Connected Health And Telemedicine

Aim: The objective of this systematic review and meta-analysis was to determine the diagnostic and prognostic utility of artificial intelligence/machine learning (AI/ML) algorithms in Brugada Syndrome (BrS). Methods: A systematic review and meta-analysis of the literature was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, EMBASE, SCOPUS, and WEB OF SCIENCE databases were searched for relevant articles. Abstract and title screening, full-text review, and data extraction were conducted independently by two of the authors. Conflicts were resolved via discussion among authors. A risk-of-bias assessment was performed using the QUADAS-2 tool for diagnostic studies and the PROBAST tool for prognostic studies. Forest plots and the summary area under the receiver operating characteristic (SAUROC) curve were done in R. Results: A total of 12 papers were included in our study. Among the best-performing diagnostic algorithms from each study, the sensitivity and specificity ranged from 0.80 to 0.89 and 0.74 to 0.97, respectively. In overall studies, sensitivity was 0.845 ± 0.014 and specificity was 0.892 ± 0.062 using a random effects model. A pooled analysis of the summary area under the receiver operating characteristic curve (SAUROC) was 0.77 for diagnostic studies. Prognostic studies showed good performance as well, with the AUC of the best-performing prognostic algorithms ranging from 0.71 to 0.90. Conclusions: Overall, AI/ML algorithms had high diagnostic and prognostic accuracy. These results highlight the potential of AI/ML algorithms for the diagnosis and prognosis of BrS and permit a choice of the best-performing ML algorithms. Keywords Brugada syndrome, artificial intelligence, machine learning, diagnostic criteria, prognosis

Aim: Data harmonization standardizes healthcare information, enhancing accessibility and interoperability, which is crucial for improving patient outcomes and driving medical research and innovation. It enables precise diagnoses and personalized treatments, and boosts AI model efficiency. However, significant challenges such as ethical concerns, technical barriers in the data lifecycle, AI biases, and varied regional regulations impede progress, underscoring the need for solutions like adopting universal standards such as HL7 FHIR, where the lack of generalized harmonization efforts is significant. Methods: We propose an advanced, holistic framework that utilizes FAIR-compliant reference ontologies (based on the FAIRplus and FAIR CookBook criteria) to make data findable, accessible, interoperable, and reusable enriched with terminologies from OHDSI (Observational Health Data Sciences and Informatics) vocabularies and word embeddings to identify lexical and conceptual overlaps across heterogeneous data models. Results: The proposed approach was applied to autoimmune diseases, cardiovascular diseases, and mental disorders using unstructured data from EU cohorts involving 7,551 patients with primary Sjogren’s Syndrome, 25,000 patients with cardiovascular diseases, and 3,500 patients with depression and anxiety. Metadata from these datasets were structured into dictionaries and linked with three newly developed reference ontologies (ROPSS, ROCVD, and ROMD), which are accessible on GitHub. These ontologies facilitated data interoperability across different systems and helped identify common terminologies with high precision within each domain. Conclusion: Through the proposed framework, we aim to urge the adoption of data harmonization as a priority, emphasizing the need for global cooperation, investment in technology and infrastructure, and adherence to ethical data usage practices toward a more efficient and patient-centered global healthcare system.

Aim: We propose to examine the causal relationship between the noninvasive features represented by pulse transit time (PTT) and blood pressure (BP), with the aim of mitigating the impact of confounding factor(s) and thus improving the performance of BP estimation. Methods: We identified the causal graph of BP and the important noninvasive features extracted from electrocardiogram (ECG) and photoplethysmogram (PPG) via fast causal inference (FCI) algorithm, with the orientations of the edges in the causal graph being determined by the causal generative neural networks (CGNN) algorithm. With the knowledge obtained from the causal graph, we further used hierarchical regression model to estimate BP, and validated the proposed method on 17 subjects. Results: We found that the obtained causal graph was almost consistent with the prior knowledge, and heart rate (HR) was one of the main confounding factors of PTT and BP. Incorporating HR into the hierarchical regression model to eliminate its confounding effect on the PTT-based BP estimation, the mean value of SBP and DBP estimation was improved by 1.27 and 1.89 mmHg, respectively, and the mean absolute difference (MAD) was improved by 2.28 and 3.60 mmHg, respectively. Conclusion: Causal inference-based method has the potential to clarify the causal relationship between BP and related wearable noninvasive features, which can further shed light on developing new methods for cuffless BP with acceptable accuracy.

Objective: This study aims to evaluate the effectiveness of deep learning techniques in estimating cuffless blood pressure (BP) across a diverse patient population in intensive care units (ICUs). Methods: A comprehensive ICU benchmarking dataset encompassing 2,154 patients with a wide demographic range (18-97 years old) and varied cardiovascular status was employed to validate several deep learning models in predicting continuous BP waveforms. Three methods were developed to enhance the model's generalizability to this heterogeneous dataset. Ten-fold subject-independent cross-validation was performed and the model performance was assessed through mean absolute error (MAE), Pearson’s correlation coefficient (PCC), and compared with significance analysis. Results: The UTransBPNet_Demo_In model, which incorporated demographic and physiological signals as inputs, achieved a PCC of 0.89 and a MAE of 10.38 mmHg in predicting arterial BP waveforms, demonstrating the highest tracking capability among all models. Notably, the performance of UTransBPNet_Demo_In remained robust across variations in demographic and cardiovascular status. Conclusion: The UTransBPNet_Demo_In model demonstrates robust predictive capabilities across a broad spectrum of demographics and cardiovascular conditions. Although the performance still needs further improvement, this study offers a benchmark in the field of cuffless BP monitoring in critical care settings for future studies.

Aim: Photoplethysmography (PPG) has gained widespread popularity as a non-invasive method for potential cuff-less blood pressure (BP) measurement in smart devices. However, the accuracy of PPG-based devices is often hindered by motion artifacts, site variability, and inconsistent contact force (CF). This study aims to investigate the influence of CF variations on PPG signals. Methods: To address these challenges, we present a novel approach involving a multi-channel PPG array integrated with CF regulation in the form of a wearable wristband. This platform enables the visualization of regional PPG/BP distribution while simultaneously monitoring CF. Moreover, our research explored the relationship between PPG waveform characteristics and CF during wrist extension. Results: The results of this study reveal that the PPG amplitude (PPGA) and the b/a ratios, computed from the second derivative peaks of the PPG AC pulse wave, exhibit inconsistency in reaction to CF variations. Notably, a shape correlation coefficient of 0.65069 between normalized PPG and flipped CF sheds light on how changes in posture affect PPG measurements. Conclusions: The proposed platform shows promise in mitigating the effects of CF and spatial positioning on PPG, thereby improving measurement precision and offering a novel approach to image tonoarteriographic (TAG) activities for continuous hypertension management.

Hypertension is a major public health problem, accounting for 7.5 million deaths and 57 million disability-adjusted life years annually worldwide. The majority of hypertension-related deaths occur in low- and middle-income countries (LMICs). Despite the escalating prevalence of hypertension in many LMICs, only one-third of those affected are aware of their hypertension status. The rapid proliferation of eHealth technologies presents an opportunity to improve the detection and management of hypertension. Many LMICs face a critical shortage of physicians, and their services often come at a considerable cost to the health system. Non-physician health workers could be a cost-effective alternative to improve the detection and management of hypertension, particularly in LMICs. In this systematic review, we aim to synthesize and evaluate the effectiveness of interventions that integrated eHealth technologies with non-physician health workers to reduce blood pressure. A diverse range of eHealth technologies, such as mobile-based applications, telemonitoring, short text messaging and electronic decision support systems, are being used by non-physician health workers for the management of hypertension. We found that eHealth technologies integrated with non-physician health workers reduced overall mean systolic blood pressure by -4.09 mmHg (95%CI: -5.87 to -2.32) compared to usual care. Similarly, such an integrated approach also reduced diastolic blood pressure by -1.25 mmHg (-2.31 to -0.81) in the intervention group than usual care. Therefore, leveraging the use of cost-effective eHealth technologies to support task-sharing with non-physicians presents an effective strategy for enhancing blood pressure management, applicable to both high- and low-income countries.

Digital health interventions for managing Non-Communicable Diseases, specifically cardiovascular diseases, are gaining momentum in Low-Middle-Income countries (LMICs), notably in the South-East Asia region. The effective implementation of these interventions hinges on their ability to effectively cater to user needs within the healthcare system. Our objective is to examine the usage of digital health approaches or modalities. A scoping review was conducted using PUBMED and SCOPUS databases, and the findings were synthesized narratively using the WHO’s Digital Health Intervention (DHI) framework. The initial search yielded 1,505 articles, of which 51 met our inclusion criteria. In terms of the target users for digital health applications, providers remain the major focus, while other stakeholders such as data managers and health system managers remain neglected. Even within “provider-focused” applications, telemedicine dominates in the functionality aspect. Further, few applications addressed client issues such as client-to-client communication, personal health tracking, and the client’s financial transactions. Few applications address the needs of data managers and health system managers. Moving forward, member countries in South-East Asia would benefit from digital health applications that specifically target data services and health system managers. For clients, functionalities such as personal health tracking, active data capture, citizen-based reporting, on-demand information services, and peer groups are required. For healthcare providers, features such as access to longitudinal client health records, decision support systems, referral coordination, prescription, and medication management, as well as laboratory and diagnostic imaging management, should be seamlessly integrated into existing digital health applications.

Aim: The DICAP feasibility study aims to determine chronological blood pressure (BP) control status and BP variability up to the end of life in different life settings in the community and their clinical implications. Methods: A simple, easy-to-use automated hybrid BP telemonitoring system combined cellular and Bluetooth BP monitors, the DICAP (DIgital Cardiovascular Prevention) system, was devised to obtain all the different BP values measured in a time series in different settings in 500 community-dwelling individuals in their homes and local elderly care facilities. Expected results and Perspectives: This study will confirm the feasibility of collecting BP variability over time until the end of life for the management of hypertension in all community-dwelling patients, including those unfamiliar with digital technology and those in diverse residential settings, such as elderly care facilities. This feasibility study has the potential to serve as a basis for future community and disaster medicine initiatives worldwide.

Electrooculography-based Human-Computer Interaction (EOG-HCI) is an emerging field. Research in this domain aims to capture eye movement patterns by measuring the corneal-retinal potential difference. This enables translating eye movements into commands, facilitating human-computer interaction through eye movements. This paper reviews articles published from 2002 to 2022 in the EOG-HCI domain, aiming to provide a comprehensive analysis of the current developments and challenges in this field. It includes a detailed and systematic analysis of EOG signal electrode arrangement, hardware design for EOG signal acquisition, commonly used features, and algorithms. Representative studies in each section are presented to help readers quickly grasp the common technologies in this field. Furthermore, the paper emphasizes the analysis of interaction design within the EOG-HCI domain, categorizing different interaction task types and modalities to provide insights into prevalent interaction research. The focus of current research in the field is revealed by examining commonly used evaluation metrics. Lastly, a user-centered EOG-HCI research model is proposed to visually present the current research status in the EOG-HCI field from the perspective of users. Additionally, we highlight the challenges and opportunities in this field.

The measurement and monitoring of continuous arterial blood pressure (BP) have undergone significant evolution over the past 170 years, transitioning from ancient invasive approaches, like kymograph, to modern non-invasive and unobtrusive technologies such as tonoarteriography (TAG). This progressive shift has revolutionized the way we track BP, providing safer, more accurate, and convenient methods for monitoring BP. This paper aims to provide some historical perspectives on the development of continuous BP technology, highlight key milestones that have shaped the field, discuss the state-of-the-art two-dimensional TAG imaging, and address challenges for future unobtrusive BP measurements. In addition to presenting a concise review of the progression of continuous BP measurement technologies, this article also emphasizes the importance of adopting more precise, convenient and affordable approaches for personalized BP monitoring at home and patient care optimizations at hospitals, thereby empowering healthcare professionals to enhance pervasive hypertension management anywhere.

During the past three years, tremendous efforts have been made to tackle the Coronavirus Disease 2019 (COVID-19) crisis, including centralized quarantine, compulsory testing, and sweeping lockdowns. The measures have taken effect, but have caused a huge burden on healthcare systems and significant disruption to global economies on an unprecedented scale. Recently, some countries and regions have observed signs of the pandemic resurgence. To better handle the resurgence in the post-COVID era and future pandemics, an immediate revolution of the precise and rapid responding system capable of early detection is needed. Based on a comprehensive review, this article summarizes the enabling wearable devices in physiological monitoring and biomolecular diagnosis, highlights their potential contributions to the detection and management of COVID-19, as well as its long-term effects, and suggests a wearable sensing-based system to avoid future pandemics. Wearable devices, in conjunction with mobile health (mHealth) technologies, provide a novel way to track and monitor diseases through continuous physiological, physical, and biomolecular sensing. Augmented by artificial intelligence (AI), especially the emerging Generative Pre-trained Transformer (GPT) algorithms, patients could potentially be identified before they become symptomatic. By combining contact tracing and effective quarantine, it is possible to arrest the spread of the disease and control its emergence at an early stage. Furthermore, with minor refinements, the proposed response system holds the potential for extended use beyond COVID-19, particularly in addressing cardiovascular diseases (CVDs) during both outbreaks and non-pandemic scenarios. By implementing this groundbreaking approach, there exist valuable prospects to transform the current healthcare paradigm and drive significant advancements in disease prevention, detection, and management.

Aim: Financial incentives improve response to electronic health surveys, yet little is known about how unconditional incentives (guaranteed regardless of survey completion), conditional incentives, and various combinations of incentives influence response rates. We compared electronic health survey completion with two different financial incentive structures. Methods: We invited women aged 30-64 years enrolled in a U.S. healthcare system and overdue for Pap screening to complete a web-based survey after receiving a mailed human papillomavirus (HPV) self-sampling kit in a pragmatic trial. HPV kit returners (n = 272) and non-returners (n = 1,083) were allocated to one of two different incentive structures: (1) Unconditional: $5 pre-incentive only (n = 653); (2) Combined:$2 pre-incentive plus $10 post-incentive conditional on completion (n = 702). Chi-square tests evaluated whether survey completion differed by incentive structure within kit return groups or was modified by kit return status. For each incentive-by-kit status group, the cost-per-survey response was calculated as: ([number invited*pre-incentive amount] + [number responses*post-incentive amount]) / number responses. Results: Overall, survey response was higher in kit returners vs. kit non-returners (42.6$13.57 unconditional; $14.15 combined); among non-returners, the cost was greater in the unconditional ($57.78) versus the combined ($25.22) group. Conclusion: A combined incentive can be cost-effective for increasing survey response in health services research, particularly in hard-to-reach populations.

Telehealth has seen rapid adoption in the past three years as a direct result of the COVID-19 pandemic. Conventional methods for the measurement of vital signs are neither optimized for remote care nor highly scalable. Blood pressure is a critical vital parameter that currently cannot be measured remotely. Cameras are versatile and capable sensors that can be repurposed to measure vital signs. In this article, we review the use of cameras for remote photoplethysmography and assessment of blood pressure. We discuss the principles behind this technology and the current evidence for blood pressure measurement. We also explore future applications and potential challenges to provide a roadmap for researchers, clinicians, and regulators considering this new technology.

Office blood pressure measurement has been the primary means of diagnosing and treating hypertension for almost a century. Increasingly, guidelines recommend out-of-office measurements (ambulatory or home blood pressure measurement) to confirm the diagnosis of hypertension and to follow treated patients. Ambulatory blood pressure measurement includes nocturnal measurement and provides a 24-hour blood pressure profile, enabling calculation of overall blood pressure, daytime mean, and nocturnal mean. Home blood pressure monitoring is a method of blood pressure measurement that is convenient and accessible. Blood pressure telemonitoring is a complementary and emerging technology that enhances the effectiveness of out-of-office blood pressure measurement and has the potential to improve the health of end users through engagement, efficiency, and enhanced communication with the care team. Blood pressure measurements can be obtained remotely, effectively transmitted to their health care team via telemonitoring for interpretation, and then a care plan can be developed and implemented. However, care must be taken to ensure that these emerging technologies record and transmit accurate blood pressure information in a secure and reliable manner.

There is a rising problem of multiple long-term conditions (“multimorbidity”) as the global population ages. Old age is the biggest risk factor for having one or more chronic conditions. Unfortunately, current care processes can be fragmented, with most focusing on individual diseases. This can lead to unintended consequences for patients, particularly if they are admitted onto an inappropriate care pathway, along with subsequent economic downsides. When people with multiple long-term conditions deteriorate, detection of illness may be delayed due to a range of non-specific symptoms being displayed. At present, there is limited research on detecting deterioration within community settings, thereby forming the basis of earlier interventions. A general measure, such as how active an individual is, might allow initial identification of decline and trigger a more targeted approach to assess the underlying reason for deterioration. Restricted activity seems to manifest earlier than the routinely used single condition clinical markers, and has been identified both in the last year of life and during periods of illness. Changes in activity could facilitate the identification of illness, leveraging technology to determine any decline. However, there is still no universally agreed definition of what constitutes a change in activity and, therefore, no accepted method of measuring it. This paper reviews the potential for a connected health approach to monitoring older adults with multimorbidity, using restricted activity as a general measure of health decline.

Aim: The aims of this study were to (i) understand what adolescents (and their parents) identify as positive and negative experiences with technology for engaging in physical activity (PA) when living with type 1 diabetes (T1D) and (ii) identify possible future design considerations for supporting or enabling technologies for this population. Methods: Nine online collaborative workshops (n = 25 people) were held over a month with participants who were either adolescents attending with (n = 22) or without (n = 3, aged 16 and over) parents. Each workshop involved (1) a training activity, (2) a design task involving describing a good day vs. a bad day, and (3) a design task asking people to consider future design changes for technology to support them in engaging with physical activity. Results: The following key themes emerged from the first design task: (1) Wearable factors; (2) Social acceptance & identity; (3) Negative emotions; (4) Glycaemic stability offers positive emotions and PA Enjoyment; and (5) Presence, preparation & prevention. The second design task identified the following additional key themes: (6) Improve attachment experiences; (7) Connected devices reduce user burden; (8) Improve accuracy; (9) Personalisation of devices; (10) Funding and policy changes – health equity. Conclusion: Technology can reduce the burden and improve PA support, but there are still gaps in how these technologies can be better designed to consider the psychosocial and emotional factors of both adolescents and their parents as co-users.

Hypertension is a major cause of cardiovascular disease worldwide and a major cause of morbidity and mortality in patients with chronic kidney disease (CKD). The Systolic Blood pressure Intervention Trial (SPRINT) demonstrated that blood pressure (BP) measurement techniques may have an impact on the achievement of outcomes. Home BP monitoring (HBPM) has several advantages over office BP recordings, including avoidance of white-coat reaction, ability to diagnose white-coat and masked hypertension, detection of BP variability, and better ability to predict cardiovascular morbidity and mortality, all of which commonly occur in CKD. The addition of telemonitoring and management support to HBPM allows remote monitoring, especially when close contact is difficult (e.g., patients in remote/rural areas, pandemic, natural disaster, or patients treated with home dialysis). Although there are few studies that have assessed the efficacy of home BP telemonitoring (HBPT) in patients with CKD, these studies suggest the benefits of HBPT for BP control and even limited evidence that it may improve kidney function. This review, using limited available evidence, assesses the roles of HBPT in patients with CKD, barriers to HBPT implementation in the care of patients with CKD, and discusses newer technologies that can be leveraged in the management of hypertension in patients with CKD.

Hypertension is the leading contributor to cardiovascular disease (CVD)-related deaths globally, with Africa being one of the World Health Organization regions with the highest prevalence of elevated blood pressure (BP). In sub-Saharan Africa (SSA), awareness, treatment, and control levels of hypertension remain low in both men and women and in different settings, including rural and urban areas. Important barriers to the management of hypertension in SSA are within health systems, usually overburdened by communicable and non-communicable diseases, acute medical conditions, and child and maternal healthcare. Health system-related challenges include the availability and cost of essential medicines and healthcare workforce constraints. At the patient level, individual barriers such as sociodemographic, economic, and psychosocial factors contribute significantly to the poor control of hypertension. Telemedicine presents a promising approach to improve the delivery of optimal care for individuals living with hypertension by serving as a connection between healthcare providers and patients. This may enhance access to isolated people living with hypertension, such as in rural areas. However, there is a concern that telemedicine may exacerbate some of the barriers to the management of hypertension in disadvantaged groups, such as those with limited access to digital technology, low education and literacy levels, and the ageing population. Therefore, the objective of this review is to summarize the current state of telemedicine use in the management of hypertension in SSA and discuss the challenges and opportunities to provide cost-effective, equitable, and sustainable access to digital health technology for people living with hypertension in SSA.

How to cite this article: Bhandari B, Neupane D, Thapa P, Pradhan PMS. Use of mHealth for management of hypertension in low and middle-income countries: opportunities and challenges. Conn Health 2023;2:1-8. https://dx. Abstract Despite being the leading cause of global mortality, the hypertension control rate is astonishingly low, particularly in low-and middle-income countries. There is evidence that the mHealth approach is a potential platform for delivering interventions for hypertension management. Our recent study from Nepal also provided strong evidence for reducing blood pressure, improving control rate, and medication adherence. The objective of this paper is to document the real-world experience of designing and implementing a mHealth project in Nepal and relates them with the evidence from other similar Low-and Middle-Income Country (LMIC) settings. We learned that mHealth provides a unique opportunity to bridge the gap between providers and patients, send health education and reminder messages, secure patients' privacy, and make data management easier. We also encountered technological and financial barriers, unclear mHealth policy and guidelines, and low literacy levels, including digital literacy. As many of them are addressable, integrating mHealth provides a promising approach to hypertension management.

Telehealth has seen rapid adoption in the past three years as a direct result of the COVID-19 pandemic. Conventional methods for the measurement of vital signs are neither optimized for remote care nor highly scalable. Blood pressure is a critical vital parameter that currently cannot be measured remotely. Cameras are versatile and capable sensors that can be repurposed to measure vital signs. In this article, we review the use of cameras for remote photoplethysmography and assessment of blood pressure. We discuss the principles behind this technology and the current evidence for blood pressure measurement. We also explore future applications and potential challenges to provide a roadmap for researchers, clinicians, and regulators considering this new technology.

In just over a half-century since the initiation of telemedicine, technological developments have created multiple options to shape how patients can access healthcare and interact with healthcare providers to better prevent and manage hypertension. In several high-income countries, patients are connecting to their healthcare providers online to book appointments, request prescriptions, see test results and engage in pro-active health management. Mounting evidence suggests that telemedicine and mobile health (mHealth) services can yield greater reductions in blood pressure when compared with usual care while also offering greater reach, efficiency, and potential cost-saving. A deeper examination of implementing such systems at scale in high-income countries shows varying approaches and levels of success. While research investigating the benefits of technology for blood pressure control in low- and middle-income countries is growing, in regions such as sub-Saharan Africa, economic and digital divides present major challenges to scaling such technology. Substantial national investments in infrastructure and skills development are needed alongside consultation with multiple stakeholders to ensure that technological advancements do not further drive health disparities in the region.