Pulse Transit Time Variability Research Articles

Posture-Dependent Variability in Wrist Ballistocardiogram-Photoplethysmogram Pulse Transit Time: Implication to Cuff-Less Blood Pressure Tracking.

Toward the ultimate goal of robust cuff-less blood pressure (BP) tracking with wrist wearables against postural changes, the goal of this work was to investigate posture-dependent variability in pulse transit time (PTT) measured with ballistocardiogram (BCG) and photoplethysmogram (PPG) signal pair at the wrist. BCG and PPG signals were acquired from 25 subjects under the combination of 3 body (standing, sitting, and supine) and 3 arm (vertical in head-to-foot direction, placed on the chest, and holding a shoulder) postures. PTT was computed as the time interval between the BCG J wave and the PPG foot, and the impact of the 9 postures on PTT was analyzed by invoking an array of possible physical mechanisms. Our work suggests that (i) wrist BCG-PPG PTT is consistent under standing and sitting postures with vertically held arms; and (ii) changes in wrist orientation and height as well as restrictions in body and arm movement may alter wrist BCG-PPG PTT via distortions in the wrist BCG and PPG waveforms. The results indicate that wrist BCG-PPG PTT varies with respect to postures even when BP remains constant. The potential of cuff-less BP tracking via wrist BCG-PPG PTT demonstrated under standing posture with arms vertically down in the head-to-foot direction may not generalize to other body and arm postures. Understanding the physical mechanisms responsible for posture-induced BCG-PPG PTT variability may increase the versatility of the wrist BCG for cuff-less BP tracking.

Carotid-Femoral Pulse Transit Time Variability Predicted Mortality and Improved Risk Stratification in the Elderly.

[Figure: see text].

CAROTID-TO-FEMORAL PULSE TRANSIT TIME VARIABILITY PREDICTS ALL-CAUSE AND CARDIOVASCULAR MORTALITY IN CHINESE AND SWEDISH ELDERLY

Objective: Acquisition of pulses at carotid and femoral arteries allows measurement of carotid-femoral pulse wave velocity (cf-PWV) via determination of pulse transit time (PTT) and pulse travelled distance. PWV predicts adverse outcome and contributes to risk stratification. However, little is known about the PTT variability during the cf-PWV measurement and its predictive value. Design and method: Community-based prospective cohorts of elderly population from Shanghai, China and Malmö, Sweden were included in the study. The cf-PWV, cf-PTT and its coefficient of variation (CV) were measured with the Sphygmocor device. Vital status in both cohorts and cause of death in the Malmö subjects were ascertained. Cox proportional hazard model and Fine-Gray competing risk model were applied for analysis. Results: Of the 1249 (median age, 75.6 years; 42.5% men) and 2999 (72.4 years; 39.6% men) participants from Shanghai and Malmö who were followed up for a median of 8.9 and 6.6 years, respectively, 292 (23.3%) and 388 (12.9%) died, respectively. The cf-PWV (median: 9.4 vs. 8.7 m/s in Shanghai and 11.2 vs. 9.9 m/s in Malmö) and CV of cf-PTT (median: 8.6 vs. 7.4 % in Shanghai and 9.0 vs. 7.9 % in Malmö) were significantly higher in the deceased people compared to those survived. Age, body mass index, heart rate, mean blood pressure and pulse pressure were determinants (P < 0.05) of the CV of PTT in both cohorts. Each 1-standard deviation increase in the log-transformed CV of cf-PTT was associated with a 14% (95% CI, 1–28%) increased risk of all-cause mortality in Shanghai subjects and 25% (13–37%) and 59% (34–89%) increased risk of all-cause and cardiovascular mortality in Malmö subjects. Adding the CV of cf-PTT to the models including cf-PWV had significant net reclassification improvement (0.202 [0.062–0.321]; P = 0.007) and integrated discrimination improvement (0.013[0.001–0.039]; P = 0.02) for cardiovascular mortality in Malmö subjects. Conclusions: The variability of cf-PTT during the cf-PWV measurement was predictive of mortality and improved risk prediction in the elderly.

Enhancing Detection Accuracy for Clinical Heart Failure Utilizing Pulse Transit Time Variability and Machine Learning

Physiological signal variability can offer important insight into cardiovascular activity and clinical cardiovascular diseases. Heart rate variability (HRV) and pulse transit time variability (PTTV) are two important time series variabilities. However, combining HRV and PTTV can enhance the classification accuracy for heart failure which is unknown. In this paper, a simultaneous analysis of HRV and PTTV performed on both normal subjects and heart failure patients, was carried out, aiming to investigate the improvement of HRV-based heart failure detection with the assistant of PTTV analysis. Forty normal subjects and forty heart failure patients were enrolled. Standard limb lead-II electrocardiogram and radial artery pressure waveforms were synchronously recorded. HRV and PTTV analysis were performed on the acquired RR and PTT time series using the standard time- (MEAN, SDNN, and RMSSD), frequency- (LF, HF, and LF/HF), and non-linear (SD1, SD2, sample entropy, and fuzzy measure entropy) domain indices. The results showed that all HRV indices except MEAN (P = 0.1) and LF/HF (P = 0.9) showed significant differences (all P <0.01) between the two group, while only MEAN in PTTV significantly decreases in heart failure patients (P < 0.01). Moreover, when combined the HRV, PTTV indices, and the predicted probabilities generated from the distance distribution matrix-based convolutional neural network models, the highest classification performances were achieved by a support vector machine classifier, outputting a sensitivity of 0.93, a specificity of 0.88, and an accuracy of 0.90. This paper demonstrated the potential of PTTV analysis for the detection of clinical heart failure.

Effect of a Percutaneous Coronary Intervention Procedure on Heart Rate Variability and Pulse Transit Time Variability: A Comparison Study Based on Fuzzy Measure Entropy

Percutaneous coronary intervention (PCI) is a common treatment method for patients with coronary artery disease (CAD), but its effect on synchronously measured heart rate variability (HRV) and pulse transit time variability (PTTV) have not been well established. This study aimed to verify whether PCI for CAD patients affects both HRV and PTTV parameters. Sixteen CAD patients were enrolled. Two five-minute ECG and finger photoplethysmography (PPG) signals were recorded, one within 24 h before PCI and another within 24 h after PCI. The changes of RR and pulse transit time (PTT) intervals due to the PCI procedure were first compared. Then, HRV and PTTV were evaluated by a standard short-term time-domain variability index of standard deviation of time series (SDTS) and our previously developed entropy-based index of fuzzy measure entropy (FuzzyMEn). To test the effect of different time series length on HRV and PTTV results, we segmented the RR and PTT time series using four time windows of 200, 100, 50 and 25 beats respectively. The PCI-induced changes in HRV and PTTV, as well as in RR and PTT intervals, are different. PCI procedure significantly decreased RR intervals (before PCI 973 ± 85 vs. after PCI 907 ± 100 ms, p &lt; 0.05) while significantly increasing PTT intervals (207 ± 18 vs. 214 ± 19 ms, p &lt; 0.01). For HRV, SDTS-only output significant lower values after PCI when time windows are 100 and 25 beats while presenting no significant decreases for other two time windows. By contrast, FuzzyMEn gave significant lower values after PCI for all four time windows (all p &lt; 0.05). For PTTV, SDTS hardly changed after PCI at any time window (all p &gt; 0.90) whereas FuzzyMEn still reported significant lower values (p &lt; 0.05 for 25 beats time window and p &lt; 0.01 for other three time windows). For both HRV and PTTV, with the increase of time window values, SDTS decreased while FuzzyMEn increased. This pilot study demonstrated that the RR interval decreased whereas the PTT interval increased after the PCI procedure and that there were significant reductions in both HRV and PTTV immediately after PCI using the FuzzyMEn method, indicating the changes in underlying mechanisms in cardiovascular system.

Pulse Transit Time Variability Predicts Severe Hypotension after Spinal Anesthesia for Elective Cesarean Delivery

Hypotension after spinal anesthesia for elective cesarean delivery may be harmful. This article first proposed pulse transit time variability (PTTV) analysis could be applied in the preoperative assessment of its risk. 42 patients were classified into groups of Mild, Moderate and Severe. Frequency domain analysis was performed on the day before surgery using autoregressive model. We divided the frequency band according to the troughs and extracted relevant parameters of power spectrum, while differences between groups were evaluated by t-test. The results indicating significant differences are presented in PR5, PR1/PR5, PR3/PR5 and PR4/PR5, with their discriminant accuracy on the 42 patients reaching 80.77% in low-BP group and 75% in norm-BP group. We conclude PTTV analysis can help predict the risk of hypotension on the day before surgery and the physiological mechanism is mainly due to parasympathetic regulation.

PTT Variability for Discrimination of Sleep Apnea Related Decreases in the Amplitude Fluctuations of PPG Signal in Children

In this paper, an analysis of pulse transit time variability (PTTV) during decreases in the amplitude fluctuations of pulse photoplethysmography signal (PPG) (DAP) events for obstructive sleep apnea syndrome (OSAS) screening is presented. The temporal evolution of time-frequency PTTV parameters during DAP was analyzed. The results show an increase in the sympathetic activity index low-frequency component (LF) during DAP for PTTV (85%) significantly higher than for heart rate variability (HRV) (33%), (p < 10(-13)). However, decreases in parasympathetic activity produce lower decrements in high-frequency component (HF) indexes for PTTV (18%) than for HRV (22%). Thus, PTTV reflects sympathetic changes more clearly than HRV. A clinical study was carried out. DAP events were classified as apneic or nonapneic using a linear discriminant analysis from the PTTV indexes. The ratio of DAP events per hour r (DAP), the ratio after filtering based on HRV indexes r (HRV) (DAP), or on PTTV indexes r (PTTV) (DAP), were computed. The results show an accuracy of 75% for r (PTTV) (DAP) (14% increase with respect to r (DAP) and 5% increase with respect to r (HRV) (DAP)), a sensitivity of 81.8%, and a specificity of 73.9% when classifying 1-h polysomnographic excerpts as OSAS or normal. These results suggest that the combination of DAP and PTTV could be better alternative for sleep apnea screening using PPG with the added benefit of its low cost and simplicity.

Measurement of respiratory pulse transit time variation as an intravascular volume index in simulated hemorrhage.

We examined the usefulness of respiratory pulse transit time (PTT) variation as an intravascular volume index in young, healthy, spontaneous, paced breathing volunteers exposed to simulated central hypovolemia by lower body negative pressure (LBNP). With paced breathing at 0.25 Hz, beat-to-beat finger blood pressure (BP), heart rate (HR), cardiac output (CO), stroke volume (SV), total peripheral resistance (TPR), and PTT were measured non-invasively in 18 healthy volunteers. Graded central hypovolemia was generated using LBNP from 0 to -20, -30, -40, and -50 mmHg. Respiratory PTT variation (PTTV) was calculated as the difference of maximal and minimal values divided by their respective means. Respiratory-frequency PTT variability (PTTRF) using power spectral analysis was also estimated. During LBNP, SV, CO and PTTRF decreased, but PTT, PTTV and TPR increased significantly. PTTV did not correlate with SV changes (r = -0.08, P = 0.52), but PTTRF (r = 0.58, P < 0.01) and PTT (r = 0.43, P < 0.01) did during progressive hypovolemia. PTTRF is more applicable to the changes in intravascular volume than PTT and PTTV, suggesting spectral analysis of PTT might be used as a dynamic preload index in patients with spontaneous and paced breathing condition, which needs further studies.