Pulse transit time: an appraisal of potential clinical applications

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.

Pulse Wave Velocity: Methodology, Clinical Applications, and Interplay with Heart Rate Variability

Pulse wave velocity (PWV) has been established as a promising biomarker in cardiovascular diagnostics, providing deep insights into vascular health and cardiovascular risk. Defined as the velocity at which the mechanical wave propagates along the arterial wall, PWV represents a useful surrogate marker for arterial vessel stiffness. PWV has garnered clinical attention, particularly in monitoring patients suffering from vascular diseases such as hypertension and diabetes mellitus. Its utility extends to preventive cardiology, aiding in identifying and stratifying cardiovascular risk. Despite the development of various measurement techniques, direct or indirect tonometry, Doppler ultrasound, oscillometric analysis, and magnetic resonance imaging (MRI), methodological variability and lack of standardization lead to inconsistencies in PWV assessment. In addition, PWV can be estimated through surrogate parameters, such as pulse arrival or pulse transit times, although this heterogeneity limits standardization and, therefore, its clinical use. Furthermore, confounding factors, such as variations in sympathetic tone, strongly influence PWV readings, thereby necessitating careful control during assessments. The bidirectional relationship between heart rate variability (HRV) and PWV underscores the interplay between cardiac autonomic function and vascular health, suggesting that alterations in one could directly influence the other. Future research should prioritize the standardization and increase comparability of PWV measurement techniques and explore the complex physiological variables influencing PWV. Integrating multiple physiological parameters such as PWV and HRV into algorithms based on artificial intelligence holds immense promise for advancing personalized vascular health assessments and cardiovascular care.

Investigating the relationship between early cardiovascular disease markers and loneliness in young adults

Loneliness is recognised as a risk factor for cardiovascular disease development. However, it is unclear whether loneliness itself or other closely related mental health symptoms, such as depression and social anxiety, are associated with the development of cardiovascular disease. In the present study, we examined the relationship between loneliness and several early cardiovascular disease markers in young adults, after controlling for depression and social anxiety. Sixty-six young adults (18-35 years old, Mage = 22.70; 75.8% females) completed psychological questionnaires and took part in several physiological tests assessing cardiovascular health (e.g., vascular function). Results revealed higher loneliness was significantly associated with shorter pulse transit time (β = - 0.70, p = 0.002; shorter pulse transit time is a subclinical marker for arterial stiffness). Additionally, results show that while loneliness and depression were both related to vascular dysfunction in young adults, the underlining physiological mechanisms through which they affect vascular function may be different. Specifically, higher loneliness was associated with increased arterial stiffness, whereas depression was associated with increased endothelial dysfunction (β = - 0.43, p = 0.04). Our findings indicate that presence of loneliness and depression in young adults may be accompanied by early indicators of poor cardiovascular health, such as arterial stiffness and endothelial dysfunction. Results from the study further support the link between loneliness and cardiovascular disease development.

Flexible Strain Sensors Based on an Interlayer Synergistic Effect of Nanomaterials for Continuous and Noninvasive Blood Pressure Monitoring

The continuous, noninvasive monitoring of human blood pressure (BP) through the accurate detection of pulse waves has extremely stringent requirements on the sensitivity and stability of flexible strain sensors. In this study, a new ultrasensitive flexible strain sensor based on the interlayer synergistic effect was fabricated through drop-casting and drying silver nanowires and graphene films on polydimethylsiloxane substrates and was further successfully applied for continuous monitoring of BP. This strain sensor exhibited ultrahigh sensitivity with a maximum gauge factor of 34357.2 (∼700% sensitivity enhancement over other major sensors), satisfactory response time (∼85 ms), wide strange range (12%), and excellent stability. An interlayer fracture mechanism was proposed to elucidate the working principle of the strain sensor. The real-time BP values can be obtained by analyzing the relationship between the BP and the pulse transit time. To verify our strain sensor for real-time BP monitoring, our strain sensor was compared with a conventional electrocardiogram-photoplethysmograph method and a commercial cuff-based device and showed similar measurement results to BP values from both methods, with only minor differences of 0.693, 0.073, and 0.566 mmHg in the systolic BP, diastolic BP, and mean arterial pressure, respectively. Furthermore, the reliability of the strain sensors was validated by testing 20 human subjects for more than 50 min. This ultrasensitive strain sensor provides a new pathway for continuous and noninvasive BP monitoring.

Calibration-free blood pressure estimation based on a convolutional neural network

In this study, we conducted research on a deep learning-based blood pressure (BP) estimation model suitable for wearable environments. To measure BP while wearing a wearable watch, it needs to be considered that computing power for signal processing is limited and the input signals are subject to noise interference. Therefore, we employed a convolutional neural network (CNN) as the BP estimation model and utilized time-series electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which are quantifiable in a wearable context. We generated periodic input signals and used differential and thresholding methods to decrease noise in the preprocessing step. We then applied a max-pooling technique with filter sizes of 2 × 1 and 5 × 1 within a 3-layer convolutional neural network to estimate BP. Our method was trained, validated, and tested using 2.4 million data samples from 49 patients in the intensive care unit. These samples, totaling 3.1 GB were obtained from the publicly accessible MIMIC database. As a result of a test with 480,000 data samples, the average root mean square error in BP estimation was 3.41, 5.80, and 2.78 mm Hg in the prediction of pulse pressure, systolic BP (SBP), and diastolic BP (DBP), respectively. The cumulative error percentage less than 5 mm Hg was 68% and 93% for SBP and DBP, respectively. In addition, the cumulative error percentage less than 15 mm Hg was 98% and 99% for SBP and DBP. Subsequently, we evaluated the impact of changes in input signal length (1 cycle vs. 30 s) and the introduction of noise on BP estimation results. The experimental results revealed that the length of the input signal did not significantly affect the performance of CNN-based analysis. When estimating BP using noise-added ECG signals, the mean absolute error (MAE) for SBP and DBP was 9.72 and 6.67 mm Hg, respectively. Meanwhile, when using noise-added PPG signals, the MAE for SBP and DBP was 26.85 and 14.00 mm Hg, respectively. Therefore, this study confirmed that using ECG signals rather than PPG signals is advantageous for noise reduction in a wearable environment. Besides, short sampling frames without calibration can be effective as input signals. Furthermore, it demonstrated that using a model suitable for information extraction rather than a specialized deep learning model for sequential data can yield satisfactory results in BP estimation.

The importance of pulmonary pulse transit time in indicating right ventricular dysfunction and pulmonary arterial stiffness in rheumatoid arthritis

SUBJECT

Rheumatoid arthritis patients are at risk of developing cardiovascular disease such as right heart failure and pulmonary hypertension (PH). Arterial stiffness can be used to assess pulmonary hemodynamics. Noninvasive approaches can also be used to assess pulmonary hemodynamics. Recently, there have been reports that pulmonary pulse transit time (PPTT) may also be a useful measure. This study aims to examine the effects of pulmonary hemodynamic alterations on PPTT in RA patients.

METHODS

Forty RA patients and 40 healthy controls were included in the study. Sociodemographic characteristics, laboratory data, and echocardiographic examinations were performed in both groups. Conventional echocardiographic examination included left and right ventricular systolic and diastolic diameters, right ventricular myocardial performance index (RVMPI), right ventricular diastolic function, estimated pulmonary artery systolic pressure (sPAP), tricuspid annular plane systolic excursion (TAPSE), pulmonary artery stiffness (PAS), and PPTT. Right ventricular diastolic and systolic volumes, right ventricular ejection fraction (RVEF), and right ventricular fractional area change (RVFAC) were determined by four-dimensional echocardiography (4DE).

RESULTS

There was no difference between the sPAP values of the patients. RVMPI and PAS were increased in RA patients compared with controls. The PPTT was shortened in RA patients and correlated with RVEF, RVFAC, RVMPI, TAPSE/sPAP, disease duration, and C-reactive protein (CRP). In univariate linear regression analysis, PPTT (p < .001) was thought to be an independent predictor of PAS. RVFAC, disease duration, and PAS were also independent predictors of PPTT.

CONCLUSION

In RA patients, PPTT may be the first evidence of early abnormalities in pulmonary vascular hemodynamics. PPTT and PAS are the values that may predict each other in RA patients. Due to its more practical application, PPTT can be used instead of PAS to assess pulmonary hemodynamics.

Camera Wavelength Selection for Multi-wavelength Pulse Transit Time based Blood Pressure Monitoring

Multi-wavelength pulse transmit time (MV-PTT) is a potential tool for remote blood pressure (BP) monitoring. It uses two wavelengths, typically green (G) and near-infrared (NIR), that have different skin penetration depths to measure the PTT between artery and arterioles of a single site of the skin for BP estimation. However, the impact of wavelength selection for MV-PTT based BP calibration is unknown. In this paper, we explore the combination of different wavelengths of camera photoplethysmography for BP measurement using a modified narrow-band camera centered at G-550/R-660/NIR-850 nm, especially focused on the comparison between G-R (full visible) and G-NIR (hybrid). The experiment was conducted on 17 adult participants in a dark chamber with their BP significantly changed by the protocol of ice water stimulation. The experimental results show that the MV-PTT obtained by G-NIR has a higher correlation with BP, and the fitted model has lower MAE in both the systolic pressure (5.78 mmHg) and diastolic pressure (6.67 mmHg) than others. It is confirmed that a hybrid wavelength of visible (G) and NIR is still essential for accurate BP calibration due to their difference in skin penetration depth that allows proper sensing of different skin layers for this measurement.

Progressive resistance training ameliorates deteriorating cardiac autonomic dysfunction, subclinical inflammation and endothelial dysfunction in type 2 diabetes mellitus: A randomized control trial

BACKGROUND AND AIMS

To investigate the effect of resistance training (RT) on outcomes of cardiac autonomic control, biomarkers of subclinical inflammation, endothelial dysfunction, and angiotensin II in T2DM patients with CAN.

METHODS

Fifty six T2DM patients with CAN were recruited in the present study.After baseline assessment of all outcome variables, patients were randomly allocated into two groups - RT (n = 28) and Control (n = 28). The experimental group underwent 12 weeks of RT and the control group received usual care. RT was performed at an intensity of 65%-75% of 1 RM, 3 times/week for 12 weeks. RT program included 10 exercises of major muscle groups in the body. Cardiac autonomic control parameters, subclinical inflammation and endothelial dysfunction biomarkers, and serum angiotensin II concentration were assessed at baseline and after 12 weeks.

RESULTS

Parameters of cardiac autonomic control showed significant improvement after RT (p < 0.05). Interleukin-6, interleukin-18 were significantly reduced while endothelial nitric oxide synthase was significantly increased post-RT (p < 0.05).

CONCLUSIONS

Findings of the present study suggest that RT has the potential to enhance deteriorating cardiac autonomic function in T2DM patients with CAN. RT also seems to have an anti-inflammatory role and it may also play some role in vascular remodeling in these patients.

TRIAL REGISTRATION

CTRI/2018/04/013321, Registered prospectively on 13th April 2018, Clinical Trial Registry, India.

Wearable Continuous Blood Pressure Monitoring Devices Based on Pulse Wave Transit Time and Pulse Arrival Time: A Review

Continuous blood pressure (BP) monitoring is of great significance for the real-time monitoring and early prevention of cardiovascular diseases. Recently, wearable BP monitoring devices have made great progress in the development of daily BP monitoring because they adapt to long-term and high-comfort wear requirements. However, the research and development of wearable continuous BP monitoring devices still face great challenges such as obvious motion noise and slow dynamic response speeds. The pulse wave transit time method which is combined with photoplethysmography (PPG) waves and electrocardiogram (ECG) waves for continuous BP monitoring has received wide attention due to its advantages in terms of excellent dynamic response characteristics and high accuracy. Here, we review the recent state-of-art wearable continuous BP monitoring devices and related technology based on the pulse wave transit time; their measuring principles, design methods, preparation processes, and properties are analyzed in detail. In addition, the potential development directions and challenges of wearable continuous BP monitoring devices based on the pulse wave transit time method are discussed.

A novel method for non-invasive blood pressure estimation based on continuous pulse transit time: An observational study

Unlike traditional pulse transit time (PTT), continuous PTT (CPTT) can be used to calculate PTT from all samples within the cardiac cycle. It has the potential to be utilized for continuous blood pressure (BP) estimation. This study evaluated the feasibility of CPTT as a non-invasive consecutive blood pressure estimation method in 20 volunteers. The CPTT was calculated with a time delay in all discrete samples of photoplethysmograms measured at two different body sites. BP was then calculated with a regression equation. For comparative evaluation, BP based on PTT was also estimated. Continuous blood pressure was measured using a non-invasive volume clamp BP monitoring device. Four types of BP measurement, systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), were estimated using PTT and CPTT. Correlation coefficients and root-mean-squared-error (RMSE) were used for evaluating BP estimation performance. For estimating SBP, DBP, PP, and MAP, PTT-based BP estimation showed correlations of .407, .373, .410, and .286, respectively, and CPTT-based BP estimation showed correlations of .436, .446, .506, and .097, respectively. With PTT-based estimation, the RMSE between the estimated BP and the baseline BP was 5.44 ± 1.56 mmHg for SBP, 3.14 ± 0.46 mmHg for DBP, 3.66 ± 0.70 mmHg for MAP, and 3.73 ± 1.31 mmHg for PP. The estimated BP using CPTT showed RMSE of 5.36 ± 1.39 mmHg for SBP, 3.02 ± 0.49 mmHg for SBP, 3.44 ± 0.63 mmHg for MAP, and 3.91 ± 1.41 mmHg for PP.

Measuring Suite for Vascular Response Monitoring during Hyperbaric Oxygen Therapy by Means of Pulse Transit Time (PTT) Analysis

The efficacy of hyperbaric oxygen therapy in treating wound healing disorders is well established. The obvious explanation is the presence of elevated oxygen tissue tensions during the high-pressure oxygen exposure. This explanation omits that the effective agent, elevated oxygen tension, is only present for 6.25% of the time. To investigate possible prevailing vascular changes caused by HBOT, the presented device monitors the vascular response during therapy by Pulse-Transit-Time analysis. The device allows synchronous 1 kHz ECG and PPG measurements. The data are stored in a 1 GBit flash drive and retrieved post-therapy. Normoxic measurements on the authors with and without nicotine validate the device's functionality. Measurements during HBO therapy have been successfully performed.

Evaluating changes in pulse transit time drop index in patients with obstructive sleep apnea before and during CPAP therapy

Airflow limitation in patients with obstructive sleep apnea (OSA) leads to arousal, increased sympathetic nervous system activity, and elevated blood pressure, which causes a decrease in pulse transit time (PTT). The present study aims to evaluate the effect of CPAP therapy on PTT in patients with moderate to severe OSA. This was a cross‐sectional study. Split‐night polysomnography (PSG) study was performed for each participant with apnea‐hypopnea index (AHI) ≥ 15 before and during CPAP therapy. The PTT was calculated as the time interval between the R wave of the electrocardiogram and the following arrival point in fingertip photoplethysmography. PTT drop was defined as a fall in the PTT curve of ≥15 ms lasting at least for 3 s and at most for 30 s. PTT drop index was defined as the number of drops in PTT that occur per hour of sleep. A total of 30 patients were included. PTT significantly increased, and PTT drop index significantly decreased during CPAP therapy (P < 0.001). PTT was significantly correlated to sleep efficiency (r_s = −0.376, P = 0.049) and oxygen desaturation index (ODI) (r_s = −0.428, P = 0.018). PTT drop index was strongly correlated to AHI (r_s = 0.802, P < 0.001), respiratory disturbance index (RDI) (r_s = 0.807, P < 0.001), ODI (r_s = 0.693, P < 0.001), arousal index (r_s = 0.807, P < 0.001), and periodic leg movement (PLM) index (r_s = 0.400, P = 0.035). Overall, the findings from this study indicated that the PTT drop index is a non‐invasive and useful marker for evaluating the severity of OSA and the effectiveness of treatment in patients with moderate to severe OSA.

Early-onset preeclampsia is characterised by an increased vascular tone in internal jugular veins

Purpose

This study aimed to investigate Doppler characteristics of maternal internal jugular veins in uncomplicated pregnancies vs. those affected by hypertensive disorders.

Materials and methods

Venous pulse transit time and venous impedance index were measured at three different locations (right proximal, right distal, left proximal) of internal jugular veins according to a standardised combined Doppler-Electrocardiogram protocol in five different groups of pregnant women: uncomplicated pregnancy, early-onset preeclampsia, late-onset preeclampsia, gestational hypertension, and normotensive pregnancies with a small for gestational age foetus. Values of both parameters of the latter four groups were plotted against the reference range of uncomplicated pregnancies at corresponding gestation. Linear mixed models with random intercept were used to investigate gestational changes in venous pulse transit time and venous impedance index at the three internal jugular vein locations within and between the different groups.

Results

A total of 127 women were included: 41 had uncomplicated pregnancies, 13 had early-onset preeclampsia, 25 had late-onset preeclampsia, 22 had gestational hypertension, and 26 had normotensive pregnancies with a small for gestational age foetus. Venous pulse transit time values were lower than uncomplicated pregnancy (p ≤ 0.001) at all three locations in the third trimester of early-onset preeclampsia.

Conclusion

Contrary to late-onset preeclampsia and gestational hypertension, early-onset preeclampsia is characterised by a lower venous pulse transit time at internal jugular veins compared to uncomplicated pregnancy, suggesting increased venous vascular tone.

Factors Associated with Variability in Pulse Wave Transit Time Using Pulse Oximetry: A Retrospective Study

Pulse wave transit time (PWTT) is the time difference between the occurrence of an R-wave on an electrocardiogram and the detection of pulsatile signals on a pulse oximeter, which reflects changes in blood pressure (BP) corresponding to the vessel wall compliance. However, the factors affecting PWTT variability have not been determined. Thus, we investigated the BP changes associated with variations in PWTT and identified the clinical characteristics associated with these variations. Data related to 605 cases of dental procedures performed under intravenous conscious sedation from April 2020 to November 2021 were collected, and 485 cases were enrolled. Heart rate, systolic blood pressure before and after local anesthesia (LA) administration, and crest and trough PWTT waves during LA administration were recorded. Thereafter, PWTT variability was calculated; cases were divided into two groups: large PWTT variability (LPV, n = 357) and small PWTT variability (SPV, n = 128). The index of large PWTT variability could not detect changes in BP. Logistic regression analysis revealed that factors, such as LA use, age, hypertension, and dental treatment phobia were associated with PWTT variability. The use of epinephrine more than 36.25 µg in each LA resulted in PWTT variability of more than 15 ms.

A prospective cohort study using non-invasive methods of cardiovascular assessment to compare postnatal adaptation in well late preterm and term infants

Echocardiography was combined with pulse oximetry plethysmography to investigate postnatal cardiovascular adaptation in late preterm and term infants. Median (IQR) pleth variability decreased over three days and similar, day2 15%(12-18%) preterm versus 16%(15-18%) term infants. Median (IQR) pulse transit time heart rate normalised was lower in term babies, day2 0.55(0.51-0.63) versus 0.64(0.62-0.68).

Validation of Continuous Monitoring System for Epileptic Users in Outpatient Settings

Epilepsy is a chronic disease with a significant social impact, given that the patients and their families often live conditioned by the possibility of an epileptic seizure and its possible consequences, such as accidents, injuries, or even sudden unexplained death. In this context, ambulatory monitoring allows the collection of biomedical data about the patients’ health, thus gaining more knowledge about the physiological state and daily activities of each patient in a more personalized manner. For this reason, this article proposes a novel monitoring system composed of different sensors capable of synchronously recording electrocardiogram (ECG), photoplethysmogram (PPG), and ear electroencephalogram (EEG) signals and storing them for further processing and analysis in a microSD card. This system can be used in a static and/or ambulatory way, providing information about the health state through features extracted from the ear EEG signal and the calculation of the heart rate variability (HRV) and pulse travel time (PTT). The different applied processing techniques to improve the quality of these signals are described in this work. A novel algorithm used to compute HRV and PTT robustly and accurately in ambulatory settings is also described. The developed device has also been validated and compared with other commercial systems obtaining similar results. In this way, based on the quality of the obtained signals and the low variability of the computed parameters, even in ambulatory conditions, the developed device can potentially serve as a support tool for clinical decision-taking stages.

Beat-to-beat Estimation of Peripheral Arterial Stiffness from Local PWV for Quantitative Evaluation of Sympathetic Nervous System Activity

Sympathetic nervous system activity (SNSA) can rapidly modulate arterial stiffness, thus making it an important biomarker for SNSA evaluation. Pulse wave velocity (PWV) is a well-known quantitative indicator of arterial stiffness, but its functional responsivity to SNSA has not been elucidated. This paper reports a method to estimate rapid changes in peripheral arterial stiffness induced by SNSA using local PWV (LPWV) and to further quantify SNSA based on the estimated stiffness. LPWV was measured from the artery near the wrist to the artery near the forefinger using a biodegradable piezoelectric sensor and a photoplethysmography sensor in an electrocutaneous stimulus experiment in which pain indicts the SNSA. The relationship between LPWV, simultaneously measured peripheral arterial stiffness index, and self-reported pain intensity was quantified. The stiffness estimated by LPWV alone and the stiffness estimated by LPWV and arterial pressure both approximate the peripheral arterial stiffness index (R² = 0.9775 and 0.9719). Pain intensity can be quantitatively evaluated in a sigmoidal relationship by either the estimated stiffness based on LPWV alone (r = 0.8594) or the estimated stiffness based on LPWV and arterial pressure (r = 0.9738). Our results demonstrated the validity of LPWV in the quantitative evaluation of SNSA and the optionality of blood pressure correction depending on application scenarios. This study advances the understanding of sympathetic innervation of peripheral arteries through the sympathetic responsivity of LPWV and contributes a quantitative biomarker for SNSA evaluation.

Assessing patent ductus arteriosus in preterm infants from standard neonatal intensive care monitoring

Monitoring patent ductus arteriosus (PDA) in premature infants is currently performed intermittently using echocardiography which requires considerable expertise. The aim of this pilot study was to investigate whether PDA status could be assessed from standard neonatal intensive care monitoring. Electrocardiography (ECG) and blood pressure (BP) waveforms were acquired from extremely preterm infants using standard neonatal monitors. We developed software using MATLAB to analyse ECG and BP waveforms and their interrelationships in terms of pulse transit time (PTT) and pulse wave velocity (PWV). The times from peak systolic BP to diastolic trough (BPFt) and from the diastolic trough to peak systolic BP (BPRt) were also calculated. PTT, BPFt and BPRt were normalised for heart rate (HR) termed NPTT, NBPFt and NBPRt, respectively. ECG, invasive aortic BP monitoring and echocardiography were performed in 14 preterm infants < 29 weeks' gestation in the first 3 days after birth. The median (range) birth weight of the infants was 0.90 (0.48-1.31) kg, gestation 26.6 (24.0-28.7) weeks, PDA diameter 1.6 (0.8-3.6) mm and mean BP 32 (16-40) mmHg. We found a significant positive correlation between PDA diameter and NPTT (r = 0.69, P = 0.007) as well as NBPFt (r = 0.65, P = 0.012) and NBPRt (r = 0.71, P = 0.005). No relationship was found between PDA diameter and pulse pressure.Conclusions: Interrelationships between ECG and BP traces as well as BP waveform time analysis are straightforward to measure and associated with PDA diameter. The results of this pilot study suggest that this approach may help provide biomarkers for continuous monitoring PDA diameter and function. What is Known: • Patent ductus arteriosus (PDA) in premature infants is associated with increased risk of developing chronic lung disease, necrotising enterocolitis and cerebral injury. • Currently PDA is assessed intermittently using echocardiography which requires considerable expertise and sometimes is not well tolerated by critically ill preterm infants. What is New: • Blood pressure (BP) and ECG waveform interrelation and BP trace time analysis, taking account of heart rate, relate to PDA diameter. • ECG and BP waveform phase difference as well as BP waveform time analysis may be useful in the continuous assessment of PDA function.

Pulse Oximetry: The Working Principle, Signal Formation, and Applications

Pulse oximeters are routinely used in various medical-grade and consumer-grade applications. They can be used to estimate, for example, blood oxygen saturation, autonomic nervous system activity and cardiac function, blood pressure, sleep quality, and recovery through the recording of photoplethysmography signal. Medical-grade devices often record red and infra-red light-based photoplethysmography signals while smartwatches and other consumer-grade devices usually rely on a green light. At its simplest, a pulse oximeter can consist of one or two photodiodes and a photodetector attached, for example, a fingertip or earlobe. These sensors are used to record light absorption in a medium as a function of time. This time-varying absorption information is used to form a photoplethysmography signal. In this chapter, we discuss the working principles of pulse oximeters and the formation of the photoplethysmography signal. We will further discuss the advantages and disadvantages of pulse oximeters, which kind of applications exist in the medical field, and how pulse oximeters are utilized in daily health monitoring.

Instrumental Evaluation of COVID-19 Related Dysautonomia in Non-Critically-Ill Patients: An Observational, Cross-Sectional Study

Coronavirus disease-19 (COVID-19) is a predominantly respiratory syndrome. Growing reports about a SARS-CoV-2 neurological involvement, including autonomic dysfunction (AD), have been reported, mostly in critically-ill patients, or in the long-COVID syndrome. In this observational, cross-sectional study, we investigated the prevalence of AD in 20 non-critically-ill COVID-19 patients (COVID+ group) in the acute phase of the disease through a composite instrumental evaluation consisting of Sudoscan, automated pupillometry, heart rate variability (HRV), and pulse transit time (PTT). All the parameters were compared to a control group of 20 healthy volunteers (COVID− group). COVID+ group presented higher values of pupillary dilatation velocities, and baseline pupil diameter than COVID− subjects. Moreover, COVID+ patients presented a higher incidence of feet sudomotor dysfunction than COVID− group. No significant differences emerged in HRV and PTT parameters between groups. In this study we observed the occurrence of autonomic dysfunction in the early stage of the disease.

Pulse arrival time, a novel sleep cardiovascular marker: the multi-ethnic study of atherosclerosis

BACKGROUND

Pulse arrival time (PAT) is commonly used to estimate blood pressure response. We hypothesised that PAT response to obstructive respiratory events would be associated with increased cardiovascular risk in people with obstructive sleep apnoea.

METHODS

PAT, defined as the time interval between electrocardiography R wave and pulse arrival by photoplethysmography, was measured in the Multi-Ethnic Study of Atherosclerosis Sleep study participants. The PAT response to apnoeas/hypopnoeas was defined as the area under the PAT waveform following respiratory events. Cardiovascular outcomes included markers of subclinical cardiovascular disease (CVD): left ventricular mass, carotid plaque burden score and coronary artery calcification (CAC) (cross-sectional) and incident composite CVD events (prospective). Multivariable logistic and Cox proportional hazard regressions were performed.

RESULTS

A total of 1407 participants (mean age 68.4 years, female 47.5%) were included. Higher PAT response (per 1 SD increase) was associated with higher left ventricular mass (5.7 g/m2 higher in fourth vs first quartile, p<0.007), higher carotid plaque burden score (0.37 higher in fourth vs first quartile, p=0.02) and trended to greater odds of CAC (1.44, 95% CI 0.98 to 2.15, p=0.06). A total of 65 incident CVD events were observed over the mean of 4.1 (2.6) years follow-up period. Higher PAT response was associated with increased future CVD events (HR: 1.20, 95% CI 1.02 to 1.42, p=0.03).

CONCLUSION

PAT is independently associated with markers of subclinical CVD and incident CVD events. Respiratory-related PAT response is a novel and promising polysomnography metric with cardiovascular implications.

Classification of ischemic and dilated cardiomyopathy patients based on the analysis of the pulse transit time

Cardiomyopathies diseases affects a great number of the elderly population. An adequate identification of the etiology of a cardiomyopathy patient is still a challenge. The aim of this study was to classify patients by their etiology in function of indexes extracted from the characterization of the pulse transit time (PTT). This time series represents the time taken by the pulse pressure to propagate through the length of the arterial tree and corresponding to the time between R peak of ECG and the mid-point of the diastolic to systolic slope in the blood pressure signal. For each patient, the PTT time series was extracted. Thirty cardiomyopathy patients (CMP) classified as ischemic (ICM - 15 patients) and dilated (DCM - 15 patients) were analyzed. Forty-three healthy subjects (CON) were used as a reference. The PTT time series was characterized through statistical descriptive indices and the joint symbolic dynamics method. The best indices were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 89.6% accuracy, 78.5% sensitivity, and 100% specificity. When comparing CMP patients and CON subjects, the best model achieved 91.3% accuracy, 91.3% sensitivity, and 88.3% specificity. Our results suggests a significantly lower pulse transit time in ischemic patients.Clinical relevance- This study analyzed the suitability of the pulse transit time for the classification of ICM and DCM patients.

Bioinspired Multifunctional Photonic-Electronic Smart Skin for Ultrasensitive Health Monitoring, for Visual and Self-Powered Sensing

Smart skin is highly desired to be ultrasensitive and self-powered as the medium of artificial intelligence. Here, an ultrasensitive self-powered mechanoluminescence smart skin (SPMSS) inspired by the luminescence mechanism of cephalopod skin and the ultrasensitive response of spider-slit-organ is developed. Benefitting from the unique strain-dependent microcrack structure design based on Ti₃ C₂ T_x (MXene)/carbon nanotube synergistic interaction, SPMSS possesses excellent strain sensing performances including ultralow detection limit (0.001% strain), ultrahigh sensitivity (gauge factor, GF = 3.92 × 10⁷ ), ultrafast response time (5 ms), and superior durability and stability (>45 000 cycles). Synchronously, SPMSS exhibits tunable and highly sensitive mechanoluminescence (ML) features under stretching. A relationship between ML features, strain sensing performances, and the deformation has been established successfully. Importantly, the SPMSS demonstrates excellent properties as triboelectric nanogenerator (4 × 4 cm² ), including ultrahigh triboelectric output (open-circuit voltage V_OC  = 540 V, short-circuit current I_SC  = 42 µA, short-circuit charge Q_SC  = 317 nC) and power density (7.42 W m^-2 ), endowing the smart skin with reliable power source supply and self-powered sensing ability. This bioinspired smart skin exhibits multifunctional applications in health monitoring, visual sensing, and self-powered sensing, showing great potential in artificial intelligence.

Study of cuffless blood pressure estimation method based on multiple physiological parameters

Objective.Noninvasive blood pressure (BP) measurement technologies have been widely studied, but they still have the disadvantages of low accuracy, the requirement for frequent calibration and limited subjects. This work considers the regulation of vascular activity by the sympathetic nervous system and proposes a method for estimating BP using multiple physiological parameters.Approach.The parameters used in the model consist of heart rate variability (HRV), pulse transit time (PTT) and pulse wave morphology features extracted from electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Through four classic machine learning algorithms, a hybrid data set of 3337 subjects from two databases is evaluated to verify the ability of cross-database migration. We also recommend an individual calibration procedure to further improve the accuracy of the method.Main results.The mean absolute error (MAE) and the root mean square error (RMSE) of the proposed algorithm is 10.03 and 14.55 mmHg for systolic BP (SBP), and 5.42 and 8.19 mmHg for diastolic BP (DBP). With individual calibration, the MAE and standard deviation (SD) is -0.16 ± 7.96 (SBP) and -0.13 ± 4.50 (DBP) mmHg, which satisfied the Advancement of Medical Instrumentation (AAMI) standard. In addition, the models are used to test single databases to evaluate their performance on different data sources. The overall performance of the Adaboost algorithm is better on the Multi-parameter Intelligent Monitoring in Intensive Care Unit (MIMIC) database; the MAE between its predicted value and true value reaches 6.6mmHg (SBP) and 3.12mmHg (DBP), respectively.Significance.The proposed method considers the regulation of blood vessels and the heart by the autonomic nervous system, and verifies its effectiveness and robustness across data sources, which is promising for improving the accuracy of continuous and cuffless BP estimation.

Cortical thinning is associated with brain pulsatility in older adults: An MRI and NIRS study

Aging is accompanied by global brain atrophy occurring unequally across the brain. Cortical thinning is seen with aging with a larger loss in the frontal and temporal subregions. We explored the link between regional cortical thickness and regional cerebral pulsatility. Sixty healthy individuals were divided into two age groups, young (aged 19-31) and older (aged 65-75) adults. Each participant underwent a near-infrared spectroscopy (NIRS) scan to index regional brain pulsatility from cerebral pulse-transit-time-to-the peak-of-the-pulse (PTTp), an anatomical magnetic resonance imaging (MRI) and a phase-contrast MRI (PC-MRI) scan to measure arterial and cerebrospinal fluid (CSF) pulsatility. In older adults, the greatest association between cerebral pulsatility and cortical thickness was found in superior and middle temporal and superior, middle and inferior frontal areas, which are the regions perfused first by the internal carotid arteries. This association dropped in the postcentral and superior parietal regions. These findings suggest higher brain pulsatility as a potential risk factor contributing to cortical thinning for some brain regions more than others.

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives

According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encouraged people to check the blood pressure regularly because a large amount of patients do not have any symptoms. However, traditional cuff measurement results are not enough to represent the patient′s blood pressure status over a period of time. Therefore, there is an urgent need for portable, easy to operate, continuous measurement, and low-cost blood pressure measuring devices. In this paper, we adopted the convolutional neural network (CNN), based on the Hilbert–Huang Transform (HHT) method, to predict blood pressure (BP) risk level using photoplethysmography (PPG). Considering that the PPG′s first and second derivative signals are related to atherosclerosis and vascular elasticity, we created a dataset called PPG+; the images of PPG+ carry information on PPG and its derivatives. We built three classification experiments by collecting 582 data records (the length of each record is 10 s) from the Medical Information Mart for Intensive Care (MIMIC) database: NT (normotension) vs. HT (hypertension), NT vs. PHT (prehypertension), and (NT + PHT) vs. HT; the F1 scores of the PPG + experiments using AlexNet were 98.90%, 85.80%, and 93.54%, respectively. We found that, first, the dataset established by the HHT method performed well in the BP grade prediction experiment. Second, because the Hilbert spectra of the PPG are simple and periodic, AlexNet, which has only 8 layers, got better results. More layers instead increased the cost and difficulty of training.

Assessment of Pulmonary Arterial Hemodynamic and Vascular Changes by Pulmonary Pulse Transit Time in Patients with Human Immunodeficiency Virus Infection

INTRODUCTION

Pulmonary arterial hypertension and human immunodeficiency virus (HIV) infection is a well-known association. Pulmonary pulse transit time (pPTT) is a recent echocardiographic marker that might be used for evaluation of pulmonary arterial stiffness (PAS) in patients with HIV infection. We aimed to investigate whether pPTT elevated in patients with HIV infection compared to healthy controls and its association with echocardiographic indices of right ventricular functions.

MATERIALS AND METHODS

Fifty HIV (+) patients from infectious disease outpatient clinics and fifty age- and sex-matched HIV (-) healthy volunteers were enrolled in this study. pPTT was measured from pulmonary vein flow velocity as the time interval between the R-wave in the electrocardiography and corresponding peak late systolic was then calculated as the mean from two separate pw-Doppler measurements.

RESULTS

pPTT, tricuspid annular peak systolic excursion (TAPSE) and right ventricle fractional area change (FAC) were significantly lower in patients with HIV than control patients (177.1 ± 34.9 vs. 215.7 ± 35.7 msn, P < 0.001; 2.33 ± 0.28 vs. 2.19 ± 0.22, P = 0.039; 45 [4.25] vs. 41.1 [4.0], P = 0.032, respectively). pPTT was positively correlated with FAC, TAPSE and cluster of differentiation 4 count (r = 0.210; P = 0.036, r = 0.256; P = 0.041, r = 0.304; P = 0.044, respectively).

CONCLUSION

Our study showed that pPTT, TAPSE, and right ventricle FAC levels were lower in patients with HIV infection. pPTT is an important predictor in patients with HIV expected to develop pulmonary vascular pathology.

Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring

Out-of-office blood pressure measurement is an essential part of diagnosing and managing hypertension. In the era of advanced digital health information technology, the approach to achieving this is shifting from traditional methods (ambulatory and home blood pressure monitoring) to wearable devices and technology. Wearable blood pressure monitors allow frequent blood pressure measurements (ideally continuous beat-by-beat monitoring of blood pressure) with minimal stress on the patient. It is expected that wearable devices will dramatically change the quality of detection and management of hypertension by increasing the number of measurements in different situations, allowing accurate detection of phenotypes that have a negative impact on cardiovascular prognosis, such as masked hypertension and abnormal blood pressure variability. Frequent blood pressure measurements and the addition of new features such as monitoring of environmental conditions allows interpretation of blood pressure data in the context of daily stressors and different situations. This new digital approach to hypertension contributes to anticipation medicine, which refers to strategies designed to identify increasing risk and predict the onset of cardiovascular events based on a series of data collected over time, allowing proactive interventions to reduce risk. To achieve this, further research and validation is required to develop wearable blood pressure monitoring devices that provide the same accuracy as current approaches and can effectively contribute to personalized medicine.

Doppler parameters of renal hemodynamics in women with preeclampsia: A systematic review and meta-analysis

The present meta-analysis aims to compare renal arterial and venous Doppler parameters in women with preeclampsia and healthy pregnant controls. Medline, Scopus, Cochrane Central Register of Controlled Trials, Clinicaltrials.gov, and Google Scholar databases were systematically searched from inception to December 04, 2019. All observational studies reporting renal resistive index, pulsatility index, renal interlobar vein impedance, or pulse transit time among preeclamptic and healthy pregnant women were held eligible. Subgroup analysis was conducted on the basis of disease onset and side of measurement. Both pair-wise and network meta-analysis were performed using Review Manager 5.3 and R-3.4.3 software. Fourteen studies were included, with a total of 1118 women. No difference of renal resistive (MD: 0.00, 95% CI: [-0.03, 0.04]) and pulsatility index (MD: -0.01, 95% CI: [-0.14, 0.12]) was evident between the two groups. Renal interlobar vein impedance was estimated to be significantly higher in preeclampsia (MD: 0.07, 95% CI: [0.06, 0.09]), while venous pulse transit time was significantly lower (MD: -0.10, 95% CI: [-0.14, -0.05]) in women with the disease. Subgroup analysis indicated that early-onset preeclampsia was associated with significantly elevated renal interlobar vein impedance and lower venous pulse transit time than late-onset disease. The outcomes of the present meta-analysis suggest that preeclampsia is characterized by venous hemodynamic dysfunction as it is associated with significantly elevated renal interlobar vein impedance and shorter venous pulse transit time. Future large-scale prospective studies should introduce cutoff values and determine the optimal timing of measurement in order to achieve optimal predictive accuracy.

Wearable skin-like optoelectronic systems with suppression of motion artifacts for cuff-less continuous blood pressure monitor

According to the statistics of the World Health Organization, an estimated 17.9 million people die from cardiovascular diseases each year, representing 31% of all global deaths. Continuous non-invasive arterial pressure (CNAP) is essential for the management of cardiovascular diseases. However, it is difficult to achieve long-term CNAP monitoring with the daily use of current devices due to irritation of the skin as well as the lack of motion artifacts suppression. Here, we report a high-performance skin-like optoelectronic system integrated with ultra-thin flexible circuits to monitor CNAP. We introduce a theoretical model via the virtual work principle for predicting the precise blood pressure and suppressing motion artifacts, and propose optical difference in the frequency domain for stable optical measurements in terms of skin-like devices. We compare the results with the blood pressure acquired by invasive (intra-arterial) blood pressure monitoring for >1500 min in total on 44 subjects in an intensive care unit. The maximum absolute errors of diastolic and systolic blood pressure were ±7/±10 mm Hg, respectively, in immobilized, and ±10/±14 mm Hg, respectively, in walking scenarios. These strategies provide advanced blood pressure monitoring techniques, which would directly address an unmet clinical need or daily use for a highly vulnerable population.

Pulse transit time in pregnancy: a new way to diagnose and classify sleep disordered breathing?

STUDY OBJECTIVES

There are significant discrepancies between the prevalence of snoring and that of objectively defined sleep disordered breathing among pregnant women, suggesting subtle airflow limitations that may not be captured by conventional scoring. This study examined the performance of pulse transit time, an indirect measure of arterial stiffness and sympathetic activation, in pregnancy.

METHODS

Pregnant women with obesity and snoring and a group of controls without symptoms of sleep disordered breathing were recruited in the first trimester. Women underwent a level III in-laboratory sleep monitoring study including an electrocardiogram and pulse oximetry, and pulse transit time was measured. Sleep disordered breathing was defined as an apnea-hypopnea index at least five events per hour of sleep. Statistical analysis was performed using Spearman correlation, Fisher's exact t-test, and univariate analysis.

RESULTS

Of the 222 women, 38 met criteria for sleep disordered breathing. Pulse transit time drops were very prevalent (95% of participants with snoring had > 5 drops per hour). Median apnea-hypopnea index was 0.7 (interquartile range [IQR]: 2.6) events per hour whereas median pulse transit time drop index was 20.70 (IQR: 35.90) events per hour. Pulse transit time index was significantly higher in snorers with apnea-hypopnea index less than five events per hours and participants with apnea-hypopnea index greater than five events per hour compared to controls. Examination of random epochs with pulse transit time drops showed that 95% of pulse transit time drops were associated with airflow limitation.

CONCLUSIONS

Pulse transit time ascertains frequent events of sympathetic activation in at-risk women with and without sleep disordered breathing beyond conventional apneas and hypopneas. Pulse transit time may be an important addition to the identification of clinically significant sleep disordered breathing in pregnant women, and may identify more sleep disordered breathing than apnea-hypopnea index.

Wearable Devices for Precision Medicine and Health State Monitoring

Wearable technologies will play an important role in advancing precision medicine by enabling measurement of clinically-relevant parameters describing an individual's health state. The lifestyle and fitness markets have provided the driving force for the development of a broad range of wearable technologies that can be adapted for use in healthcare. Here we review existing technologies currently used for measurement of the four primary vital signs: temperature, heart rate, respiration rate, and blood pressure, along with physical activity, sweat, and emotion. We review the relevant physiology that defines the measurement needs and evaluate the different methods of signal transduction and measurement modalities for the use of wearables in healthcare.

Mathematical Modeling of Arterial Blood Pressure Using Photo- Plethysmography Signal in Breath-hold Maneuver

recent research has shown that each apnea episode results in a significant rise of the beat-to-beat blood pressure followed by a drop to the pre-episode levels when patient resumes normal breathing. While the physiological implications of these repetitive and significant oscillations are still unknown, it is of interest to quantify them. Since current array of instruments deployed for polysomnography studies does not include beat-to-beat measurement of blood pressure, but includes oximetry which can supply pulsatile photoplethysmography (PPG) signal, in addition to percent oxygen saturation. Hence, we have investigated a new method for continuous estimation of systolic (SBP), diastolic (DBP), and mean (MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are used as input to a 5th order autoregressive moving average model to construct estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown to faithfully simulate apnea episodes, we evaluated the performance of the proposed method in 7 subjects (4 F; $32 \pm 4$ yrs., BMI $24.57 \pm 3.87$ kg/m2) in supine position doing 5 breath holding maneuvers with 90s of normal breathing between them. The modeling error ranges were (all units are in mmHg $) 0.88 \pm 4.87$ to $- 2.19 \pm 5.73($ SBP); $0.29 \pm 2.39$ to $- 0.97 \pm 3.83($ DBP); and $- 0.42 \pm 2.64$ to $- 1.17 \pm 3.82($ MBP). The cross validation error ranges were $0.28 \pm 6.45$ to $- 1.74 \pm 6.55($ SBP); $0.09 \pm 3.37$ to $0.97 \pm 3.67($ DBP); and $0.33 \pm 4.34$ to $- 0.87 \pm 4.42($ MBP). The overall level of estimation error, as measured by the root mean squared of the model residuals, was less than 7 mmHg.

Sex-Related Differences in Photoplethysmography Signals Measured From Finger and Toe

Sex plays an important role in the normal cardiovascular system function including resting heart rate and arterial blood pressure. In addition, it has been reported that men and women are at different levels of risk for cardiovascular diseases. The aim of this study was to evaluate and compare the temporal and morphological features of both finger and toe photoplethysmography (PPG), and anthropometric and biological parameters with respect to sex. A customized PPG and electrocardiography (ECG) combo device was developed to measure the signals of interest. ECG/PPG features in addition to subjects’ information were compared regarding finger and toe PPGs. Eighty-eight subjects participated in the study. Linear regression and Student’s t-test were used for statistical analysis. Our results revealed that pulse arrival time (PAT), pulse transit time (PTT), systolic pulse transit time (SPTT), and the ratio of areas under the PPG waveform from the onset to the inflection point and the inflection point to the end of the waveform (S2/S1), are dependent on sex. The highest dependence was shown for the finger PTT while the toe PTT did not indicate any significant dependence on sex. This is the first study that evaluates the effect of sex on cardiovascular system function using finger and toe PPG based features which can help to understand sex-based risk factors for cardiovascular diseases and to improve related disease management and treatments.

Advanced polysomnographic analysis for OSA: A pathway to personalized management?

Obstructive sleep apnea (OSA) is a highly heterogeneous disorder, with diverse pathways to disease, expression of disease, susceptibility to co-morbidities and response to therapy, and is ideally suited to precision medicine approaches. Clinically, the content of the information-rich polysomnogram (PSG) is not currently fully utilized in determining patient management. Novel PSG parameters such as hypoxic burden, pulse transit time, cardiopulmonary coupling and the frequency representations of PSG sensor signals could predict a variety of cardiovascular disease, cancer and neurodegeneration co-morbidities. The PSG can also be used to identify key pathophysiological parameters such as loop gain, arousal threshold and muscle compensation which can enhance understanding of the causes of OSA in an individual, and thereby guide choices on therapy. Machine learning methods performing their own parameter extraction coupled with large PSG data sets offer an exciting opportunity for discovering new links between the PSG variables and disease outcomes. By exploiting existing and emerging analytical methods, the PSG may offer a pathway to personalized management for OSA.

Pulse transit time technique for cuffless unobtrusive blood pressure measurement: from theory to algorithm

Cuffless technique holds great promise to measure blood pressure (BP) in an unobtrusive way, improving diagnostics and monitoring of hypertension and its related cardiovascular diseases, and maximizing the independence and participation of individual. Pulse transit time (PTT) has been the most commonly employed techniques for cuffless BP estimation. Many studies have been conducted to explore its feasibility and validate its performance in the clinical settings. However, there is still issues and challenges ahead before its wide application. This review will investigate the understanding and development of the PTT technique in depth, with a focus on the physiological regulation of arterial BP, the relationship between PTT and BP, and the summaries of the PTT-based models for BP estimation.

Continuous non-invasive determination of nocturnal blood pressure variation using photoplethysmographic pulse wave signals: comparison of pulse propagation time, pulse transit time and RR-interval

OBJECTIVE

Cardiovascular diseases are the leading cause of death, whereas nocturnal ambulatory blood pressure (BP) is the most potent predictor for cardiovascular risk. The volume clamp and pulse transit time (PTT) are common methods for continuous non-invasive BP measurement, but have drawbacks during unsupervised ambulatory use and undisturbed sleep. The pulse propagation time (PPT), defined as the time between pulse wave systolic peak and diastolic peak, provides valid information about the pressure pulse waveform. However, the use of PPT for nocturnal BP variation determination and whether such variation is affected by BP or heart rate (i.e. RR-interval or RRI) has not been investigated.

APPROACH

To assess whether the PPT method is suitable for ubiquitous nocturnal BP monitoring, we compared systolic blood pressure (SBP) estimates derived from PPT, PTT, and RRI signals with parallel recorded BP measurements. The RRI-derived SBP signals were used as a baseline for testing a potential heart rate dependency. This work provides an overview of BP measurements, presents the developed real-time signal analysis, and describes the performance assessment. The signal analysis was validated with data records from 42 subjects acquired from an ergometry and sleep laboratory in equal parts.

MAIN RESULTS

The algorithms applied to the ergometry laboratory database achieved a correlation coefficient between reference SBP and estimated SBP_PPT of 0.89 (p  <  0.001) with bias 0.1 mmHg and limits of agreement (LoA)  -29.8 to 30.0 mmHg, SBP_PTT of 0.97 (p  <  0.001) with bias 0.0 mmHg and LoA  -15.2 to 15.3 mmHg, and SBP_RRI of 0.96 (p  <  0.001) with bias 0.0 mmHg and LoA  -19.5 to 19.5 mmHg. For the sleep laboratory database, the correlation coefficient was 0.95 (p  <  0.001) with bias 0.2 mmHg and LoA  -18.3 to 18.8 mmHg for SBP_PPT, 0.88 (p  <  0.001) with bias 0.0 mmHg and LoA  -25.0 to 24.9 mmHg for SBP_PTT, and 0.88 (p  <  0.001) with bias of 0.1 mmHg and LoA  -23.6 to 23.7 mmHg for SBP_RRI. A heart rate dependency of PPT or PTT could not be found. The analysis of variance shows no significant differences between the reference SBP values and the estimated values for either the ergometry (F(3, 627)  =  2.27, p  =  0.08) or the sleep laboratory (F(3, 327)  =  2.28, p  =  0.08).

SIGNIFICANCE

In conclusion, the PPT method seems to be an interesting alternative for continuous determination of SBP during simplified cardiovascular monitoring and sleep screening compared to more expensive devices based on volume clamp or PTT methods.

Photoplethysmography for Quantitative Assessment of Sympathetic Nerve Activity (SNA) During Cold Stress

The differences in the degree of sympathetic nerve activity (SNA) over cutaneous blood vessels, although known to be more prominent in the periphery than the core vasculature, has not been thoroughly investigated quantitatively. Hence, two studies were carried out to investigate the differences in SNA between the periphery and the core during the cold pressor test (CPT) (right-hand immersion in ice water) and cold exposure (whole body exposed to cold air) using photoplethysmography (PPG). Two methods utilizing PPG, namely differential multi-site PTT measurements and low-frequency spectral analysis were explored for quantitative determination of SNA. Each study involved 12 healthy volunteers, and PPG signals were acquired from the right index finger (RIF), left index finger (LIF) (periphery) and the ear canal (core). During CPT, Pulse Transit Time (PTT) was measured to the respective locations and the mean percentage change in PTT during ice immersion at each location was used as an indicator for the extent of SNA. During cold exposure, the low-frequency spectral analysis was performed on the acquired raw PPGs to extract the power of the sympathetic [low-frequency (LF): 0.04–0.15 Hz] and parasympathetic components [high-frequency (HF): 0.15–0.4 Hz]. The ratio of LF/HF components was then used to quantify the differences in the influence of SNA on the peripheral and core circulation. PTT measured from the EC, and the LIF has dropped by 5 and 7%, respectively during ice immersion. The RIF PTT, on the other hand, has dropped significantly (P < 0.05) by 12%. During the cold exposure, the LF/HF power ratio at the finger has increased to 86.4 during the cold exposure from 19.2 at the baseline (statistically significant P = 0.002). While the ear canal LF/HF ratio has decreased to 1.38 during the cold exposure from 1.62 at baseline (P = 0.781). From these observations, it is evident that differential PTT measurements or low-frequency analysis can be used to quantify SNA. The results also demonstrate the effectiveness of the central auto-regulation during both short and long-term stress stimulus as compared to the periphery.

A Low-Power Photoplethysmogram-Based Heart Rate Sensor Using Heartbeat Locked Loop

In this paper, we present an ultralow power heart rate (HR) monitoring photoplethysmography (PPG) sensor using a heartbeat locked loop (HBLL). The HBLL generates a narrow window that turns on the LED and analog-front-end only when a peak is expected in the PPG signal. The prototype PPG sensor implemented in 0.18  μm CMOS has an effective duty-cycle of 0.01% and consumes only 43.4  μW at a HR of 60 b/m, which is the lowest power consumption compared with previous state-of-the-art PPG sensors. The HR error of the proposed sensor is less than 2.1 b/m for HR below 180 b/m.

Detecting Cardiac Activity by Capacitive Electrodes from a Single Point on the Wrist

Ballistocardiography (BCG) is the measurement of body movement by forces associated with heart contraction that can be used for monitoring cardiac activity. It has already been measured by force sensor and accelerometer. In this research, we developed a capacitive wristband that provides a method for single point, continuous BCG measurement, which has the potential to become a new type of sensor for wearable health care. The aim of this paper is to validate that the signal detected by capacitive electrodes is actually the BCG signal. Signals from four healthy subjects were acquired by a capacitive wristband together with Electrocardiogram (ECG). The capacitive signal was validated by both morphology matching analysis and wave occurrence time matching analysis to show that it is indeed BCG signal. JJ intervals extracted from BCG were shown to have potential to be surrogate of ECG RR series in heart rate variability analysis.

Arterial blood pressure feature estimation using photoplethysmography

Continuous and noninvasive monitoring of blood pressure has numerous clinical and fitness applications. Current methods of continuous measurement of blood pressure are either invasive and/or require expensive equipment. Therefore, we investigated a new method for the continuous estimation of two main features of blood pressure waveform: systolic and diastolic pressures. The estimates were obtained from a photoplethysmography signal as input to the fifth order autoregressive moving average models. The performance of the method was evaluated using beat-to-beat full-wave blood pressure measurements from 15 young subjects, with no known cardiovascular disorder, in supine position as they breathed normally and also while they performed a breath-hold maneuver. The level of error in the modeling and prediction estimates during normal breathing and breath-hold maneuvers, as measured by the root mean square of the residuals, were less than 5 mmHg and 11 mm Hg, respectively. The mean of model residuals both during normal breathing and breath-hold maneuvers was considered to be less than 3.2 mmHg. The dependency of the accuracy of the estimates on the subject data was assessed by comparing the modeling errors for the 15 subjects. Less than 1% of the models showed significant differences (p < 0.05) from the other models, which indicates a high level of consistency among the models.