Arterial stiffness indices in healthy volunteers using non-invasive digital photoplethysmography

Relationship of Non-Invasive Arterial Stiffness Parameters with 10-Year Atherosclerotic Cardiovascular Disease Risk Score in Post-COVID-19 Patients-The Results of a Cross-Sectional Study

This study evaluated the relationship of non-invasive arterial stiffness parameters with an individual 10-year risk of fatal and non-fatal atherosclerotic cardiovascular disease (ASCVD) events in the cohort post-coronavirus disease 2019 (COVID-19). The study group included 203 convalescents aged 60.0 (55.0-63.0) and 115 (56.7%) women. The ASCVD risk was assessed as low to moderate to very high based on medical history (for 62 participants with pre-existing ASCVD/diabetes/chronic kidney disease in the entire cohort) or calculated in percentages using the Systemic Coronary Risk Evaluation 2 (SCORE2) algorithm based on age, sex, smoking status, systolic blood pressure (BP), and non-high-density lipoprotein cholesterol (for 141 healthy participants). The stiffness index (SI) and reflection index (RI) measured by photoplethysmography, as well as pulse pressure (PP), calculated as the difference between systolic and diastolic BP, were markers of arterial stiffness. Stiffness parameters increased significantly with the increase in ASCVD risk in the entire cohort. In 30 (14.8%) patients in the low- to moderate-risk group, the median SI was 8.07 m/s (7.10-8.73), RI 51.40% (39.40-65.60), and PP 45.50 mmHg (40.00-57.00); in 111 (54.7%) patients in the high-risk group, the median SI was 8.70 m/s (7.40-10.03), RI 57.20% (43.65-68.40), and PP 54.00 mmHg (46.00-60.75); and in 62 (30.5%) patients in the very-high-risk group, the median was SI 9.27 m/s (7.57-10.44), RI 59.00% (50.40-72.40), and PP 60.00 mmHg (51.00-67.00). In healthy participants, the SI ≤ 9.0 m/s (sensitivity of 92.31%, area under the curve [AUC] 0.686, p < 0.001) based on the receiver operating characteristics was the most sensitive variable for discriminating low to moderate risk, and PP > 56.0 mmHg (sensitivity of 74.36%, AUC 0.736, p < 0.001) was used for discriminating very high risk. In multivariate logistic regression, younger age, female sex, PP ≤ 50 mmHg, SI ≤ 9.0 m/s, and triglycerides < 150 mg/dL had the best relationship with low to moderate SCORE2 risk. In turn, older age, currently smoking, PP > 56.0 mmHg, RI > 68.6%, and diastolic BP ≥ 90 mmHg were related to very high SCORE2 risk. In conclusion, arterial stiffness is significantly related to ASCVD risk in post-COVID-19 patients and can be helpful as a single risk marker in everyday practice. Cut-off points for arterial stiffness parameters determined based on SCORE2 may help make individual decisions about implementing lifestyle changes or pharmacological treatment of ASCVD risk factors.

Signal completion using generative adversarial networks for enhanced photoplethysmography measurement accuracy

Despite the growing adoption of wearable photoplethysmography (PPG) devices in personal health management, their measurement accuracy remains limited due to susceptibility to noise. This paper proposes a novel signal completion technique using generative adversarial networks that ensures both global and local consistency. Our approach innovatively addresses both short- and long-term PPG variations to restore waveforms while maintaining waveform consistency within and between pulses. We evaluated our model by removing up to 50 % of segments from segmented PPG waveforms and comparing the original and reconstructed waveforms, including systolic peak information. The results demonstrate that our method accurately reconstructs waveforms with high fidelity, producing natural and seamless transitions without discontinuities at reconstructed boundaries. Additionally, the reconstructed waveforms preserve typical PPG shapes with minimal distortion, underscoring the effectiveness and novelty of our technique.

Do Photopletysmographic Parameters of Arterial Stiffness Differ Depending on the Presence of Arterial Hypertension and/or Atherosclerosis?

BACKGROUND

Hypertension and atherosclerotic cardiovascular diseases (ASCVD) increase cardiovascular risk and worsen patients' prognoses. One early predictor of increased risk is a change in arterial stiffness. This study aimed to evaluate arterial stiffness parameters using the non-invasive photoplethysmography (PPG) method in Polish patients with arterial hypertension (AH) and/or atherosclerosis (AS).

METHODS

The study group consisted of 333 patients (Caucasians, both sexes, aged 30-85 years old). Patients were analyzed in four groups depending on AH and AS (Group I: patients without AH or AS, Group II: AH patients, Group III: AS patients, and Group IV: AH/AS patients) and, in addition, according to sex and history of SARS-CoV-2 infection. Arterial stiffness parameters, i.e., reflection index (RI), peak-to-peak time (PPT), and stiffness index (SI) were automatically calculated with PPG based on the analysis of the pulse wave contour.

RESULTS

Mean values of RI and SI were higher in men than women (p < 0.001 each). Diastolic blood pressure (DBP) also differed between sexes (p = 0.010). Mean SI values differed between the study groups (p = 0.038) with the highest SI found in AS/AH patients and the lowest-in patients without AH or AS. The mean SI values were significantly lower in women compared to men in both Group I and Group II (p = 0.006 and p < 0.001, respectively). The mean values of RI were also greater in men than in women in Group I and Group II (p < 0.001 for each group). Regarding COVID-19 history, only HR values differed between patients with and without COVID-19 in AH patients (p = 0.012). In AH patients, men had higher values of RI and SI compared to women (p < 0.001 and p < 0.001). On the other hand, AS women with COVID-19 had significantly greater mean values of SI (9.66 m/s ± 1.61) than men with COVID-19 (7.98 m/s ± 1.09) (p = 0.045).

CONCLUSIONS

The present study confirmed that sex had a significant impact on arterial stiffness parameters. Both AH and AS affected arterial stiffness. Heart rate was greater in hypertensive patients after COVID-19 compared to hypertensive patients without COVID-19.

Impact of Microbubble Degradation and Flow Velocity on Subharmonic-aided Pressure Estimation (SHAPE): An Experimental Investigation

OBJECTIVE

This study aimed to investigate the impact of microbubble degradation and flow velocity on Sub-Harmonic Aided Pressure Estimation (SHAPE), and to explore the correlation between subharmonic amplitude and pressure as a single factor.

METHODS

We develop an open-loop vascular phantom platform system and utilize a commercial ultrasound machine and microbubbles for subharmonic imaging. Subharmonic amplitude was measured continuously at constant pressure and flow velocity to assess the impact of microbubble degradation. Flow velocity was varied within a range of 4-14 cm/s at constant pressure to investigate its relationship to subharmonic amplitude. Furthermore, pressure was varied within a range of 10-110 mm Hg at constant flow velocity to assess its isolated effect on subharmonic amplitude.

RESULTS

Under constant pressure and flow velocity, subharmonic amplitude exhibited a continuous decrease at an average rate of 0.221 dB/min, signifying ongoing microbubble degradation during the experimental procedures. Subharmonic amplitude demonstrated a positive correlation with flow velocity, with a variation ratio of 0.423 dB/(cm/s). Under controlled conditions of microbubble degradation and flow velocity, a strong negative linear correlation was observed between pressure and subharmonic amplitude across different Mechanical Index (MI) settings (all R2 > 0.90). The sensitivity of SHAPE was determined to be 0.025 dB/mmHg at an MI of 0.04.

CONCLUSION

The assessment of SHAPE sensitivity is affected by microbubble degradation and flow velocity. Excluding the aforementioned influencing factors, a strong linear negative correlation between pressure and subharmonic amplitude was still evident, albeit with a sensitivity coefficient lower than previously reported values.

Preserving shape details of pulse signals for video-based blood pressure estimation

In recent years, imaging photoplethysmograph (iPPG) pulse signals have been widely used in the research of non-contact blood pressure (BP) estimation, in which BP estimation based on pulse features is the main research direction. Pulse features are directly related to the shape of pulse signals while iPPG pulse signals are easily disturbed during the extraction process. To mitigate the impact of pulse feature distortion on BP estimation, it is necessary to eliminate interference while retaining valuable shape details in the iPPG pulse signal. Contact photoplethysmograph (cPPG) pulse signals measured at rest can be considered as the undisturbed reference signal. Transforming the iPPG pulse signal to the corresponding cPPG pulse signal is a method to ensure the effectiveness of shape details. However, achieving the required shape accuracy through direct transformation from iPPG to the corresponding cPPG pulse signals is challenging. We propose a method to mitigate this challenge by replacing the reference signal with an average cardiac cycle (ACC) signal, which can approximately represent the shape information of all cardiac cycles in a short time. A neural network using multi-scale convolution and self-attention mechanisms is developed for this transformation. Our method demonstrates a significant improvement in the maximal information coefficient (MIC) between pulse features and BP values, indicating a stronger correlation. Moreover, pulse signals transformed by our method exhibit enhanced performance in BP estimation using different model types. Experiments are conducted on a real-world database with 491 subjects in the hospital, averaging 60 years of age.

Photoplethysmography for the Assessment of Arterial Stiffness

This review outlines the latest methods and innovations for assessing arterial stiffness, along with their respective advantages and disadvantages. Furthermore, we present compelling evidence indicating a recent growth in research focused on assessing arterial stiffness using photoplethysmography (PPG) and propose PPG as a potential tool for assessing vascular ageing in the future. Blood vessels deteriorate with age, losing elasticity and forming deposits. This raises the likelihood of developing cardiovascular disease (CVD), widely reported as the global leading cause of death. The ageing process induces structural modifications in the vascular system, such as increased arterial stiffness, which can cause various volumetric, mechanical, and haemodynamic alterations. Numerous techniques have been investigated to assess arterial stiffness, some of which are currently used in commercial medical devices and some, such as PPG, of which still remain in the research space.

Machine learning approaches for cardiovascular hypertension stage estimation using photoplethysmography and clinical features

Cardiovascular diseases (CVDs) are a leading cause of death worldwide, with hypertension emerging as a significant risk factor. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. This work proposes a novel approach employing features extracted from the acceleration photoplethysmography (APG) waveform, alongside clinical parameters, to estimate different stages of hypertension. The current study used a publicly available dataset and a novel feature extraction algorithm to extract APG waveform features. Three distinct supervised machine learning algorithms were employed in the classification task, namely: Decision Tree (DT), Linear Discriminant Analysis (LDA), and Linear Support Vector Machine (LSVM). Results indicate that the DT model achieved exceptional training accuracy of 100% during cross-validation and maintained a high accuracy of 96.87% on the test dataset. The LDA model demonstrated competitive performance, yielding 85.02% accuracy during cross-validation and 84.37% on the test dataset. Meanwhile, the LSVM model exhibited robust accuracy, achieving 88.77% during cross-validation and 93.75% on the test dataset. These findings underscore the potential of APG analysis as a valuable tool for clinicians in estimating hypertension stages, supporting the need for early detection and intervention. This investigation not only advances hypertension risk assessment but also advocates for enhanced cardiovascular healthcare outcomes.

Reduction in Arterial Stiffness Index (SI) in Response to Combination Antioxidant Therapy

Antioxidants reduce arterial stiffness, but the effects previously reported are weak. A systematic review of the antioxidants vitamin E, vitamin C, vitamin A, and beta-carotenes (the most commonly studied antioxidants) on pulse wave velocity (PWV) found an effect size of only -0.20 (approximately -16 m/s or -2.5%). Studies in rats of the potent pro-oxidant substance acetaldehyde have shown that combinations of sulfur-containing antioxidants, including thiamine and l-cysteine, with ascorbic acid potently protect against oxidative-stress-mediated mortality. The effects of these combinations of oxidants on PWV have not been studied. The present study evaluated the effects of 2 weeks of therapy with a combination of sulfur-containing antioxidants (cysteine, thiamine, and pyridoxine) in combination with ascorbic acid on stiffness index (SI), a measure of arterial stiffness that is strongly correlated with PWV, using a Pulse Trace recorder in a diverse group of 78 volunteers. SI fell by -1.7 m/s relative to placebo (95% confidence intervals -0.6 to -2.7 m/s), a reduction of -19% (95% confidence intervals -9% to -31%). The Glass effect size was 1.4, indicating a very strong treatment effect which was substantially greater than the effect size found in previous studies of antioxidants. PWV reduction was correlated significantly with increasing age. Further studies of similar antioxidant combinations are required to determine whether they are of value in the treatment or prevention of cardiovascular disease.

Clustered photoplethysmogram pulse wave shapes and their associations with clinical data

Photopletysmography (PPG) is a non-invasive and well known technology that enables the recording of the digital volume pulse (DVP). Although PPG is largely employed in research, several aspects remain unknown. One of these is represented by the lack of information about how many waveform classes best express the variability in shape. In the literature, it is common to classify DVPs into four classes based on the dicrotic notch position. However, when working with real data, labelling waveforms with one of these four classes is no longer straightforward and may be challenging. The correct identification of the DVP shape could enhance the precision and the reliability of the extracted bio markers. In this work we proposed unsupervised machine learning and deep learning approaches to overcome the data labelling limitations. Concretely we performed a K-medoids based clustering that takes as input 1) DVP handcrafted features, 2) similarity matrix computed with the Derivative Dynamic Time Warping and 3) DVP features extracted from a CNN AutoEncoder. All the cited methods have been tested first by imposing four medoids representative of the Dawber classes, and after by automatically searching four clusters. We then searched the optimal number of clusters for each method using silhouette score, the prediction strength and inertia. To validate the proposed approaches we analyse the dissimilarities in the clinical data related to obtained clusters.

The Dicrotic Notch: Mechanisms, Characteristics, and Clinical Correlations

PURPOSE OF REVIEW

The dicrotic notch (DN) has long been considered a marker of arterial stiffness and compliance. Herein, we explored the recent developments in vascular medicine research in an attempt to assess the DN utility in clinical cardiovascular medicine.

RECENT FINDINGS

Since its discovery, several studies have attempted to measure the changes in different parameters of the DN in physiological and pathological states. Despite the significance of their findings, the clinical role of the DN remained limited. This may have been related to the difficulty of measuring the DN via indwelling arterial catheters in the past. However, over the past two decades, several non-invasive methods have been developed, which may re-ignite interest in DN research. The DN may have broader applications in clinical cardiovascular medicine. Further research is needed to establish the accuracy of DN non-invasive measurement methods and compare its prognostic value to other circulatory parameters.

Stretchable Photodiodes with Polymer-Engineered Semiconductor Nanowires for Wearable Photoplethysmography

Healthcare systems worldwide have been stressed to provide sufficient resources to serve the increasing and aging population in our society. The situation became more challenging at the time of pandemic. Technology advancement, especially the adoption of wearable health monitoring devices, has provided an important supplement to current clinical equipment. Most health monitoring devices are rigid, however, human tissues are soft. Such a difference has prohibited intimate contact between the two and jeopardized wearing comfortableness, which hurdles measurement accuracy especially during longtime usage. Here, we report a soft and stretchable photodiode that can conformally adhere onto the human body without any pressure and measure cardiovascular variables for an extended period with higher reliability than commercial devices. The photodiode used a composite light absorber consisting of an organic bulk heterojunction embedded into an elastic polymer matrix. It is discovered that the elastic polymer matrix not only improves the morphology of the bulk heterojunction for obtaining the desired mechanical properties but also alters its electronic band structure and improves the electrical properties that lead to a reduced dark current and enhanced photovoltage in the stretchable photodiode. The work has demonstrated high fidelity measurements and longtime monitoring of heat rate variability and oxygen saturation, potentially enabling next-generation wearable photoplethysmography devices for point-of-care diagnosis of cardiovascular diseases in a more accessible and affordable way.

PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points

Photoplethysmography is a non-invasive technique used for measuring several vital signs and for the identification of individuals with an increased disease risk. Its principle of work is based on detecting changes in blood volume in the microvasculature of the skin through the absorption of light. The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task, where various feature extraction methods have been proposed in the literature. In this work, we present PPGFeat, a novel MATLAB toolbox supporting the analysis of raw photoplethysmography waveform data. PPGFeat allows for the application of various preprocessing techniques, such as filtering, smoothing, and removal of baseline drift; the calculation of photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting photoplethysmography fiducial points. PPGFeat includes a graphical user interface allowing users to perform various operations on photoplethysmography signals and to identify, and if required also adjust, the fiducial points. Evaluating the PPGFeat's performance in identifying the fiducial points present in the publicly available PPG-BP dataset, resulted in an overall accuracy of 99% and 3038/3066 fiducial points were correctly identified. PPGFeat significantly reduces the risk of errors in identifying inaccurate fiducial points. Thereby, it is providing a valuable new resource for researchers for the analysis of photoplethysmography signals.

Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation

The bold vision of AI-driven pervasive physiological monitoring, through the proliferation of off-the-shelf wearables that began a decade ago, has created immense opportunities to extract actionable information for precision medicine. These AI algorithms model input-output relationships of a system that, in many cases, exhibits complex nature and personalization requirements. A particular example is cuffless blood pressure estimation using wearable bioimpedance. However, these algorithms need training over significant amount of ground truth data. In the context of biomedical applications, collecting ground truth data, particularly at the personalized level is challenging, burdensome, and in some cases infeasible. Our objective is to establish physics-informed neural network (PINN) models for physiological time series data that would use minimal ground truth information to extract complex cardiovascular information. We achieve this by building Taylor's approximation for gradually changing known cardiovascular relationships between input and output (e.g., sensor measurements to blood pressure) and incorporating this approximation into our proposed neural network training. The effectiveness of the framework is demonstrated through a case study: continuous cuffless BP estimation from time series bioimpedance data. We show that by using PINNs over the state-of-the-art time series models tested on the same datasets, we retain high correlations (systolic: 0.90, diastolic: 0.89) and low error (systolic: 1.3 ± 7.6 mmHg, diastolic: 0.6 ± 6.4 mmHg) while reducing the amount of ground truth training data on average by a factor of 15. This could be helpful in developing future AI algorithms to help interpret pervasive physiologic data using minimal amount of training data.

Photoplethysmographic Measurement of Arterial Stiffness in Polish Patients with Long-COVID-19 Syndrome-The Results of a Cross-Sectional Study

The coronavirus disease 2019 (COVID-19) is associated with an increase in the incidence of cardiovascular diseases (CVD) that persists even several months after the onset of infection. COVID-19 may also have an impact on arterial stiffness, which is a risk factor for CVD. We aimed to analyze if and to what extent arterial stiffness measured by photoplethysmography differed among COVID-19 convalescents depending on the acute phase severity and time elapsed since disease onset. A total of 225 patients (mean age 58.98 ± 8.57 years, 54.7% women) were analyzed after COVID-19 hospitalization at the Cardiac Rehabilitation Department of the Ustron Health Resort (Poland). In the entire study population, no differences were found in the mean values of stiffness index (SI) and reflection index (RI) depending on the severity of the acute COVID-19 and the time since the onset of the disease. There were no differences in the heart rate (HR) according to the severity of acute COVID-19; the mean HR was higher in patients who had COVID-19 less than 12 weeks before the study than in convalescents more than 24 weeks after the acute disease (p = 0.002). The mean values of SI and RI were higher in men than in women (p < 0.001), while the heart rate (HR) was similar in both sexes (p = 0.286). However, multiple linear regression analyses after adjusting for factors influencing arterial stiffness, i.e., sex, age, body mass index, smoking status, hypertension, diabetes, the severity of the acute COVID-19, and the time from the disease onset, confirmed that age, sex, time from disease onset, and diabetes are the most important determinants that could influence arterial stiffness.

Applicability of the single-layer flat-coil-oscillator technology-based vibration and vibro-acoustic sensors in medical and biological study of the cardiovascular system: Advantages and perspectives of the carotid pulse wave registration

The possibility and feasibility of using the single-layer flat-coil-oscillator (SFCO) technology-based vibration and vibro-acoustic sensors in diagnostic devices and biomedical studies of the cardiovascular system are discussed in this paper. Using an example of recording pulse waves of left carotid artery and their analysis, the information content of the data recorded by these sensors in a number of cases is shown-assessment of age-related changes in the stiffness of the vascular wall, assessment of the dynamics of systolic volume, reflecting myocardial contractility, and rhythm disturbance (extra-systole and arrhythmia). These sensors are shown to be promising in recording heart sounds due to their high sensitivity. The possibility of assessing the dynamics of relaxation of the cardiovascular system after exercise (stress test) is shown. The advantages of using SFCO vibration and vibro-acoustic sensors are high sensitivity, ease of use, and no need to train specialists. These advantages open new perspectives for their implementation in mobile wearable "smart" devices for individual monitoring.

Assessing hemodynamics from the photoplethysmogram to gain insights into vascular age: a review from VascAgeNet

The photoplethysmogram (PPG) signal is widely measured by clinical and consumer devices, and it is emerging as a potential tool for assessing vascular age. The shape and timing of the PPG pulse wave are both influenced by normal vascular aging, changes in arterial stiffness and blood pressure, and atherosclerosis. This review summarizes research into assessing vascular age from the PPG. Three categories of approaches are described: 1) those which use a single PPG signal (based on pulse wave analysis), 2) those which use multiple PPG signals (such as pulse transit time measurement), and 3) those which use PPG and other signals (such as pulse arrival time measurement). Evidence is then presented on the performance, repeatability and reproducibility, and clinical utility of PPG-derived parameters of vascular age. Finally, the review outlines key directions for future research to realize the full potential of photoplethysmography for assessing vascular age.

Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review

Recent research indicates that Photoplethysmography (PPG) signals carry more information than oxygen saturation level (SpO2) and can be utilized for affordable, fast, and noninvasive healthcare applications. All these encourage the researchers to estimate its feasibility as an alternative to many expansive, time-wasting, and invasive methods. This systematic review discusses the current literature on diagnostic features of PPG signal and their applications that might present a potential venue to be adapted into many health and fitness aspects of human life. The research methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 2020. To this aim, papers from 1981 to date are reviewed and categorized in terms of the healthcare application domain. Along with consolidated research areas, recent topics that are growing in popularity are also discovered. We also highlight the potential impact of using PPG signals on an individual's quality of life and public health. The state-of-the-art studies suggest that in the years to come PPG wearables will become pervasive in many fields of medical practices, and the main domains include cardiology, respiratory, neurology, and fitness. Main operation challenges, including performance and robustness obstacles, are identified.

Photoplethysmogram Analysis and Applications: An Integrative Review

Beyond its use in a clinical environment, photoplethysmogram (PPG) is increasingly used for measuring the physiological state of an individual in daily life. This review aims to examine existing research on photoplethysmogram concerning its generation mechanisms, measurement principles, clinical applications, noise definition, pre-processing techniques, feature detection techniques, and post-processing techniques for photoplethysmogram processing, especially from an engineering point of view. We performed an extensive search with the PubMed, Google Scholar, Institute of Electrical and Electronics Engineers (IEEE), ScienceDirect, and Web of Science databases. Exclusion conditions did not include the year of publication, but articles not published in English were excluded. Based on 118 articles, we identified four main topics of enabling PPG: (A) PPG waveform, (B) PPG features and clinical applications including basic features based on the original PPG waveform, combined features of PPG, and derivative features of PPG, (C) PPG noise including motion artifact baseline wandering and hypoperfusion, and (D) PPG signal processing including PPG preprocessing, PPG peak detection, and signal quality index. The application field of photoplethysmogram has been extending from the clinical to the mobile environment. Although there is no standardized pre-processing pipeline for PPG signal processing, as PPG data are acquired and accumulated in various ways, the recently proposed machine learning-based method is expected to offer a promising solution.

Sex features of cutaneous microvasculature in healthy working-age people

Aim. To study sex characteristics of cutaneous microvascular structure and function in a cohort of healthy working-age people without cardiovascular diseases.

Material and methods. The study included 35 healthy men (42±4 years) and 34 women (41 ±5 years). The cardiovascular system was assessed in all patients. The microcirculatory bed of the skin was investigated by the following non-invasive methods: 1) computerized video capillaroscopy; 2) laser Doppler flowmetry; 3) photoplethysmography.

Results. According to computerized video capillaroscopy in men, compared with women, there was a smaller number of both functioning capillaries (78 vs 86 capillaries/mm2, respectively (p<0,05)) and their total number (100 vs 120 capillaries/mm2, respectively (p<0,001)). Against the background of a decrease in capillary density in men, there was a higher skin interstitial hydration — 113 vs 96 gm (p<0,005) in men than in women. At the level of precapillary arterioles, where humoral tone regulation prevails. Laser Doppler flowmetry revealed lower pulse amplitude in men than in women — 0,87 vs 1,02 pf, respectively (p<0,05), which indicates a lower arterial blood inflow to exchange microvessels. Against this background, the constrictor response of precapillary arterioles to a sympathetic nervous system stimulation in men is higher than in women — 45% vs 40%, respectively (p<0,05). At the level of large arterioles, where neural tone regulation prevails, photoplethysmography revealed lower augmentation index standardized at a heart rate in men (-4,6 vs 1,7%, respectively, p<0,05), which indicates lower rigidity of muscular vessels in men.

Conclusion. In working-age healthy people, sex differences are noted at all cutaneous microvascular levels, which must be taken into account when planning studies.

Photoplethysmography Analysis with Duffing–Holmes Self-Synchronization Dynamic Errors and 1D CNN-Based Classifier for Upper Extremity Vascular Disease Screening

Common upper limb peripheral artery diseases (PADs) are atherosclerosis, embolic diseases, and systemic diseases, which are often asymptomatic, and the narrowed arteries (stenosis) will gradually reduce blood flow in the right or left upper limbs. Upper extremity vascular disease (UEVD) and atherosclerosis are high-risk PADs for patients with Type 2 diabetes or with both diabetes and end-stage renal disease. For early UEVD detection, a fingertip-based, toe-based, or wrist-based photoplethysmography (PPG) tool is a simple and noninvasive measurement system for vital sign monitoring and healthcare applications. Based on time-domain PPG analysis, a Duffing–Holmes system with a master system and a slave system is used to extract self-synchronization dynamic errors, which can track the differences in PPG morphology (in amplitudes (systolic peak) and time delay (systolic peak to diastolic peak)) between healthy subjects and PAD patients. In the preliminary analysis, the self-synchronization dynamic errors can be used to evaluate risk levels based on the reflection index (RI), which includes normal condition, lower PAD, and higher PAD. Then, a one-dimensional convolutional neural network is established as a multilayer classifier for automatic UEVD screening. The experimental results indicated that the self-synchronization dynamic errors have a positive correlation with the RI (R2 = 0.6694). The K-fold cross-validation is used to verify the performance of the proposed classifier with recall (%), precision (%), accuracy (%), and F1 score.

A comparative study of photoplethysmogram and piezoelectric plethysmogram signals

The Photoplethysmogram (PPG) signal is one of the most important vital signals in biomedical applications. The non-invasive property and the convenience in the acquisition of both PPG and Piezoelectric Plethysmogram (PZPG) signals are considered as powerful and accurate tools for biomedical diagnosing applications, such as oxygen saturation in blood, blood flow, and blood pressure measurements. In this paper, a number of features for PPG and PZPG signals (ex. first derivative, second derivative, area under the curve and the ratio of systolic area to the diastolic area) are acquired and compared. The results show that both systems are able to extract the pulse rate (PR) and pulse rate variability (PRV), accurately with an estimation error of less than 10%. The averaged standard deviation of the ratio of the systolic area to the diastolic area for the first derivative of PPG and PZPG signals was small with less than 0.49 and 0.69 for the PPG and PZPG, respectively. Statistical analysis techniques (such as cross-correlation, P-value test, and Bland Altman method) are performed to address the relation between the PPG and PZPG signals. All of these methods showed a strong relationship between the features of the two signals (i.e. PPG and PZPG). The correlation value is found to be 0.954 with a p-value of < 0.05. This opens possibilities for combining both the PPG and PZPG systems to extract more features that can be used in diagnosing cardiovascular diseases. Such a system can provide a possibility to reduce the number of devices connected to patients (especially in emergencies) by means of measuring simultaneously both signals (PZPG and PPG).

Is Heart Rate a Confounding Factor for Photoplethysmography Markers? A Systematic Review

Finger photoplethysmography (PPG) waveform is blood volume change of finger microcirculation that reflects vascular function. Reflection index (RI), stiffness index (SI) and second derivative of photoplethysmogram (SDPPG) are derived from PPG waveforms proposed as cardiovascular disease (CVD) markers. Heart rate (HR) is a known factor that affects vascular function. Individual resting HR variation may affect RI, SI and SDPPG. This review aims to identify studies about the relationship between HR with RI, SI and SDPPG among humans. A literature search was conducted in Medline via the Ebscohost and Scopus databases to find relevant articles published within 11 years. The main inclusion criteria were articles in the English language that discuss the relationship between HR with RI, SI and SDPPG using PPG among humans. The search found 1960 relevant articles but only six articles that met the inclusion criteria. SI and RI showed an association with HR. SDPPG (SDPPG-b/SDPPG-a ratio, SDPPG-d/SDPPG-a ratio, aging index (AGI) and revised aging index (RAGI)) also had an association with HR. Only RI had a considerable association with HR, the association between SI and HR was non-considerable and the association between HR and SDPPG was inconclusive. Further interventional studies should be conducted to investigate this issue, as a variation in resting HR may challenge the validity of PPG-based CVD markers.

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.

Familial history of hypertension as a predictor of increased arterial stiffness in normotensive offspring

Background

Increased arterial stiffness can be used as a prognostic marker of arterial hypertension. The relationship between arterial stiffness and arterial hypertension seems to be reciprocal.

Objective

Evaluation of changes of the arterial elastic prosperities in normotensive subjects, with and without parental history of hypertension.

Subjects and Methods

One hundred and ten normotensive individuals, aged 20–30 years, were divided into two groups: group-A (n = 57) and group-B (n = 53) subjects with positive and negative parental history of hypertension, respectively. Systolic, diastolic and pulse pressures were measured using mercury sphygmomanometer. The elastic properties of the ascending aorta and the common carotid arteries were assessed using M-mode echo and B-mode imaging, respectively. Stiffness index of the digital volume pulse (SIDVP) was measured in the right index finger using photoplethysmography.

Results

Group A subjects showed higher aortic stiffness index (p = 0.002), carotid stiffness index (p = 0.001), carotid pulse wave velocity (p ⩽ 0.001) and stiffness index of digital volume pulse (p = 0.001). Group A subjects showed lower aortic distensibility (p = 0.001), aortic strain (p = 0.004), changes in aortic diameter (p = 0.022), carotid distension (p = 0.026), carotid distensibility coefficient (p ⩽ 0.001) and carotid compliance coefficient (p = 0.002).

Conclusion

The aortic and carotid stiffness parameters and SIDVP were higher in normotensive offspring of hypertensive parents. This finding could direct the attention towards the increased cardiovascular risk in this group and thus prompt earlier and tighter prevention of cardiovascular risk factors.

Feasibility study for the non-invasive blood pressure estimation based on ppg morphology: normotensive subject study

Background

Blood pressure is a critical bio-signal and its importance has been increased with the aged society and the growth of cardiovascular disease population. However, most of hypertensive patients have been suffered the inconvenience in monitoring blood pressure in daily life because the measurement of the blood pressure depends on the cuff-based technique. Nowadays there are many trials to measure blood pressure without cuff, especially, photoplethysmography (PPG) based research is carried out in various ways.

Methods

Our research is designed to hypothesis the relationship between vessel wall movement and pressure-flow relationship of PPG and to validate its appropriateness by experimental methods. PPG waveform is simplified by approximate model, and then it is analyzed as the velocity and the acceleration of blood flow using the derivatives of PPG. Finally, we develop pressure index (PI) as an estimation factor of blood pressure by combining of statistically significant segments of photoplethysmographic waveform.

Results

Twenty-five subjects were participated in the experiment. As a result of simulation, correlation coefficients between developed PI and blood pressure were represented with R = 0.818, R = 0.827 and R = 0.615 in systolic blood pressure, pulse pressure and mean arterial pressure, respectively, and both of result showed the meaningful statistically significance (P < 0.05).

Conclusions

Current study can estimate only the relative variation of blood pressure but could not find the absolute pressure value. Moreover, proposed index has the limitation of diastolic pressure tracing. However, the result shows that the proposed PI is statistically significantly correlated with blood pressures, and it suggests that the proposed PI as a promising additional parameter for the cuff less blood pressure monitoring.

A vibration-based approach to quantifying the dynamic elastance of the superficial arterial wall

Background

The purpose of this study is to propose a novel method for assessing dynamic elastance of the superficial arterial wall using the sinusoidal minute vibration method.

Methods

A sinusoidal signal was used to drive a vibrator which induced a displacement of 0.15 mm with a frequency range between 40 and 85 Hz. The vibrator closely contacted with the wall of a superficial radial artery, and caused the arterial wall to shift simultaneously. A force sensor attached to the tip of the vibrator was used to pick up the reactive force exerted by the radial arterial wall. According to the Voigt and Maxwell models, a linear relationship was found between the maximum reactive force and the squared angular frequency of the vibration. The intercept of the linear function represents the arterial wall elastance. In order to validate the feasibility of our method, twenty-nine healthy subjects were recruited and the wall elastances of their radial arteries were measured at room temperature (25 °C), after a 5-min cold stress (4 °C) and a 5-min hot stress (42 °C), respectively.

Results

After the 5-min cold stimulation, the maximum radial wall elastance significantly increased from 0.441 ± 0.182 × 10⁶ dyne/cm to 0.611 ± 0.251 × 10⁶ dyne/cm (p = 0.001). In the 5-min hot stress, the maximum radial wall elastance significantly decreased to 0.363 ± 0.106 × 10⁶ dyne/cm (p = 0.013).

Conclusions

The sinusoidal minute vibration method proposed can be employed to obtain the quantitative elastance of a superficial artery under different thermal conditions, and to help assess the severity of arterial stiffness in conduit arteries.

Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram

Monitoring of cardiovascular function on a beat-to-beat basis is fundamental for protecting patients in different settings including emergency medicine and interventional cardiology, but still faces technical challenges and several limitations. In the present study, we propose a new method for the extraction of cardiovascular performance surrogates from analysis of the photoplethysmographic (PPG) signal alone.We propose using a multi-Gaussian (MG) model consisting of five Gaussian functions to decompose the PPG pulses into its main physiological components. From the analysis of these components, we aim to extract estimators of the left ventricular ejection time, blood pressure and vascular tone changes. Using a multi-derivative analysis of the components related with the systolic ejection, we investigate which are the characteristic points that best define the left ventricular ejection time (LVET). Six LVET estimates were compared with the echocardiographic LVET in a database comprising 68 healthy and cardiovascular diseased volunteers. The best LVET estimate achieved a low absolute error (15.41   ±   13.66 ms), and a high correlation (ρ = 0.78) with the echocardiographic reference.To assess the potential use of the temporal and morphological characteristics of the proposed MG model components as surrogates for blood pressure and vascular tone, six parameters have been investigated: the stiffness index (SI), the T1_d and T1_2 (defined as the time span between the MG model forward and reflected waves), the reflection index (RI), the R1_d and the R1_2 (defined as their amplitude ratio). Their association to reference values of blood pressure and total peripheral resistance was investigated in 43 volunteers exhibiting hemodynamic instability. A good correlation was found between the majority of the extracted and reference parameters, with an exception to R1_2 (amplitude ratio between the main forward wave and the first reflection wave), which correlated low with all the reference parameters. The highest correlation ([Formula: see text] = 0.45) was found between T1_2 and the total peripheral resistance index (TPRI); while in the patients that experienced syncope, the highest agreement ([Formula: see text] = 0.57) was found between SI and systolic blood pressure (SBP) and mean blood pressure (MBP).In conclusion, the presented method for the extraction of surrogates of cardiovascular performance might improve patient monitoring and warrants further investigation.

Effect of Different Phases of Menstrual Cycle on Reflection Index, Stiffness index and Pulse wave velocity in Healthy subjects

INTRODUCTION

Arterial compliance will result in stabilizing the fluctuations in arterial pressure and blood flow. So arterial stiffness can be a good indicator for monitoring the cardiovascular system. Arterial stiffness can be measured using indices like reflection index (RI), stiffness index (SI) and Brachial Finger Pulse Wave Velocity (BFPWV).

OBJECTIVES

Aim of our study was to evaluate the changes in RI, SI and BFPWV during different phases of the menstrual cycle and to correlate RI with SI in healthy female subjects between the age group of 18-30 years from Bangalore, India.

MATERIALS AND METHODS

Basal recordings of RI and SI were determined by Photo Pulse Plethysmography (PPG) picked up from the fingertip using BIOPAC system and BFPWV was obtained using Doppler. Recordings were obtained at three different time points during the menstrual cycle. Analysis was done using repeated measures ANOVA with Bonferroni correction.

RESULT

There was a significant decrease in above parameters p <0.05 during the mid-cycle. Correlation between RI and SI was also significant p<0.05.

CONCLUSION

These findings suggests that the menstrual cycle affects the arterial stiffness and one of the factor is oestrogen. Hence, women are less prone to the incidence of cardiovascular diseases before menopause. Screening for arterial stiffness in a general population, using these indices is valid, economical and reliable.

Three-Grade Classification of Photoplethysmography for Evaluating the Effects of Treatment in Raynaud Phenomenon

We assessed the utility of a 3-grade classification of photoplethysmography (PPG) with cold water provocation test in Raynaud phenomenon (RP). A total of 35 patients with RP and 38 healthy volunteers were recruited. In healthy volunteers, PPG was measured twice at intervals of 30 minutes for evaluating reproducibility of test. Percentage variation of the PPG amplitude in post- versus precold provocation was expressed on a 3-grade scale at 1, 3, and 5 minutes (reflection index: RI) in patients with RP. The improvement pattern of the PPG (IPPPG) was evaluated by summing the score differences from RI1 min to RI3 min and RI5 min. After a therapeutic period of 8 weeks with nifedipine, the decreases in posttherapeutic RI3 min and RI5 min were statistically significant ( P < .05). Subgroup analysis of IPPPG showed statistical significance in patients with negative fluorescent antinuclear antibody ( P < .05). The analysis of cold-provoked PPG waves demonstrated and quantified improvements in peripheral arterial circulation in RP.

A novel method for assessing arterial stiffness by a hydrostatic approach

Arterial stiffness is an important index for cardiovascular events. The objective of this study is to examine possible parameters related to arterial stiffness that can be estimated during simple arm movements. An experiment was conducted on 32 subjects divided into two groups, one with an age of 26+/-4 years old, and the other 61+/-9. The pulse transit time measured from electrocardiogram to finger photoplethysmogram (PPG) and the amplitude of PPG were calculated beat-to-beat for the subjects while they had their arms lowered. The results of the study showed that the ratio between percentage changes in PTT and finger height are significantly different for the two groups of subjects with different age and health conditions, indicating that parameters can be potentially extracted from this procedure to represent the difference in arterial stiffness of the two groups of subjects.

A study on polymorphisms of elastin gene in Chinese Han patients with isolated systolic hypertension

BACKGROUND

Elastin (ELN) is mainly located in the internal elastic lamina of large arteries. Degradation of ELN is expected to induce large vessel stiffness, which could lead to elderly systolic hypertension. Recent studies have shown that polymorphism of ELN is associated with stiffness of elastic arteries and elevated blood pressure; however, there are no further studies on isolated systolic hypertension (ISH).

METHODS

We identified the genotype of the ELN gene in 358 patients with ISH, 413 essential hypertension (EH) patients with elevated diastolic blood pressure (DBP), and 244 age-matched normotensive (NT) controls for five single-nucleotide polymorphisms (SNPs) and detected the brachial-ankle pulse wave velocity (baPWV), C-reactive protein (CRP), and intima-media thickness (IMT) for these patients.

RESULTS

ISH was statistically significant in association with SNP rs34208922 (A allele frequency was 0.068 in ISH patients, 0.036 in EH patients, and 0.014 in NT controls; P < 0.001, P(corr) < 0.005) and possibly with SNP rs2071307 (A allele frequency was 0.103 in ISH patients, 0.079 in EH patients, and 0.047 in NT controls; P = 0.002, P(corr) = 0.01), however, the A allele frequency was not different between ISH patients and EH patients. In addition, baPWV and CRP were significantly associated with SNP rs34208922 and rs2071307. The other three SNPs were not significantly associated with ISH, baPWV, CRP, or IMT. Haplotypes of TGGTA and TGAT- were also significantly associated with ISH (P = 0.0001, P(corr) = 0.0021; P = 0.0023, P(corr) = 0.0483).

CONCLUSIONS

Variants within the ELN gene are associated with increased risk of ISH and aortic stiffness in the Chinese Han population.