Rate; Humans; Mental Disorders; Pandemics; SARS-CoV-2
PubMed: 34892718
DOI: 10.1109/EMBC46164.2021.9630038 -
Journal of Behavioral Medicine Feb 1994Heart rate and reactivity from pulse and ECG were compared over rest and mental arithmetic periods of 2-min duration each for 32 males and 50 females. Data from the two...
Heart rate and reactivity from pulse and ECG were compared over rest and mental arithmetic periods of 2-min duration each for 32 males and 50 females. Data from the two sources of heart rate were not significantly different during the rest period but did differ significantly during periods of heart rate acceleration and deceleration. Sex effects were also noted, with females having consistently higher heart rates from both sources of measurement. Calculation of heart rate reactivity via five procedures based upon the wider literature revealed significant differences between data from different sources of heart rate. Implications for assessment of heart rate reactivity to laboratory stressors are discussed, with suggestions for future research.
Topics: Adolescent; Adult; Electrocardiography; Female; Heart Rate; Humans; Male; Mathematics; Middle Aged; Plethysmography; Sex Factors; Stress, Psychological
PubMed: 8201615
DOI: 10.1007/BF01856885 -
Technology and Health Care : Official... 2017The usefulness of heart rate variability (HRV) in the clinical research has been verified in numerous studies. However, it is controversy that using pulse rate... (Comparative Study)
Comparative Study
BACKGROUND
The usefulness of heart rate variability (HRV) in the clinical research has been verified in numerous studies. However, it is controversy that using pulse rate variability (PRV) as a surrogate of HRV in different clinical applications.
OBJECTIVE
We aimed to investigate whether PRV extracted from finger pulse photoplethysmography (Pleth) signal could substitute HRV from ECG signal during different sleep stages by analyzing the common time-domain, frequency-domain and non-linear indices.
METHODS
Seventy-five sleep apnea patients were enrolled. For each patient, ECG and Pleth signals were simultaneously recorded for the whole night using Alice Sleepware Polysomnographic System and the sleep stage signals were automatically calculated by this System. Time-domain, frequency-domain and non-linear indices of both HRV and PRV were calculated for each sleep stage.
RESULTS
Mann-Whitney U-test showed that for both time-domain and frequency-domain indices, there were no statistical differences between HRV and PRV results during all four sleep stages. For non-linear indices, sample entropy reported statistical differences between HRV and PRV results for N1, N2 and REM sleeps (all P< 0.01) whereas fuzzy measure entropy only reported statistical differences for REM sleep (P< 0.05). SDNN, LF and LF/HF indices decreased for both HRV and PRV with the sleep deepening while HF and non-linear indices increased. In addition, there were strong and significant correlation between HRV and PRV indices during all four sleep stages (all P< 0.01).
CONCLUSIONS
PRV measurement could present the similar results as HRV analysis for sleep apnea patients during different sleep stages.
Topics: Electrocardiography; Female; Heart Rate; Humans; Male; Middle Aged; Photoplethysmography; Polysomnography; Pulse; Sleep Apnea Syndromes; Sleep Stages
PubMed: 27911348
DOI: 10.3233/THC-161283 -
Annual International Conference of the... 2014The heart rate variability (HRV) is a commonly used method to quantify the sympathetic and the parasympathetic modulation of the heart rate. HRV is mainly conducted on... (Comparative Study)
Comparative Study
The heart rate variability (HRV) is a commonly used method to quantify the sympathetic and the parasympathetic modulation of the heart rate. HRV is mainly conducted on electrocardiograms (ECG). However, the use of photo-plethysmography (PPG) as a marker of the autonomic tone is emerging. In this study we investigated the feasibility of deriving pulse rate variability (PRV) using PPG signals recorded by a reflectance PPG sensor attached to the chest bone (sternum) and comparing it to HRV. The recordings were conducted on 9 healthy subjects being in a relaxed supine position and under forced respiration, where the subjects were asked to breathe following a visual scale with a rate of 27 breaths/min. HRV parameters such as the mean intervals (meanNN), the standard deviation of intervals (SDNN), the root mean square of difference of successive intervals (RMSSD), and the proportion of intervals differing more than 50 ms (pNN50) were calculated from the R peak-to-R peak (R-R) and pulse-to-pulse (P-P) intervals. In the frequency domain the low and high frequency ratio of the power spectral density (LF/HF) was also computed. The Pearson correlation coefficient showed significant correlation for all the parameters (r > 0.95 with p < 0.001) and the Bland-Altmann analysis showed close agreement between the two methods for all the parameters during resting and forced respiration condition. Thus, PRV analysis using sternal PPG can be an alternative to HRV analysis on healthy subjects at.
Topics: Adult; Electrocardiography; Female; Healthy Volunteers; Heart Rate; Humans; Male; Photoplethysmography; Signal Processing, Computer-Assisted; Sternum; Time Factors
PubMed: 25570719
DOI: 10.1109/EMBC.2014.6944351 -
Advances in Physiology Education Jun 2022Information and Communication Technology (ICT) is a commonly used concept in schools, implemented in laboratory work in the form of various digital devices. We evaluated...
Information and Communication Technology (ICT) is a commonly used concept in schools, implemented in laboratory work in the form of various digital devices. We evaluated the ICT implementation in cardiovascular physiology in Slovenian primary school education. Surprisingly, we showed a relatively low acceptance rate in biology classes: only 42.8% of involved Slovenian biology teachers used a pulse rate (PR) measuring device. As a part of a Slovenian Project, students designed, developed, and manufactured a device capable of low-cost, automatic, noninvasive, and straightforward PR sampling in real time. The device was named Fingerbeeper, and teachers' perceptions of its efficacy and efficiency were evaluated in the elementary school biology lessons, comparing its ease of use with other commercially available devices: the systems from Vernier, Biopac, and the Gear Sport Samsung smartwatch. The most preferred system was the system from Vernier (36.4%), followed by the Fingerbeeper (29.1%), the system from Biopac (18.2%), and the smartwatch (16.3%). Teachers provided their opinion on the efficiency of the Fingerbeeper in terms of cost compared with the other three measurement devices. Its perception of efficiency was comparable to the other commercially available devices while having the estimated cost of only a few percent of the Biopac or Vernier systems. Considering the general low funding in the public primary schools in Slovenia, the bias toward Fingerbeeper seemed rational, outweighing the superior performance of the commercial systems. Further research and improvement of such low-cost and high-efficiency devices, also in general terms, would lead to broader acceptance and implementation of the ICT in curricula.
Topics: Biology; Heart Rate; Humans; Perception; School Teachers; Schools; Students
PubMed: 35143359
DOI: 10.1152/advan.00088.2021 -
Clinical Science (London, England :... Oct 1999To investigate the differences between heart rate (HR) variability and pulse rate (PR) variability, short-term variability of finger pulse wave and ECG signals were...
To investigate the differences between heart rate (HR) variability and pulse rate (PR) variability, short-term variability of finger pulse wave and ECG signals were studied in 10 children with a fixed ventricular pacemaker rhythm (80 beats/min). Ten healthy children in sinus rhythm served as a reference population. Distal PR and HR were measured continuously using a Finapres device and an ECG respectively. Power spectra for HR and PR were calculated in both the supine and orthostatic positions. In paced subjects, PR spectra exhibited the characteristic respiratory peak, although the HR spectra were flat. Similarly, in healthy children the respiratory fluctuations were more pronounced when calculated from the finger pulse wave signal compared with the ECG signal. The overestimation of HR respiratory fluctuation resulting from distal PR measurement was more pronounced in the standing position; however, this postural effect was demonstrated only in healthy subjects. We observed mechanical respiratory modulation of distal PR independent of classical HR modulations. Our results suggest a mechanical respiratory influence via cardiac output and aortic transmural pressure changes on pulse wave velocity. We conclude that respiratory PR variability does not precisely reflect respiratory HR variability in standing healthy subjects and in patients with low HR variability. Consequently, HR modulation should be studied using the ECG signal rather than the distal pulse wave signal. However, when ECG recording is not available, the distal pulse wave is an acceptable alternative.
Topics: Adolescent; Cardiac Pacing, Artificial; Child; Electrocardiography; Heart Rate; Humans; Posture; Pulse; Respiration; Signal Processing, Computer-Assisted
PubMed: 10491338
DOI: No ID Found -
Journal of Clinical Monitoring and... Dec 2016Pulse rate variability (PRV) is a promising physiological and analytic technique used as a substitute for heart rate variability (HRV). PRV is measured by pulse wave...
Pulse rate variability (PRV) is a promising physiological and analytic technique used as a substitute for heart rate variability (HRV). PRV is measured by pulse wave from various devices including mobile and wearable devices but HRV is only measured by an electrocardiogram (ECG). The purpose of this study was to evaluate PRV and HRV at various ambient temperatures and elaborate on the interchangeability of PRV and HRV. Twenty-eight healthy young subjects were enrolled in the experiment. We prepared temperature-controlled rooms and recorded the ECG and photoplethysmography (PPG) under temperature-controlled, constant humidity conditions. The rooms were kept at 17, 25, and 38 °C as low, moderate, and high ambient temperature environments, respectively. HRV and PRV were derived from the synchronized ECG and PPG measures and they were studied in time and frequency domain analysis for PRV/HRV ratio and pulse transit time (PTT). Similarity and differences between HRV and PRV were determined by a statistical analysis. PRV/HRV ratio analysis revealed that there was a significant difference between HRV and PRV for a given ambient temperature; this was with short-term variability measures such as SDNN SDSD or RMSSD, and HF-based variables including HF, LF/HF and normalized HF. In our analysis the absolute value of PTT was not significantly influenced by temperature. Standard deviation of PTT, however, showed significant difference not only between low and moderate temperatures but also between low and high temperatures. Our results suggest that ambient temperature induces a significant difference in PRV compared to HRV and that the difference becomes greater at a higher ambient temperature.
Topics: Algorithms; Body Mass Index; Electrocardiography; Female; Healthy Volunteers; Heart Rate; Humans; Male; Photoplethysmography; Temperature; Young Adult
PubMed: 26511754
DOI: 10.1007/s10877-015-9798-0 -
Journal of Healthcare Engineering 2018Heart rate variability (HRV) provides information about the activity of the autonomic nervous system. Because of the small amount of data collected, the importance of...
BACKGROUND
Heart rate variability (HRV) provides information about the activity of the autonomic nervous system. Because of the small amount of data collected, the importance of HRV has not yet been proven in clinical practice. To collect population-level data, smartphone applications leveraging photoplethysmography (PPG) and some medical knowledge could provide the means for it.
OBJECTIVE
To assess the capabilities of our smartphone application, we compared PPG (pulse rate variability (PRV)) with ECG (HRV). To have a baseline, we also compared the differences among ECG channels.
METHOD
We took fifty parallel measurements using iPhone 6 at a 240 Hz sampling frequency and Cardiax PC-ECG devices. The correspondence between the PRV and HRV indices was investigated using correlation, linear regression, and Bland-Altman analysis.
RESULTS
High PPG accuracy: the deviation of PPG-ECG is comparable to that of ECG channels. Mean deviation between PPG-ECG and two ECG channels: RR: 0.01 ms-0.06 ms, SDNN: 0.78 ms-0.46 ms, RMSSD: 1.79 ms-1.21 ms, and pNN50: 2.43%-1.63%.
CONCLUSIONS
Our iPhone application yielded good results on PPG-based PRV indices compared to ECG-based HRV indices and to differences among ECG channels. We plan to extend our results on the PPG-ECG correspondence with a deeper analysis of the different ECG channels.
Topics: Adult; Electrocardiography; Female; Heart Rate; Humans; Male; Photoplethysmography; Pulse; Signal Processing, Computer-Assisted; Smartphone
PubMed: 29666670
DOI: 10.1155/2018/4038034