Measurement of Aortic Pulse Wave Velocity With a Connected Bathroom Scale

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

Unlabelled

The integration of health and activity data from various wearable devices into research studies presents technical and operational challenges. The Awesome Data Acquisition Method (ADAM) is a versatile, web-based system that was designed for integrating data from various sources and managing a large-scale multiphase research study. As a data collecting system, ADAM allows real-time data collection from wearable devices through the device's application programmable interface and the mobile app's adaptive real-time questionnaires. As a clinical trial management system, ADAM integrates clinical trial management processes and efficiently supports recruitment, screening, randomization, data tracking, data reporting, and data analysis during the entire research study process. We used a behavioral weight-loss intervention study (SMARTER trial) as a test case to evaluate the ADAM system. SMARTER was a randomized controlled trial that screened 1741 participants and enrolled 502 adults. As a result, the ADAM system was efficiently and successfully deployed to organize and manage the SMARTER trial. Moreover, with its versatile integration capability, the ADAM system made the necessary switch to fully remote assessments and tracking that are performed seamlessly and promptly when the COVID-19 pandemic ceased in-person contact. The remote-native features afforded by the ADAM system minimized the effects of the COVID-19 lockdown on the SMARTER trial. The success of SMARTER proved the comprehensiveness and efficiency of the ADAM system. Moreover, ADAM was designed to be generalizable and scalable to fit other studies with minimal editing, redevelopment, and customization. The ADAM system can benefit various behavioral interventions and different populations.

Long-term trajectories of weight loss and health outcomes: protocol of the SCOOP-RNPC nationwide observational study

INTRODUCTION

Behavioural weight loss programmes are generally accepted as being beneficial in reducing cardiometabolic risk and improving patient-reported outcomes. However, prospective data from large real-world cohorts are scarce concerning the mid-term and long-term impact of such interventions. The objective of this large prospective cohort study (n>10 000 participants) is to demonstrate the effectiveness of the standardised Nutritional and Psycho-Behavioural Rehabilitation programme (RNPC Programme) in reducing the percentage of subjects requiring insulin and/or other diabetes drug therapy, antihypertensive drugs, lipid-lowering therapies and continuous positive airway pressure therapy for obstructive sleep apnoea after the end of the intervention. The rate of remission of hypertension, type 2 diabetes and sleep apnoea will also be prospectively assessed.

METHODS

This is a prospective multicentre observational study carried out in 92 RNPC centres in France. Participants will follow the standardised RNPC Programme. The prospective dataset will include clinical, anthropometric and biochemical data, comorbidities, medications, body composition, patient-reported outcome questionnaire responses, sleep study data with objective measurements of sleep apnoea severity and surrogate markers of cardiovascular risk (ie, blood pressure and arterial stiffness). About 10 000 overweight or obese participants will be included over 2 years with a follow-up duration of up to 5 years.

ETHICS AND DISSEMINATION

Ethical approval for this study has been granted by the Ethics Committee (Comité de protection des personnes Sud-Est I) of Saint-Etienne University Hospital, France (SI number: 23.00174.000237). Results will be submitted for publication in peer-review journals, presented at conferences and inform the design of a future randomised controlled trial in the specific population identified as good responders to the RNPC Programme.

TRIAL REGISTRATION NUMBER

NCT05857319.

Estimated pulse-wave velocity predicts survival in patients requiring extracorporeal membrane oxygenation

INTRODUCTION

Arterial stiffness, measured by estimated pulse-wave velocity is a known predictor of major adverse cardiovascular events, however its predictive value in patients requiring extracorporeal membrane oxygenation (ECMO) is unknown.

METHODS

A retrospective cohort study was performed at the London Health Science Centre in London, Canada between 1996-2021, totaling 255 patients requiring ECMO. Estimated pulse-wave velocity (ePWV) was calculated using an algorithm from the Reference Values for Arterial Stiffness Collaboration. Recorded outcomes included in-hospital death, ischemic stroke, hemorrhagic stroke, renal failure and need for renal replacement therapy (RRT). For adjusted analysis, survival-to-discharge was used. Multivariate logistic regression and propensity-score matching were utilized to control for confounding.

RESULTS

On univariate analysis, higher ePWV was significantly predictive of ischemic stroke (OR 1.676, p = 0.0002) and in-hospital death (OR 1.20, p = 0.006), but insignificant for predicting hemorrhagic stroke (OR 1.07, p = 0.710), and appeared protective for renal failure (OR 0.88 [0.78-0.99], p = 0.034) and RRT (OR 0.87, p = 0.027). On multivariate analysis and propensity-score matching, five of six models demonstrated ePWV as an independent predictor of survival-to-discharge. (OR 0.70, p = 0.00,021; OR 0.72, p = 0.0002; OR 0.87, p = 0.045; OR 0.85, p = 0.013; OR 0.57, p = 0.012).

CONCLUSIONS

ePWV is a promising marker for risk-stratification in ECMO patients. Further investigation is required to better delineate the role of arterial health assessment in disease trajectory and strengthen the validity of AS as a marker of interest in medical and surgical management.

2024 Recommendations for Validation of Noninvasive Arterial Pulse Wave Velocity Measurement Devices

BACKGROUND

Arterial stiffness, as measured by arterial pulse wave velocity (PWV), is an established biomarker for cardiovascular risk and target-organ damage in individuals with hypertension. With the emergence of new devices for assessing PWV, it has become evident that some of these devices yield results that display significant discrepancies compared with previous devices. This discrepancy underscores the importance of comprehensive validation procedures and the need for international recommendations.

METHODS

A stepwise approach utilizing the modified Delphi technique, with the involvement of key scientific societies dedicated to arterial stiffness research worldwide, was adopted to formulate, through a multidisciplinary vision, a shared approach to the validation of noninvasive arterial PWV measurement devices.

RESULTS

A set of recommendations has been developed, which aim to provide guidance to clinicians, researchers, and device manufacturers regarding the validation of new PWV measurement devices. The intention behind these recommendations is to ensure that the validation process can be conducted in a rigorous and consistent manner and to promote standardization and harmonization among PWV devices, thereby facilitating their widespread adoption in clinical practice.

CONCLUSIONS

It is hoped that these recommendations will encourage both users and developers of PWV measurement devices to critically evaluate and validate their technologies, ultimately leading to improved consistency and comparability of results. This, in turn, will enhance the clinical utility of PWV as a valuable tool for assessing arterial stiffness and informing cardiovascular risk stratification and management in individuals with hypertension.

Vascular ageing: moving from bench towards bedside

Prevention of cardiovascular disease (CVD) remains one of the largest public health challenges of our time. Identifying individuals at increased cardiovascular risk at an asymptomatic, sub-clinical stage is of paramount importance for minimizing disease progression as well as the substantial health and economic burden associated with overt CVD. Vascular ageing (VA) involves the deterioration in vascular structure and function over time and ultimately leads to damage in the heart, brain, kidney, and other organs. Vascular ageing encompasses the cumulative effect of all cardiovascular risk factors on the arterial wall over the life course and thus may help identify those at elevated cardiovascular risk, early in disease development. Although the concept of VA is gaining interest clinically, it is seldom measured in routine clinical practice due to lack of consensus on how to characterize VA as physiological vs. pathological and various practical issues. In this state-of-the-art review and as a network of scientists, clinicians, engineers, and industry partners with expertise in VA, we address six questions related to VA in an attempt to increase knowledge among the broader medical community and move the routine measurement of VA a little closer from bench towards bedside.

Wrist ballistocardiography and invasively recorded blood pressure in healthy volunteers during reclining bike exercise

Objective: Ballistocardiogram (BCG) features are of interest in wearable cardiovascular monitoring of cardiac performance. We assess feasibility of wrist acceleration BCG during exercise for estimating pulse transit time (PTT), enabling broader cardiovascular response studies during acute exercise and improved monitoring in individuals at risk for cardiovascular disease (CVD). We also examine the relationship between PTT, blood pressure (BP), and stroke volume (SV) during exercise and posture interventions. Methods: 25 participants underwent a bike exercise protocol with four incremental workloads (0 W, 50 W, 100 W, and 150 W) in supine and semirecumbent postures. BCG, invasive radial artery BP, tonometry, photoplethysmography (PPG) and echocardiography were recorded. Ensemble averages of BCG signals determined aortic valve opening (AVO) timings, combined with peripheral pulse wave arrival times to calculate PTT. We tested for significance using Wilcoxon signed-rank test. Results: BCG was successfully recorded at the wrist during exercise. PTT exhibited a moderate negative correlation with systolic BP (ρ_Sup = -0.65, ρ_SR = -0.57, ρ_All = -0.54). PTT differences between supine and semirecumbent conditions were significant at 0 W and 50 W (p < 0.001), less at 100 W (p = 0.0135) and 150 W (p = 0.031). SBP and DBP were lower in semirecumbent posture (p < 0.01), while HR was slightly higher. Echocardiography confirmed association of BCG features with AVO and indicated a positive relationship between BCG amplitude and SV (ρ = 0.74). Significance: Wrist BCG may allow convenient PTT and possibly SV tracking during exercise, enabling studies of cardiovascular response to acute exercise and convenient monitoring of cardiovascular performance.

Collecting health-related research data using consumer-based wireless smart scales

BACKGROUND

Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population's health. They can present us with a picture of our metabolism, body health, and disease risks. Combining body composition data with physical activity measurements from devices such as smart watches could contribute to building a human digital twin.

OBJECTIVE

The objectives of this study were to (1) investigate the evolution of smart scales in the last decade, (2) map status and supported sensors of smart scales, (3) get an overview of how smart scales have been used in research, and (4) identify smart scales for current and future research.

METHOD

We searched for devices through web shops and smart scale tests/reviews, extracting data from the manufacturer's official website, user manuals when available, and data from web shops. We also searched scientific literature databases for smart scale usage in scientific papers.

RESULT

We identified 165 smart scales with a wireless connection from 72 different manufacturers, released between 2009 and end of 2021. Of these devices, 49 (28%) had been discontinued by end of 2021. We found that the use of major variables such as fat and muscle mass have been as good as constant over the years, and that minor variables such as visceral fat and protein mass have increased since 2015. The main contribution is a representative overview of consumer grade smart scales between 2009 and 2021.

CONCLUSION

The last six years have seen a distinct increase of these devices in the marketplace, measuring body composition with bone mass, muscle mass, fat mass, and water mass, in addition to weight. Still, the number of research projects featuring connected smart scales are few. One reason could be the lack of professionally accurate measurements, though trend analysis might be a more feasible usage scenario.

Digital health technology to support care and improve outcomes of chronic kidney disease patients: as a case illustration, the Withings toolkit health sensing tools

Cardiovascular disease (CVD) is a major burden in dialysis-dependent chronic kidney disease (CKD5D) patients. Several factors contribute to this vulnerability including traditional risk factors such as age, gender, life style and comorbidities, and non-traditional ones as part of dialysis-induced systemic stress. In this context, it appears of utmost importance to bring a closer attention to CVD monitoring in caring for CKD5D patients to ensure early and appropriate intervention for improving their outcomes. Interestingly, new home-used, self-operated, connected medical devices offer convenient and new tools for monitoring in a fully automated and ambulatory mode CKD5D patients during the interdialytic period. Sensoring devices are installed with WiFi or Bluetooth. Some devices are also available in a cellular version such as the Withings Remote Patient Monitoring (RPM) solution. These devices analyze the data and upload the results to Withings HDS (Hybrid data security) platform servers. Data visualization can be viewed by the patient using the Withings Health Mate application on a smartphone, or with a web interface. Health Care Professionals (HCP) can also visualize patient data via the Withings web-based RPM interface. In this narrative essay, we analyze the clinical potential of pervasive wearable sensors for monitoring ambulatory dialysis patients and provide an assessment of such toolkit digital medical health devices currently available on the market. These devices offer a fully automated, unobtrusive and remote monitoring of main vital functions in ambulatory subjects. These unique features provide a multidimensional assessment of ambulatory CKD5D patients covering most physiologic functionalities, detecting unexpected disorders (i.e., volume overload, arrhythmias, sleep disorders) and allowing physicians to judge patient's response to treatment and recommendations. In the future, the wider availability of such pervasive health sensing and digital technology to monitor patients at an affordable cost price will improve the personalized management of CKD5D patients, so potentially resulting in improvements in patient quality of life and survival.

Expert Consensus on the Clinical Use of Pulse Wave Velocity in Asia

Arterial stiffness is a progressive aging process that predicts cardiovascular disease. Pulse wave velocity (PWV) has emerged as a noninvasive, valid, and reliable measure of arterial stiffness and an independent risk predictor for adverse outcomes. However, up to now, PWV measurement has mostly been used as a tool for risk prediction and has not been widely used in clinical practice. This consensus paper aims to discuss multiple PWV measurements currently available in Asia and to provide evidence-based assessment together with recommendations on the clinical use of PWV. For the methodology, PWV measurement including the central elastic artery is essential and measurements including both the central elastic and peripheral muscular arteries, such as brachial-ankle PWV and cardio-ankle vascular index, can be a good alternative. As Asian populations are rapidly aging, timely detection and intervention of "early vascular aging" in terms of abnormally high PWV values are recommended. More evidence is needed to determine if a PWV-guided therapeutic approach will be beneficial to the prevention of cardiovascular diseases beyond current strategies. Large-scale randomized controlled intervention studies are needed to guide clinicians.

Home monitoring of arterial pulse-wave velocity during COVID-19 total or partial lockdown using connected smart scales. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2022;3:362-372. [PMID: 36712157 PMCID: PMC9384477 DOI: 10.1093/ehjdh/ztac027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Aims

To investigate the impact of coronavirus disease 2019 lockdown on trajectories of arterial pulse-wave velocity in a large population of users of connected smart scales that provide reliable measurements of pulse-wave velocity.

Methods and results

Pulse-wave velocity recordings obtained by Withings Heart Health & Body Composition Wi-Fi Smart Scale users before and during lockdown were analysed. We compared two demonstrative countries: France, where strict lockdown rules were enforced (n = 26 196) and Germany, where lockdown was partial (n = 26 847). Subgroup analysis was conducted in users of activity trackers and home blood pressure monitors. Linear growth curve modelling and trajectory clustering analyses were performed. During lockdown, a significant reduction in vascular stiffness, weight, blood pressure, and physical activity was observed in the overall population. Pulse-wave velocity reduction was greater in France than in Germany, corresponding to 5.2 month reduction in vascular age. In the French population, three clusters of stiffness trajectories were identified: decreasing (21.1%), stable (60.6%), and increasing pulse-wave velocity clusters (18.2%). Decreasing and increasing clusters both had higher pulse-wave velocity and vascular age before lockdown compared with the stable cluster. Only the decreasing cluster showed a significant weight reduction (-400 g), whereas living alone was associated with increasing pulse-wave velocity cluster. No clusters were identified in the German population.

Conclusions

During total lockdown in France, a reduction in pulse-wave velocity in a significant proportion of French users of connected smart bathroom scales occurred. The impact on long-term cardiovascular health remains to be established.

Pulse wave velocity measurement along the ulnar artery in the wrist region using a high frequency ultrasonic array

A pulse wave velocity (PWV) measurement method performed above a small blood vessel using an ultrasonic probe is studied and reported in this paper. These experimentations are carried out using a high-frequency probe (14-22 MHz), allowing a high level of resolution compatible with the vessel dimensions, combined with an open research ultrasound scanner. High frame-rate (HFR) imaging (10 000 frames per second) is used for a precise PWV estimation. The measurements are performed in-vivo on a healthy volunteer. The probe is placed above the ulnar artery on the wrist in order to make longitudinal scans. In addition to conventional duplex ultrasound evaluation, the measurement of the PWV using this method at this location could strengthen the detection and diagnosis of cardiovascular diseases (CVDs), in particular for arm artery diseases (AADs). Moreover, these experimentations are also carried out within the scope of a demonstration for a potential miniaturized and wearable device (i.e., a probe with fewer elements, typically less than 32, and its associated electronics). The study has shown results coherent with expected PWV and also promising complementary results such as intima-media thickness (IMT) with spatiotemporal resolution on the order of 6.2 μm and 0.1 ms.

Leveraging the potential of machine learning for assessing vascular ageing: state-of-the-art and future research

Vascular ageing biomarkers have been found to be predictive of cardiovascular risk independently of classical risk factors, yet are not widely used in clinical practice. In this review, we present two basic approaches for using machine learning (ML) to assess vascular age: parameter estimation and risk classification. We then summarize their role in developing new techniques to assess vascular ageing quickly and accurately. We discuss the methods used to validate ML-based markers, the evidence for their clinical utility, and key directions for future research. The review is complemented by case studies of the use of ML in vascular age assessment which can be replicated using freely available data and code.

The Latest Progress and Development Trend in the Research of Ballistocardiography (BCG) and Seismocardiogram (SCG) in the Field of Health Care

The current status of the research of Ballistocardiography (BCG) and Seismocardiogram (SCG) in the field of medical treatment, health care and nursing was analyzed systematically, and the important direction in the research was explored, to provide reference for the relevant researches. This study, based on two large databases, CNKI and PubMed, used the bibliometric analysis method to review the existing documents in the past 20 years, and made analyses on the literature of BCG and SCG for their annual changes, main countries/regions, types of research, frequently-used subject words, and important research subjects. The results show that the developed countries have taken a leading position in the researches in this field, and have made breakthroughs in some subjects, but their research results have been mainly gained in the area of research and development of the technologies, and very few have been actually industrialized into commodities. This means that in the future the researchers should focus on the transformation of BCG and SCG technologies into commercialized products, and set up quantitative health assessment models, so as to become the daily tools for people to monitor their health status and manage their own health, and as the main approaches of improving the quality of life and preventing diseases for individuals.

Can pulse wave velocity (PWV) alone express arterial stiffness? A neglected tool for vascular function assessment

Arterial stiffness, defined as the rigidity of the arterial wall, is the consequence of vascular aging and is associated with the full spectrum of cardiovascular diseases. Carotid-femoral pulse wave velocity (cf-PWV) is the gold standard method for arterial stiffness evaluation: it measures the velocity of the arterial pulse along the thoracic and abdominal aorta alongside arterial distensibility. Its value rises as stiffness progresses. Cf-PWV is helpful to assess residual cardiovascular risk (CVR) in hypertension (HT). In fact, an increase in pulsatility and arterial stiffness predicts CVR in patients affected by arterial HT, independently of other risk factors. Arterial stiffness can predict cardiovascular events in several other clinical conditions such as heart failure, diabetes, and pulmonary HT. However, cf-PWV has not been yet included in routine clinical practice so far. A possible reason might be its methodological and theoretical limitations (inaccuracy in the traveled distance, intra and interindividual variability, lack of well-defined references values, and age- and blood pressure-independent cutoff). To exceed these limits a strict adherence to guidelines, use of analytical approaches, and possibility of integrating the results with other stiffness examinations are essential approaches.

Arterial Stiffness and Cardiovascular Risk in Hypertension

Arterial stiffness, a leading marker of risk in hypertension, can be measured at material or structural levels, with the latter combining effects of the geometry and composition of the wall, including intramural organization. Numerous studies have shown that structural stiffness predicts outcomes in models that adjust for conventional risk factors. Elastic arteries, nearer to the heart, are most sensitive to effects of blood pressure and age, major determinants of stiffness. Stiffness is usually considered as an index of vascular aging, wherein individuals excessively affected by risk factor exposure represent early vascular aging, whereas those resistant to risk factors represent supernormal vascular aging. Stiffness affects the function of the brain and kidneys by increasing pulsatile loads within their microvascular beds, and the heart by increasing left ventricular systolic load; excessive pressure pulsatility also decreases diastolic pressure, necessary for coronary perfusion. Stiffness promotes inward remodeling of small arteries, which increases resistance, blood pressure, and in turn, central artery stiffness, thus creating an insidious feedback loop. Chronic antihypertensive treatments can reduce stiffness beyond passive reductions due to decreased blood pressure. Preventive drugs, such as lipid-lowering drugs and antidiabetic drugs, have additional effects on stiffness, independent of pressure. Newer anti-inflammatory drugs also have blood pressure independent effects. Reduction of stiffness is expected to confer benefit beyond the lowering of pressure, although this hypothesis is not yet proven. We summarize different steps for making arterial stiffness measurement a keystone in hypertension management and cardiovascular prevention as a whole.

Withings Body Cardio versus Gold Standards of Pulse-Wave Velocity and Body Composition

Home blood pressure monitors are widely used by consumers yet cardiovascular health may be better defined by pulse-wave velocity (PWV). So far, the Withings Body Cardio scale is the only consumer device that has been designed to measure PWV and body composition, including fat mass (FM) and fat-free mass (FFM), in the home setting. While one study has demonstrated that this device meets the acceptable accuracy standards of the ARTERY Society, no study has accounted for the gravitational effect of standing on a scale on aortic-leg PWV.

PURPOSE

The purpose of this study was to assess the accuracy of PWV and body composition as determined by the Body Cardio scale.

METHODS

Measurements of PWV and body composition in healthy, young males and females (n = 20) using the Body Cardio device were compared to PWV assessed by applanation tonometry (SphygmoCor) and body composition analysis determined by air displacement plethysmography (Bod Pod). Bland-Altman analysis and mean absolute percent error (MAPE) were used to assess accuracy.

RESULTS

Data are reported as the mean bias (95% confidence interval). The Body Cardio overestimated PWV by 0.68 m/s (-0.16, 1.51) and FM by 2.91 kg (-2.91, 8.73). Body Cardio PWV and FM estimations had a MAPE of 9.7% and 25.8%, respectively. The Body Cardio underestimated body mass (BM) and FFM by 0.11 kg (-0.41, 0.18) and 2.87 kg (-9.04, 3.30), respectively. Body Cardio BM and FFM estimations had a MAPE of 0.15% and 5.6%, respectively.

CONCLUSIONS

The Body Cardio scale provides accurate measures of BM and PWV; however, it should be used cautiously for measures of FM and FFM.

Biosensors for Personal Mobile Health: A System Architecture Perspective

Advances in mobile biosensors, integrating developments in materials science and instrumentation, are fueling an expansion in health data being collected and analyzed in decentralized settings. For example, semiconductor-based sensors are enabling measurement of vital signs, and microfluidic-based sensors are enabling measurement of biochemical markers. As biosensors for mobile health are becoming increasingly paired with smart devices, it will become critical for researchers to design biosensors - with appropriate functionalities and specifications - to work seamlessly with accompanying connected hardware and software. This article describes recent research in biosensors, as well as current mobile health devices in use, as classified into four distinct system architectures that take into account the biosensing and data processing functions required in personal mobile health devices. We also discuss the path forward for integrating biosensors into smartphone-based mobile health devices.

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

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

The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study

Background

This study examines the development of the connected health (CH) research landscape with a view to providing an overview of the existing CH research. The research field of CH has experienced rapid growth coinciding with increasing pressure on health care systems to become more proactive and patient centered.

Objective

This study aimed to assess the extent and coverage of the current body of knowledge in CH. In doing so, we sought to identify specific topics that have drawn the attention of CH researchers and to identify research gaps, in particular those offering opportunities for further interdisciplinary research.

Methods

A systematic mapping study that combined scientific contributions from research in the disciplines of medicine, business, computer science, and engineering was used. Overall, seven classification criteria were used to analyze the papers, including publication source, publication year, research type, empirical type, contribution type, research topic, and the medical condition studied.

Results

The search resulted in 208 papers that were analyzed by a multidisciplinary group of researchers. The results indicated a slow start for CH research but showed a more recent steady upswing since 2013. The majority of papers proposed health care solutions (77/208, 37.0%) or evaluated CH approaches (49/208, 23.5%). Case studies (59/208, 28.3%) and experiments (55/208, 26.4%) were the most popular forms of scientific validation used. Diabetes, cancer, multiple sclerosis, and heart conditions were among the most prevalent medical conditions studied.

Conclusions

We conclude that CH research has become an established field of research that has grown over the last five years. The results of this study indicate a focus on technology-driven research with a strong contribution from medicine, whereas the business aspects of CH have received less research attention.

Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography

This study investigates the potential of the limb ballistocardiogram (BCG) for unobtrusive estimation of cardiovascular (CV) parameters. In conjunction with the reference CV parameters (including diastolic, pulse, and systolic pressures, stroke volume, cardiac output, and total peripheral resistance), an upper-limb BCG based on an accelerometer embedded in a wearable armband and a lower-limb BCG based on a strain gauge embedded in a weighing scale were instrumented simultaneously with a finger photoplethysmogram (PPG). To standardize the analysis, the more convenient yet unconventional armband BCG was transformed into the more conventional weighing scale BCG (called the synthetic weighing scale BCG) using a signal processing procedure. The characteristic features were extracted from these BCG and PPG waveforms in the form of wave-to-wave time intervals, wave amplitudes, and wave-to-wave amplitudes. Then, the relationship between the characteristic features associated with (i) the weighing scale BCG-PPG pair and (ii) the synthetic weighing scale BCG-PPG pair versus the CV parameters, was analyzed using the multivariate linear regression analysis. The results indicated that each of the CV parameters of interest may be accurately estimated by a combination of as few as two characteristic features in the upper-limb or lower-limb BCG, and also that the characteristic features recruited for the CV parameters were to a large extent relevant according to the physiological mechanism underlying the BCG.

Physiological Association between Limb Ballistocardiogram and Arterial Blood Pressure Waveforms: A Mathematical Model-Based Analysis

By virtue of its direct association with the cardiovascular (CV) functions and compatibility to unobtrusive measurement during daily activities, the limb ballistocardiogram (BCG) is receiving an increasing interest as a viable means for ultra-convenient CV health and disease monitoring. However, limited insights on its physical implications have hampered disciplined interpretation of the BCG and systematic development of the BCG-based approaches for CV health monitoring. In this study, a mathematical model that can predict the limb BCG in responses to the arterial blood pressure (BP) waves in the aorta was developed and experimentally validated. The validated mathematical model suggests that (i) the limb BCG waveform reveals the timings and amplitudes associated with the aortic BP waves; (ii) mechanical filtering exerted by the musculoskeletal properties of the body can obscure the manifestation of the arterial BP waves in the limb BCG; and (iii) the limb BCG exhibits meaningful morphological changes in response to the alterations in the CV risk predictors. The physical insights garnered by the analysis of the mathematical model may open up new opportunities toward next generation of the BCG-based CV healthcare techniques embedded with transparency, interpretability, and robustness against the external variability.

Mitigation of Instrument-Dependent Variability in Ballistocardiogram Morphology: Case Study on Force Plate and Customized Weighing Scale

The objective of this study was to investigate the measurement instrument-dependent variability in the morphology of the ballistocardiogram (BCG) waveform in human subjects and computational methods to mitigate the variability. The BCG was measured in 22 young healthy subjects using a high-performance force plate and a customized commercial weighing scale under upright standing posture. The timing and amplitude features associated with the major I, J, K waves in the BCG waveforms were extracted and quantitatively analyzed. The results indicated that 1) the I, J, K waves associated with the weighing scale BCG exhibited delay in the timings within the cardiac cycle relative to the ECG R wave as well as attenuation in the absolute amplitudes than the respective force plate counterparts, whereas 2) the time intervals between the I, J, K waves were comparable. Then, two alternative computational methods were conceived in an attempt to mitigate the discrepancy between force plate versus weighing-scale BCG: a transfer function and an amplitude-phase correction. The results suggested that both methods effectively mitigated the discrepancy in the timings and amplitudes associated with the I, J, K waves between the force plate and weighing-scale BCG. Hence, signal processing may serve as a viable solution to the mitigation of the instrument-induced morphological variability in the BCG, thereby facilitating the standardized analysis and interpretation of the timing and amplitude features in the BCG across wide-ranging measurement platforms.

The Clinical Significance and Application of Vascular Stiffness Measurements

Increasing evidence points out at vascular stiffness (and in particular aortic stiffness measured by pulse wave velocity) as a reliable biomarker of vascular aging, able to integrate in a single measure the overall burden of cardiovascular (CV) risk factors on the vasculature over time; furthermore, it may be per se a mechanism of disease, by inducing microcirculatory damage and favoring CV events. Increased aortic stiffness has been shown to predict future CV events and improve risk reclassification in those at intermediate risk. However, several questions in this field are still open, limiting the wide use of these tools in the clinical practice. This article will review the basic aspects of physiology of large artery stiffness, as well as current evidence about its possible clinical applications.

Advanced and Accurate Mobile Health Tracking Devices Record New Cardiac Vital Signs

Cardiovascular disease remains the leading cause of death and disease worldwide. As demands on an already resource-constrained healthcare system intensify, disease prevention in the future will likely depend on out-of-office monitoring of cardiovascular risk factors. Mobile health tracking devices that can track blood pressure and heart rate, in addition to new cardiac vital signs, such as physical activity level and pulse wave velocity (PWV), offer a promising solution. An initial barrier is the development of accurate and easily-scalable platforms. In this study, we made a customized smartphone app and used mobile health devices to track PWV, blood pressure, heart rate, physical activity, sleep duration, and multiple lifestyle risk factors in ≈250 adults for 17 continual weeks. Eligible participants were identified by a company database and then were consented and enrolled using only a smartphone app, without any special training given. Study participants reported high overall satisfaction, and 73% of participants were able to measure blood pressure and PWV, <1 hour apart, for at least 14 of 17 weeks. The study population's blood pressure, PWV, heart rate, activity levels, sleep duration, and the interrelationships among these measurements were found to closely match either population averages or values obtained from studies performed in a controlled setting. As a proof-of-concept, we demonstrated the accuracy and ease, as well as many challenges, of using mHealth technology to accurately track PWV and new cardiovascular vital signs at home.

Estimation of Cardiovascular Risk Predictors from Non-Invasively Measured Diametric Pulse Volume Waveforms via Multiple Measurement Information Fusion

This paper presents a novel multiple measurement information fusion approach to the estimation of cardiovascular risk predictors from non-invasive pulse volume waveforms measured at the body's diametric (arm and ankle) locations. Leveraging the fact that diametric pulse volume waveforms originate from the common central pulse waveform, the approach estimates cardiovascular risk predictors in three steps by: (1) deriving lumped-parameter models of the central-diametric arterial lines from diametric pulse volume waveforms, (2) estimating central blood pressure waveform by analyzing the diametric pulse volume waveforms using the derived arterial line models, and (3) estimating cardiovascular risk predictors (including central systolic and pulse pressures, pulse pressure amplification, and pulse transit time) from the arterial line models and central blood pressure waveform in conjunction with the diametric pulse volume waveforms. Experimental results obtained from 164 human subjects with a wide blood pressure range (systolic 144 mmHg and diastolic 103 mmHg) showed that the approach could estimate cardiovascular risk predictors accurately (r ≥ 0.78). Further analysis showed that the approach outperformed a generalized transfer function regardless of the degree of pulse pressure amplification. The approach may be integrated with already available medical devices to enable convenient out-of-clinic cardiovascular risk prediction.

Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform

In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.