Increasing accuracy of pulse transit time measurements by automated elimination of distorted photoplethysmography waves

Minimum detectable change estimates of heart-to-finger arterial pulse wave conduction time in cardiovascular-healthy young adults

BACKGROUND

Pulse wave velocity (PWV) measurements are the gold standard for assessing arterial stiffness and estimating time or treatment-related changes in cardiovascular status. What constitutes a statistically significant change is an important clinical consideration. This study aimed to describe the variability of heart-to-finger pulse wave conduction time (PWCT) to provide estimates of the minimum detectable change (MDC) dependent on the number of PWCT samples used.

MATERIALS AND METHODS

Heart-to-finger PWCT was measured based on the time delay between the peak of the EKG R-wave and arterial pulse arrival at the left hand index finger as measured by a photoplethysmographic sensor. Measurements were done in 10 young adults (25.7 ± 1.2 years) while supine for 45 min. Depending on the subject's heart rate, these measurements yielded 2430 to 3750 contiguous PWCT for analysis. The variability in these PWCTs was used to determine the minimal detectable percentage change for specified p-values of 0.05, 0.01, and 0.001.

RESULTS

Sample sizes of 10, 30, 50, or 300 contiguous PWCTs yield similar MDC estimates for a given targeted p-value. The MDC% depended on the chosen p-value, with values of MDC% for p-values of 0.05, 0.01, and 0.001 being 7.8%, 10.5%, and 13.6%.

CONCLUSIONS

The estimates may help plan experiments when changes or differences in PWCT or PWV are of interest. Also, these MDC estimates may help assess the validity of clinical study outcomes if PWV changes are outcome measures. The main limitation of the estimates is that they are based on 10 healthy subjects.

Contactless and short-range vital signs detection with doppler radar millimetre-wave (76-81 GHz) sensing firmware

Vital signs such as heart rate (HR) and respiration rate (RR) are essential physiological parameters that are routinely used to monitor human health and bodily functions. They can be continuously monitored through contact or contactless measurements performed in the home or a hospital. In this study, a contactless Doppler radar W-band sensing system was used for short-range, contactless vital sign estimation. Frequency-modulated continuous wave (FMCW) measurements were performed to reduce the influence of a patient's micromotion. Sensing software was developed that can process the received chirps to filter and extract heartbeat and breathing rhythm signals. The proposed contactless sensing system eliminates the need for the contact electrodes, electric patches, photoelectric sensors, and conductive wires used in typical physiological sensing methods. The system operates at 76-81 GHz in FMCW mode and can detect objects on the basis of changes in frequency and phase. The obtained signals are used to precisely monitor a patient's HR and RR with minimal noise interference. In a laboratory setting, the heartbeats and breathing rhythm signals of healthy young participants were measured, and their HR and RR were estimated through frequency- and time-domain analyses. The experimental results confirmed the feasibility of the proposed W-band mm-wave radar for contactless and short-range continuous detection of human vital signs.

Severe obstructive sleep apnea in children with syndromic craniosynostosis: analysis of pulse transit time

STUDY OBJECTIVES

We examined the association between pulse transit time (PTT) and obstructive sleep apnea (OSA) in children with syndromic craniosynostosis (SCS), where OSA is a common problem and may cause cardiorespiratory disturbance.

METHODS

A retrospective study of children (age < 18 years) with SCS and moderate-to-severe OSA (ie, obstructive apnea-hypopnea index ≥ 5) or no OSA (obstructive apnea-hypopnea index < 1) who underwent overnight polysomnography. Children without SCS and normal polysomnography were included as controls. Reference intervals for PTT were computed by nonparametric bootstrap analysis. Based on reference intervals of controls, the sensitivity and specificity of PTT to detect OSA were determined. In a linear mixed model, the explanatory variables assessed were sex, age, sleep stage, and time after obstructive events.

RESULTS

In all 68 included children (19 with SCS with OSA, 30 with SCS without OSA, 19 controls), obstructive events occurred throughout all sleep stages, most prominently during rapid eye movement (REM) sleep and non-REM sleep stages N1 and N2, with evident PTT changes. The greatest reductions were observed 4-8 seconds after an event (P < .05). In SCS with OSA, PTT reference intervals were lower during all sleep stages compared with SCS without OSA. The highest sensitivity was observed during N1 (55.5%), and the highest specificity during REM sleep (76.5%). The lowest PTT values were identified during N1.

CONCLUSIONS

Obstructive events occur throughout all sleep stages with transient reductions in PTT. However, PTT as a variable for OSA detection is limited by its sensitivity and specificity.

CITATION

Yang S, van Twist E, van Heesch GGM, et al. Severe obstructive sleep apnea in children with syndromic craniosynostosis: analysis of pulse transit time. J Clin Sleep Med. 2024;20(8):1233-1240.

Variation in blood pressure and heart rate of radiological technologists in worktime tracked by a wearable device: A preliminary study

The aim of this preliminary study was to measure the systolic BP (SBP) and diastolic BP (DBP) and heart rate (HR) of radiological technologists by WD, and evaluate variation among individuals by worktime, day of the week, job, and workplace. Measurements were obtained using a wristwatch-type WD with optical measurement technology that can measure SBP and DBP every 10 minutes and HR every 30 minutes. SBP, DBP, and HR data obtained at baseline and during work time were combined with the hours of work, day of the week, job, and workplace recorded by the participants in 8 consecutive weeks. We calculated the mean, the ratio to baseline and coefficient of variation [CV(%)] for SBP, DBP, and HR. SBP, DBP, and HR values were significantly higher during work hours than at baseline (p<0.03). The ratio to baseline values ranged from 1.02 to 1.26 for SBP and from 1.07 to 1.30 for DBP. The ratio to baseline for SBP and DBP showed CV(%) of approximately 10% according to the day of the week and over the study period. For HR, ratio to baseline ranged from 0.95 to 1.29. The ratio of mean BP to baseline was >1.2 at the time of starting work, middle and after lunch, and at 14:00. The ratio to baseline of SBP were 1.2 or more for irradiation, equipment accuracy control, registration of patient data, dose verification and conference time, and were also working in CT examination room, treatment planning room, linac room, and the office. CV(%) of BP and HR were generally stable for all workplaces. WD measurements of SBP, DBP, and HR were higher during working hours than at baseline and varied by the individuals, work time, job, and workplace. This method may enable evaluation of unconscious workload in individuals.

Wearable blood pressure measurement devices and new approaches in hypertension management: the digital era

Out-of-office blood pressure (BP) measurement is considered an integral component of the diagnostic algorithm and management of hypertension. In the era of digitalization, a great deal of wearable BP measuring devices has been developed. These digital blood pressure monitors allow frequent BP measurements with minimal annoyance to the patient while they do promise radical changes regarding the diagnostic accuracy, as the importance of making an accurate diagnosis of hypertension has become evident. By increasing the number of BP measurements in different conditions, these monitors allow accurate identification of different clinical phenotypes, such as masked hypertension and pathological BP variability, that seem to have a negative impact on cardiovascular prognosis. Frequent measurements of BP and the incorporation of new features in BP variability, both enable well-rounded interpretation of BP data in the context of real-life settings. This article is a review of all different technologies and wearable BP monitoring devices.

Feasibility of home-based tracking of insulin resistance from vascular stiffness estimated from the photoplethysmographic finger pulse waveform

In this study, we explored the utility of post-prandial vascular stiffness as a surrogate measure for the estimation of insulin resistance (IR), which is a pre-diabetic condition. A cohort of 51 healthy young adults of varying Body mass index values (BMI) were studied by fasting plasma values of insulin and glucose; fasting and post-meal finger photoplethysmography (PPG), and electrocardiogram (ECG). Insulin resistance was estimated by Homeostatic model assessment-Insulin resistance 2 (HOMA-IR2) using fasting plasma insulin and glucose. Vascular stiffness was estimated by reciprocal of pulse arrival time (rPAT) from ECG and finger PPG at five time points from fasting to 2-hours post oral glucose ingestion. We examined if insulin resistance is correlated with meal induced vascular stiffness changes supporting the feasibility of using finger PPG for the estimation of insulin resistance. HOMA-IR2 was found to be positively correlated with early rise (0- to 30- minutes post meal) and delayed fall (30- to 120-minutes) of rPAT. Correlation persisted even after the effect of BMI has been partialled out in sub-group analysis. We conclude that finger PPG based pulse waveform and single lead ECG has the potential to be used as a non-invasive method for the assessment of insulin resistance. As both signals viz., ECG and PPG can be easily acquired using wearable and other low-cost sensing systems, the present study can serve as a pointer for the development of accessible methods of monitoring and longitudinal tracking of insulin resistance in health and pathophysiological states.

Hap-pulse: A Wearable Vibrotactile Glove for Medical Pulse Wave Rendering

Pulse palpation is an important procedure that allows a physician to rapidly assess the status of a patient's cardiovascular system. This paper explores the possibility of using vibrotactile stimuli to render fine temporal profiles of pulse pressure waves. A lightweight wearable vibrotactile glove, called Hap-pulse, is designed to render fine pulse waves through vibrotactile stimuli on users' fingertips. To preserve the fine features of original pulse waves, models are fitted from real pulse wave data (photoplethysmogram (PPG) pulse waveform database), using fourth-order polynomial functions. A square wave envelope mapping algorithm is proposed to produce vibration amplitudes of Linear Resonance Actuators (LRAs), which aims to render the detailed waveform of systolic and diastolic blood pressure states. Evaluation results suggest that Hap-pulse can render pulse waves with an average correlation coefficient 97.84%. To validate the distinguishability and fidelity of Hap-pulse's palpation rendering, a user study consisting of traditional Chinese medicine doctors and unskilled students is conducted. The correct recognition rate of identifying four typical pulse waves is 87.08% (doctors), 57.50% (untrained students) and 79.59% (trained students). These results indicate a novel application of rendering subtle pulse wave signals with vibrotactile gloves, which illustrates the potential of simulating patient palpation training in virtual or remote medical diagnosis.

Blood pressure wave propagation - a multisensor setup for cerebral autoregulation studies

OBJECTIVE

Cerebral autoregulation is critically important to maintain proper brain perfusion and supply the brain with oxygenated blood. Non-invasive measures of blood pressure (BP) are critical in assessing cerebral autoregulation. Wave propogation velocity may be a useful technique to estimate BP but the effect of the location of the sensors on the readings has not been thoroughly examined. In this paper, we were interested to study if propagation velocity of the pressure wave in the direction from the heart to the brain may differ compared with propagation from the heart to the periphery, as well as across different physiological tasks and/or health conditions. Using non-invasive sensors simultaneously placed on different locations of the human body allow for the study of how propagation velocity of the pressure wave, based on pulse transit time (PTT), varies across different directions.

APPROACH

We present multi-sensor BP wave propagation measurement setup aimed for cerebral autoregulation studies. The presented sensor setup consists of three sensors, one each placed on the neck, chest and finger, allowing simultaneous measurement of changes in BP propagation velocity towards the brain and to the periphery. We show how commonly tested physiological tasks affect the relative changes of PTT and correlations with BP.

MAIN RESULTS

We observed that during maximal blow, valsalva and breath hold breathing tasks, the relative changes of PTT were higher when PTT was measured in the direction from the heart to the brain than from the heart to the peripherals. In contrast, during a deep breathing task, the relative change in PTT from the heart to the brain was lower. In addition, we present a short literature review of PTT methods used in brain research.

SIGNIFICANCE

These preliminary data suggest that physiological task and direction of PTT measurement may affect relative PTT changes. Presented three-sensor setup provides an easy and neuroimaging compatible method for cerebral autoregulation studies by allowing to measure BP wave propagation velocity towards the brain vs. towards the periphery.

Future possibilities for artificial intelligence in the practical management of hypertension

The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming increasingly more common. This review describes the current status and a future possibility for artificial intelligence in blood pressure management, that is, the possibility of accurately predicting and estimating blood pressure using large-scale data, such as personal health records and electronic medical records. Individual blood pressure continuously changes because of lifestyle habits and the environment. This review focuses on two topics regarding controlling changing blood pressure: a novel blood pressure measurement system and blood pressure analysis using artificial intelligence. Regarding the novel blood pressure measurement system, we compare the conventional cuff-less method with the analysis of pulse waves using artificial intelligence for blood pressure estimation. Then, we describe the prediction of future blood pressure values using machine learning and deep learning. In addition, we summarize factor analysis using "explainable AI" to solve a black-box problem of artificial intelligence. Overall, we show that artificial intelligence is advantageous for hypertension management and can be used to establish clinical evidence for the practical management of hypertension.

Heart-brain interactions shape somatosensory perception and evoked potentials

Even though humans are mostly not aware of their heartbeats, several heartbeat-related effects have been reported to influence conscious perception. It is not clear whether these effects are distinct or related phenomena, or whether they are early sensory effects or late decisional processes. Combining electroencephalography and electrocardiography, along with signal detection theory analyses, we identify two distinct heartbeat-related influences on conscious perception differentially related to early vs. late somatosensory processing. First, an effect on early sensory processing was found for the heartbeat-evoked potential (HEP), a marker of cardiac interoception. The amplitude of the prestimulus HEP negatively correlated with localization and detection of somatosensory stimuli, reflecting a more conservative detection bias (criterion). Importantly, higher HEP amplitudes were followed by decreases in early (P50) as well as late (N140, P300) somatosensory-evoked potential (SEP) amplitudes. Second, stimulus timing along the cardiac cycle also affected perception. During systole, stimuli were detected and correctly localized less frequently, relating to a shift in perceptual sensitivity. This perceptual attenuation was accompanied by the suppression of only late SEP components (P300) and was stronger for individuals with a more stable heart rate. Both heart-related effects were independent of alpha oscillations' influence on somatosensory processing. We explain cardiac cycle timing effects in a predictive coding account and suggest that HEP-related effects might reflect spontaneous shifts between interoception and exteroception or modulations of general attentional resources. Thus, our results provide a general conceptual framework to explain how internal signals can be integrated into our conscious perception of the world.

Non-invasive continuous blood pressure monitoring systems: current and proposed technology issues and challenges

High blood pressure (BP) or hypertension is the single most crucial adjustable risk factor for cardiovascular diseases (CVDs) and monitoring the arterial blood pressure (ABP) is an efficient way to detect and control the prevalence of the cardiovascular health of patients. Therefore, monitoring the regulation of BP during patients' daily life plays a critical role in the ambulatory setting and the latest mobile health technology. In recent years, many studies have been conducted to explore the feasibility and performance of such techniques in the health care system. The ultimate aim of these studies is to find and develop an alternative to conventional BP monitoring by using cuff-less, easy-to-use, fast, and cost-effective devices for controlling and lowering the physical harm of CVDs to the human body. However, most of the current studies are at the prototype phase and face a range of issues and challenges to meet clinical standards. This review focuses on the description and analysis of the latest continuous and cuff-less methods along with their key challenges and barriers. Particularly, most advanced and standard technologies including pulse transit time (PTT), ultrasound, pulse arrival time (PAT), and machine learning are investigated. The accuracy, portability, and comfort of use of these technologies, and the ability to integrate to the wearable healthcare system are discussed. Finally, the future directions for further study are suggested.

Continuous monitoring of cerebrovascular reactivity through pulse transit time and intracranial pressure

OBJECTIVE

Cerebrovascular reactivity (CR) is a mechanism that maintains stable blood flow supply to the brain. Pressure reactivity index (PRx), the correlation coefficient between slow waves of invasive arterial blood pressure (ABP) and intracranial pressure (ICP) has been validated for CR assessment. However, in clinical ward, not every subarachnoid hemorrhage (SAH) patient has invasive ABP monitoring. Pulse transit time (PTT), the propagation time of a pulse wave travelling from the heart to peripheral arteries, has been suggested as a surrogate measure of ABP. In this study, we proposed to use PTT instead of invasive ABP to monitor CR.

APPROACH

Forty-five SAH patients with simultaneous recordings of invasive ABP, ICP, oxygen saturation level (SpO2) and electrocardiograph (ECG) were included. PTT was calculated as the time from the ECG R-wave peak to the onset of SpO2. PTT based pressure reactivity index (tPRx) was calculated as the correlation coefficient between slow waves of PTT and ICP. Wavelet tPRx (wtRx) was calculated as the cosine of wavelet phase shift between PTT and ICP. Meanwhile, PRx and wPRx were also calculated using invasive ABP and ICP as input.

MAIN RESULTS

The result showed a negative relationship between PTT and ABP (r  =  -0.58, p   <  0.001). tPRx negatively correlated with PRx (r  =  -0.51, p   =  0.003). Wavelet method correlated well with correlation method demonstrated through positive relationship between wPRx and PRx (r  =  0.82, p   <  0.001) as well as wtPRx and tPRx (r  =  0.84, p   <  0.001).

SIGNIFICANCE

PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable. Key points • Pulse transit time (PTT), defined as the propagation time of a pulse wave travelling from the heart to the peripheral arteries, has been proposed as a surrogate measure of ABP. The relationship between PTT and ABP in SAH patients remains unknown. • Cerebrovascular reactivity (CR) assessment through PTT has advantages over invasive ABP, as it avoids bleeding and infection risk, and can be used outside of the ICU. • We introduced a new method to assess CR using PTT and ICP through correlation based method and wavelet based method. • We found that beat-to-beat PTT was negatively related with invasive ABP in SAH patients. A significant linear relationship exists between PTT-based CR parameter and a well validated method, PRx. PTT demonstrates great potential as a useful tool for CR assessment when invasive ABP is unavailable in SAH patients.

Small intra-individual variability of the pre-ejection period justifies the use of pulse transit time as approximation of the vascular transit

Background

Vascular transit time (VTT) is the propagation time of a pulse wave through an artery; it is a measure for arterial stiffness. Because reliable non-invasive VTT measurements are difficult, as an alternative we measure pulse transit time (PTT). PTT is defined as the time between the R-wave on electrocardiogram and arrival of the resulting pulse wave in a distal location measured with photoplethysmography (PPG). The time between electrical activation of the ventricles and the resulting pulse wave after opening of the aortic valve is called the pre-ejection period (PEP), a component of PTT. The aim of this study was to estimate the variability of PEP at rest, to establish how accurate PTT is as approximation of VTT.

Methods

PTT was measured and PEP was assessed with echocardiography (gold standard) in three groups of 20 volunteers: 1) a control group without cardiovascular disease aged <50 years and 2) aged >50 years, and 3) a group with cardiovascular risk factors, defined as arterial hypertension, dyslipidemia, kidney failure and diabetes mellitus.

Results

Per group, the mean PEP was: 1) 58.5 ± 13.0 ms, 2) 52.4 ± 11.9 ms, and 3) 57.6 ± 11.6 ms. However, per individual the standard deviation was much smaller, i.e. 1) 2.0–5.9 ms, 2) 2.8–5.1 ms, and 3) 1.6–12.0 ms, respectively. There was no significant difference in the mean PEP of the 3 groups (p = 0.236).

Conclusion

In conclusion, the intra-individual variability of PEP is small. A change in PTT in a person at rest is most probably the result of a change in VTT rather than of PEP. Thus, PTT at rest is an easy, non-invasive and accurate approximation of VTT for monitoring arterial stiffness.

Comparison between pulse wave velocities measured using Complior and measured using Biopac

Arterial stiffness is a reliable prognostic parameter for cardiovascular diseases. The effect of change in arterial stiffness can be measured by the change of the pulse wave velocity (PWV). The Complior system is widely used to measure PWV between the carotid and radial arteries by means of piezoelectric clips placed around the neck and the wrist. The Biopac system is an easier to use alternative that uses ECG and simple optical sensors to measure the PWV between the heart and the fingertips, and thus extends a bit more to the peripheral vasculature compared to the Complior system. The goal of this study was to test under various conditions to what extent these systems provide comparable and correlating values. 25 Healthy volunteers, 20-30 years old, were measured in four sequential position: sitting, lying, standing and sitting. The results showed that the Biopac system measured consistently and significantly lower PWV values than the Complior system, for all positions. Correlation values and Bland-Altman plots showed that despite the difference in PWV magnitudes obtained by the two systems the measurements did agree well. Which implies that as long as the differences in PWV magnitudes are taken into account, either system could be used to measure PWV changes over time. However, when basing diagnosis on absolute PWV values, one should be very much aware of how the PWV was measured and with what system.