scholarly journals A common neural substrate for elevated PTSD symptoms and reduced pulse rate variability in combat‐exposed veterans

2019 ◽  
Vol 57 (1) ◽  
Author(s):  
Daniel W. Grupe ◽  
Ted Imhoff‐Smith ◽  
Joseph Wielgosz ◽  
Jack B. Nitschke ◽  
Richard J. Davidson
Keyword(s):  
Pulse Rate ◽  
Ptsd Symptoms ◽  
Pulse Rate Variability ◽  
Neural Substrate

scholarly journals A common neural substrate for elevated PTSD symptoms and reduced pulse rate variability in combat-exposed veterans

2018 ◽  
Author(s):  
Daniel W. Grupe ◽  
Ted Imhoff-Smith ◽  
Joseph Wielgosz ◽  
Jack B. Nitschke ◽  
Richard J. Davidson
Keyword(s):  
Heart Rate ◽  
Pulse Rate ◽  
Functional Neuroimaging ◽  
Ptsd Symptoms ◽  
Pulse Rate Variability ◽  
Structural Abnormalities ◽  
Neural Substrate ◽  
Parasympathetic Control ◽  
Separate Line ◽  
Ptsd Symptomatology

AbstractBackgroundPrevious studies have identified reduced heart rate variability (HRV) in posttraumatic stress disorder (PTSD), which may temporally precede the onset of the disorder. A separate line of functional neuroimaging research suggests that the ventromedial prefrontal cortex (vmPFC) — a key aspect of a descending neuromodulatory system that exerts inhibitory control over heart rate — shows functional and structural abnormalities in PTSD. No research to date, however, has simultaneously investigated whether altered vmPFC activation is associated with reduced HRV and elevated PTSD symptoms in the same individuals.MethodsWe collected fMRI data during alternating conditions of threat of shock and safety from shock in 51 male, combat-exposed veterans with either high or low levels of PTSD symptoms. Pulse rate variability (PRV) – an HRV surrogate calculated from pulse oximetry – was assessed during a subsequent resting scan. Correlational analyses tested for hypothesized relationships between vmPFC activation, PRV, and distinct dimensions of PTSD symptomatology.ResultsRe-experiencing PTSD symptoms were inversely associated with high-frequency (HF)-PRV, thought to primarily reflect parasympathetic control of heart rate, in veterans with elevated PTSD symptoms. Lower HF-PRV was associated with reduced vmPFC activation for the contrast of safety-threat in a region that also showed an inverse relationship with re-experiencing symptoms.ConclusionsReduced vmPFC responses to safety vs. threat were associated with both reduced HF-PRV and increased re-experiencing symptoms. These results tie together previous observations of reduced HRV/PRV and impaired vmPFC function in PTSD and call for further research on reciprocal brain-body relationships in understanding PTSD pathophysiology.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

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.

scholarly journals Spectrum Analysis of Pulse Rate Variability in Counseling

2019 ◽  
Vol 83 (0) ◽  
pp. 3C-033-3C-033
Author(s):  
Yumi Adachi ◽  
Hiroaki Yoshikawa
Keyword(s):  
Pulse Rate ◽  
Spectrum Analysis ◽  
Pulse Rate Variability

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

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.

Comment on ‘pulse rate variability in cardiovascular health: a review on its applications and relationship with heart rate variability’

2021 ◽  
Vol 42 (9) ◽  
pp. 098001
Author(s):  
Jacquelin Peck ◽  
Michael J Wishon ◽  
Harrison Wittels ◽  
Hector Davila ◽  
S Howard Wittels ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Cardiovascular Health ◽  
Pulse Rate Variability

Association between oximetry-derived pulse-rate variability and stroke risk in patients with obstructive sleep apnoea

2021 ◽  
Author(s):  
A Sabil ◽  
C Gervès-Pinquié ◽  
M Blanchard ◽  
M Feuilloy ◽  
W Trzepizur ◽  
...  
Keyword(s):  
Obstructive Sleep Apnoea ◽  
Pulse Rate ◽  
Stroke Risk ◽  
Sleep Apnoea ◽  
Pulse Rate Variability ◽  
Obstructive Sleep

scholarly journals Differences in pulse rate variability with measurement site

2020 ◽  
Vol 39 (1) ◽  
Author(s):  
Emi Yuda ◽  
Kento Yamamoto ◽  
Yutaka Yoshida ◽  
Junichiro Hayano
Keyword(s):  
Pulse Rate ◽  
Pulse Rate Variability ◽  
Measurement Site

Optimal fiducial points for pulse rate variability analysis from forehead and finger photoplethysmographic signals

2019 ◽  
Vol 40 (2) ◽  
pp. 025007 ◽  
Author(s):  
Elena Peralta ◽  
Jesus Lazaro ◽  
Raquel Bailon ◽  
Vaidotas Marozas ◽  
Eduardo Gil
Keyword(s):  
Pulse Rate ◽  
Pulse Rate Variability ◽  
Variability Analysis
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