A Systematic Review of Wearable Patient Monitoring Systems --- Current Challenges and Opportunities for Clinical Adoption
TL;DR: The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings and to consider recent studies published between 2015 and 2017.
Abstract: The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and `silo' solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology.
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TL;DR: An all-inclusive review of the newly developed WFHE along with a summary of imperative requirements of material properties, sensor capabilities, electronics performance, and skin integrations is provided.
Abstract: Recent advances in soft materials and system integration technologies have provided a unique opportunity to design various types of wearable flexible hybrid electronics (WFHE) for advanced human healthcare and human-machine interfaces. The hybrid integration of soft and biocompatible materials with miniaturized wireless wearable systems is undoubtedly an attractive prospect in the sense that the successful device performance requires high degrees of mechanical flexibility, sensing capability, and user-friendly simplicity. Here, the most up-to-date materials, sensors, and system-packaging technologies to develop advanced WFHE are provided. Details of mechanical, electrical, physicochemical, and biocompatible properties are discussed with integrated sensor applications in healthcare, energy, and environment. In addition, limitations of the current materials are discussed, as well as key challenges and the future direction of WFHE. Collectively, an all-inclusive review of the newly developed WFHE along with a summary of imperative requirements of material properties, sensor capabilities, electronics performance, and skin integrations is provided.
554 citations
TL;DR: The landscape of wearable health technology and data integration to provider EHRs, specifically Epic, is reviewed to identify the current innovations and new directions in the field across start-ups, health systems, and insurance companies and understand the associated challenges to inform future Wearable health technology projects at other health organizations.
Abstract: Background:
Due to the adoption of electronic health records (EHRs) and legislation on meaningful use in recent decades, health systems are increasingly interdependent on EHR capabilities, offerings, and innovations to better capture patient data. A novel capability offered by health systems encompasses the integration between EHRs and wearable health technology. Although wearables have the potential to transform patient care, issues such as concerns with patient privacy, system interoperability, and patient data overload pose a challenge to the adoption of wearables by providers.
Methods:
We used a scoping process to survey existing efforts through Epic’s Web-based hub and discussion forum, UserWeb, and on the general Web, PubMed, and Google Scholar. We contacted Epic, because of their position as the largest commercial EHR system, for information on published client work in the integration of patient-collected data. Results from our searches had to meet criteria such as publication date and matching relevant search terms.
Results:
Numerous health institutions have started to integrate device data into patient portals. We identified the following 10 start-up organizations that have developed, or are in the process of developing, technology to enhance wearable health technology and enable EHR integration for health systems: Overlap, Royal Philips, Vivify Health, Validic, Doximity Dialer, Xealth, Redox, Conversa, Human API, and Glooko. We reported sample start-up partnerships with a total of 16 health systems in addressing challenges of the meaningful use of device data and streamlining provider workflows. We also found 4 insurance companies that encourage the growth and uptake of wearables through health tracking and incentive programs: Oscar Health, United Healthcare, Humana, and John Hancock.
Conclusions:
The future design and development of digital technology in this space will rely on continued analysis of best practices, pain points, and potential solutions to mitigate existing challenges. Although this study does not provide a full comprehensive catalog of all wearable health technology initiatives, it is representative of trends and implications for the integration of patient data into the EHR. Our work serves as an initial foundation to provide resources on implementation and workflows around wearable health technology for organizations across the health care industry.
161 citations
Cites background from "A Systematic Review of Wearable Pat..."
...Although machine learning and artificial intelligence (AI) algorithms are potential solutions to this issue, current algorithms are often tested in fixed conditions that are not likely to hold up in live scenarios [35]....
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...Wearable health technology requires critical checkpoints along the workflow to protect the confidentiality and privacy of patients [35]....
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TL;DR: This article presents an introduction to, and a systematic review of, current ML work regarding psycho-socially based mental health conditions from the computing and HCI literature, and reflects on the current state-of-the-art of ML work for mental health.
Abstract: High prevalence of mental illness and the need for effective mental health care, combined with recent advances in AI, has led to an increase in explorations of how the field of machine learning (ML) can assist in the detection, diagnosis and treatment of mental health problems. ML techniques can potentially offer new routes for learning patterns of human behavior; identifying mental health symptoms and risk factors; developing predictions about disease progression; and personalizing and optimizing therapies. Despite the potential opportunities for using ML within mental health, this is an emerging research area, and the development of effective ML-enabled applications that are implementable in practice is bound up with an array of complex, interwoven challenges. Aiming to guide future research and identify new directions for advancing development in this important domain, this article presents an introduction to, and a systematic review of, current ML work regarding psycho-socially based mental health conditions from the computing and HCI literature. A quantitative synthesis and qualitative narrative review of 54 papers that were included in the analysis surfaced common trends, gaps, and challenges in this space. Discussing our findings, we (i) reflect on the current state-of-the-art of ML work for mental health, (ii) provide concrete suggestions for a stronger integration of human-centered and multi-disciplinary approaches in research and development, and (iii) invite more consideration of the potentially far-reaching personal, social, and ethical implications that ML models and interventions can have, if they are to find widespread, successful adoption in real-world mental health contexts.
153 citations
Cites background from "A Systematic Review of Wearable Pat..."
...Further excluded were papers that described ML research outside a specific focus on mental health (n = 16 [21, 26, 32, 43, 75, 81, 88, 114, 118, 120, 160, 167, 200, 208, 215, 221]); or that otherwise did not fit thematically (n = 20 [11, 14, 18, 29, 30, 36, 55, 87, 101, 107, 110, 113, 138, 143, 147, 174, 178, 194, 197, 198])....
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TL;DR: An assessment of the maturity of the field and successful examples of recent clinical experiments is provided, including key elements of analytical and clinical validation in the specific context of use (COU).
Abstract: The development of innovative wearable technologies has raised great interest in new means of data collection in healthcare and biopharmaceutical research and development. Multiple applications for wearables have been identified in a number of therapeutic areas; however, researchers face many challenges in the clinic, including scientific methodology as well as regulatory, legal, and operational hurdles. To facilitate further evaluation and adoption of these technologies, we highlight methodological and logistical considerations for implementation in clinical trials, including key elements of analytical and clinical validation in the specific context of use (COU). Additionally, we provide an assessment of the maturity of the field and successful examples of recent clinical experiments.
144 citations
TL;DR: A generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG Monitoring systems’ value chain is conducted, and a thorough review of the relevant literature, classified against the experts’ taxonomy, is presented, highlighting challenges and current trends.
Abstract: Health monitoring and its related technologies is an attractive research area. The electrocardiogram (ECG) has always been a popular measurement scheme to assess and diagnose cardiovascular diseases (CVDs). The number of ECG monitoring systems in the literature is expanding exponentially. Hence, it is very hard for researchers and healthcare experts to choose, compare, and evaluate systems that serve their needs and fulfill the monitoring requirements. This accentuates the need for a verified reference guiding the design, classification, and analysis of ECG monitoring systems, serving both researchers and professionals in the field. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. This provides evidence-based support for critically understanding ECG monitoring systems’ components, contexts, features, and challenges. Hence, a generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG monitoring systems’ value chain is conducted, and a thorough review of the relevant literature, classified against the experts’ taxonomy, is presented, highlighting challenges and current trends. Finally, we identify key challenges and emphasize the importance of smart monitoring systems that leverage new technologies, including deep learning, artificial intelligence (AI), Big Data and Internet of Things (IoT), to provide efficient, cost-aware, and fully connected monitoring systems.
139 citations
Cites background from "A Systematic Review of Wearable Pat..."
...[54] highlighted a few system integration challenges that face the existing clinical decision support models concerning scalability and reliability, pointing this out as a future research direction....
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...[58] 3 3 3 3 3 [42–45,61–63] 3 3 [64] 3 [46,47,65–67] 3 3 3 [68] 3 3 3 [62] 3 3 3 3 [69] 3 3 3 [70] 3 3 3 [12] 3 3 [13] 3 3 3 3 [71] 3 3 3 3 [72] 3 3 3 3 3 [73,74] 3 3 3 3 [61] 3 3 [75] 3 3 3 3 3 3 [76] 3 3 3 3 [77] 3 3 3 3 [55] 3 3 3 3 3 [54] 3 3 3 3 3 [49] 3 3 3 3 [78] 3 3 3 3 3 [79] 3 3 3 3 [80–82] 3 [83] 3 3 3 3 3 3 [84,85] 3 3 3 3 [86,87] 3 3 3 3 [88] 3 3 3 3...
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References
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TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
62,157 citations
Journal Article•
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews.
Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7
In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1).
Box 1
Conceptual issues in the evolution from QUOROM to PRISMA
46,935 citations
01 Jan 2010
TL;DR: A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions and evaluate the maturity level of the top current achievements in wearable health-monitoring systems.
Abstract: The design and development of wearable biosensor systems for health monitoring has garnered lots of attention in the scientific community and the industry during the last years. Mainly motivated by increasing healthcare costs and propelled by recent technological advances in miniature biosensing devices, smart textiles, microelectronics, and wireless communications, the continuous advance of wearable sensor-based systems will potentially transform the future of healthcare by enabling proactive personal health management and ubiquitous monitoring of a patient's health condition. These systems can comprise various types of small physiological sensors, transmission modules and processing capabilities, and can thus facilitate low-cost wearable unobtrusive solutions for continuous all-day and any-place health, mental and activity status monitoring. This paper attempts to comprehensively review the current research and development on wearable biosensor systems for health monitoring. A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions. An emphasis is given to multiparameter physiological sensing system designs, providing reliable vital signs measurements and incorporating real-time decision support for early detection of symptoms or context awareness. In order to evaluate the maturity level of the top current achievements in wearable health-monitoring systems, a set of significant features, that best describe the functionality and the characteristics of the systems, has been selected to derive a thorough study. The aim of this survey is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.
2,051 citations
"A Systematic Review of Wearable Pat..." refers methods in this paper
...4-capable nodes interfaced with electrocardiogram (ECG) and blood pressure sensors, as well as a basic cell phone device for data display and signal feature extraction [6]; (3) the Human++ project in the Netherlands which developed a body area network consisting of three sensor nodes and a base station [7]; (4) the CodeBlue project developed by researchers at Harvard University [8]; (5) research from the Media Laboratory of the Massachusetts Institute of Technology (MIT) which involved designing LiveNet [9]; (6) the development of the SmartVest, a wearable physiological monitoring system that consists of a vest and a variety of sensors integrated into the garment’s fabric to collect several biosignals [10]; (7–9) and three European IST FP6 programs (the MERMOTH, MyHeart and HeartCycle projects), which are recent examples of WPM systems [11–14]....
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TL;DR: In this paper, a review of wearable sensors and systems that are relevant to the field of rehabilitation is presented, focusing on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders.
Abstract: The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.
1,826 citations