The minimal sampling frequency of the photoplethysmogram for accurate pulse rate variability parameters in healthy volunteers

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

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Resonance in pulse rate variability induced by respiratory control

2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) ◽

10.23919/sice.2017.8105549 ◽

2017 ◽

Author(s):

Koji Kashihara ◽

Yutaka Kameda

Keyword(s):

Pulse Rate ◽

Respiratory Control ◽

Pulse Rate Variability

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Spectrum Analysis of Pulse Rate Variability in Counseling

The Proceedings of the Annual Convention of the Japanese Psychological Association ◽

10.4992/pacjpa.83.0_3c-033 ◽

2019 ◽

Vol 83 (0) ◽

pp. 3C-033-3C-033

Author(s):

Yumi Adachi ◽

Hiroaki Yoshikawa

Keyword(s):

Pulse Rate ◽

Spectrum Analysis ◽

Pulse Rate Variability

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A New Measure of Pulse Rate Variability and Detection of Atrial Fibrillation Based on Improved Time Synchronous Averaging

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/5597559 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Xiaodong Ding ◽

Yiqin Wang ◽

Yiming Hao ◽

Yi Lv ◽

Rui Chen ◽

...

Keyword(s):

Atrial Fibrillation ◽

Pulse Rate ◽

Euclidean Distance ◽

Operating Characteristic ◽

Pulse Wave ◽

Characteristic Curve ◽

Signal Quality ◽

Training Set ◽

Pulse Rate Variability ◽

Operating Characteristic Curve

Background. Pulse rate variability monitoring and atrial fibrillation detection algorithms have been widely used in wearable devices, but the accuracies of these algorithms are restricted by the signal quality of pulse wave. Time synchronous averaging is a powerful noise reduction method for periodic and approximately periodic signals. It is usually used to extract single-period pulse waveforms, but has nothing to do with pulse rate variability monitoring and atrial fibrillation detection traditionally. If this method is improved properly, it may provide a new way to measure pulse rate variability and to detect atrial fibrillation, which may have some potential advantages under the condition of poor signal quality. Objective. The objective of this paper was to develop a new measure of pulse rate variability by improving existing time synchronous averaging and to detect atrial fibrillation by the new measure of pulse rate variability. Methods. During time synchronous averaging, two adjacent periods were regarded as the basic unit to calculate the average signal, and the difference between waveforms of the two adjacent periods was the new measure of pulse rate variability. 3 types of distance measures (Euclidean distance, Manhattan distance, and cosine distance) were tested to measure this difference on a simulated training set with a capacity of 1000. The distance measure, which can accurately distinguish regular pulse rate and irregular pulse rate, was used to detect atrial fibrillation on the testing set with a capacity of 62 (11 with atrial fibrillation, 8 with premature contraction, and 43 with sinus rhythm). The receiver operating characteristic curve was used to evaluate the performance of the indexes. Results. The Euclidean distance between waveforms of the two adjacent periods performs best on the training set. On the testing set, the Euclidean distance in atrial fibrillation group is significantly higher than that of the other two groups. The area under receiver operating characteristic curve to identify atrial fibrillation was 0.998. With the threshold of 2.1, the accuracy, sensitivity, and specificity were 98.39%, 100%, and 98.04%, respectively. This new index can detect atrial fibrillation from pulse wave signal. Conclusion. This algorithm not only provides a new perspective to detect AF but also accomplishes the monitoring of PRV and the extraction of single-period pulse wave through the same technical route, which may promote the popularization and application of pulse wave.

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Abstract 399: The Circadian Rhythm of Plasma Angiotensinogen in Healthy Volunteers

Hypertension ◽

10.1161/hyp.60.suppl_1.a399 ◽

2012 ◽

Vol 60 (suppl_1) ◽

Author(s):

Kumiko Kaifu ◽

Hiroyuki Kobori ◽

Yoko Nishijima ◽

Akira Nishiyama ◽

Masakazu Kohno

Keyword(s):

Blood Pressure ◽

Circadian Rhythm ◽

Healthy Volunteers ◽

Pulse Rate ◽

Capillary Tube ◽

Kidney Diseases ◽

Surrogate Marker ◽

Recumbent Position ◽

Time Points ◽

Significant Difference

Background: We have previously reported that urinary angiotensinogen (AGT) excretion did not have a circadian rhythm and could be a novel biomarker for the activity of the renin-angiotensin system (RAS) in kidney. However, there have been few reports investigating the circadian rhythm of plasma AGT in human body. Thus, this study was performed to examine the circadian rhythm in plasma AGT in human. METHODS: Evaluating RAS in clinical practice is generally performed in a recumbent position after a 30-minute stabilization period. However, to determine the necessity of recumbent position, we first compared plasma AGT concentrations measured right after waking up and after a 5-minute sitting rest. Next, we examined the circadian rhythm of plasma AGT in 43 healthy volunteers who had shown no abnormalities in the medical examinations in 2011. Plasma AGT was measured at three time points (9 a.m., 1 p.m., and 4 p.m.) in the above volunteers. Blood was collected by a micro hematocrit capillary tube with heparin, frozen for storage after centrifugation, and thawed for the measurement of plasma AGT using an ELISA kit. Results: There was no significant difference between the plasma AGT values of the two measuring methods (P = 0.1202, n = 5). Based on the result, we performed blood sampling after a 5-minute sitting rest in the volunteers consisting of 17 men and 26 women. Average blood pressure was 116.3/75.1 mmHg at 9 a.m., 116.3/71.9 mmHg at 1 p.m., and 115.5/70.1 mmHg at 4 p.m.; average pulse rate was 78.7/min at 9 a.m., 77.1/min at 1 p.m., and 73.3/min at 4 p.m. Blood pressure and pulse rate did not change throughout the day. Average plasma AGT was 20.4 ± 6.0 ng/ml at 9 a.m., 20.7 ± 5.0 ng/ml at 1 p.m., and 19.8 ± 6.4 ng/ml at 4 p.m. Plasma AGT did not show a circadian rhythm (P = 0.3803). Conclusion: We found in this study that plasma AGT did not have a circadian rhythm. We also found that plasma AGT was not affected by daily life actions. Thus, future patients may not be required to rest nor wait for certain time points before measuring plasma AGT. We also have to unveil the normal AGT levels and the influence on the levels by diseases. As we think that plasma AGT and ratio of urinary AGT to plasma AGT can be a new surrogate marker of hypertension and kidney diseases, we further need to go into this research area.

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