Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare.

Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the "Smart Healthcare" era, a series of cutting-edge technologies has brought new experiences to the management of chronic diseases. Among them, smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state. However, how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management, in terms of quality of life, patient outcomes, and privacy protection, is an urgent issue that needs to be addressed. Artificial intelligence (AI) can provide intelligent suggestions by analyzing a patient's physiological data from wearable devices for the diagnosis and treatment of diseases. In addition, blockchain can improve healthcare services by authorizing decentralized data sharing, protecting the privacy of users, providing data empowerment, and ensuring the reliability of data management. Integrating AI, blockchain, and wearable technology could optimize the existing chronic disease management models, with a shift from a hospital-centered model to a patient-centered one. In this paper, we conceptually demonstrate a patient-centric technical framework based on AI, blockchain, and wearable technology and further explore the application of these integrated technologies in chronic disease management. Finally, the shortcomings of this new paradigm and future research directions are also discussed.

Child and adolescent asynchronous technology competencies for clinical care and training: Scoping review.

Objective: Asynchronous technologies such as mobile health, e-mail, e-consult, and social media are being added to in-person and synchronous service delivery. To ensure quality care, clinicians need skills, knowledge, and attitudes related to technology that can be measured. This study sought out competencies for asynchronous technologies and/or an approach to define them. Methods: This 6-stage scoping review of Pubmed/Medline, APA PsycNET, PsycINFO and other databases was based on a broad research question, "What skills are needed for clinicians and trainees to provide quality care using asynchronous technologies for children and adolescents, and how can they be made measurable to implement, teach and evaluate?" The search focused on key words in 4 concept areas: (a) competencies; (b) asynchronous technology; (c) synchronous telepsychiatry, telebehavioral or telemental health; and (d) clinical. The screeners reviewed the full-text articles based on inclusion (mesh of the key words) and exclusion criteria. Results: From a total of 5,877 potential references, 2 authors found 509 eligible for full text review and found 110 articles directly relevant to the concepts. Clinical studies discuss clinical, technical and administrative workflow rather than competencies, though behavioral health professions' position statements advise on adapting care and training. Existing technology competencies for video, social media, mobile health, and other asynchronous technologies were used to build a framework. Training, faculty development, and organizational suggestions are suggested. Conclusions: Research is needed on how to implement and evaluate asynchronous competencies to ensure quality clinical care and training, which is a paradigm shift for participants. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Current Evidence for Continuous Vital Signs Monitoring by Wearable Wireless Devices in Hospitalized Adults: Systematic Review.

BACKGROUND: Continuous monitoring of vital signs by using wearable wireless devices may allow for timely detection of clinical deterioration in patients in general wards in comparison to detection by standard intermittent vital signs measurements. A large number of studies on many different wearable devices have been reported in recent years, but a systematic review is not yet available to date. OBJECTIVE: The aim of this study was to provide a systematic review for health care professionals regarding the current evidence about the validation, feasibility, clinical outcomes, and costs of wearable wireless devices for continuous monitoring of vital signs. METHODS: A systematic and comprehensive search was performed using PubMed/MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 2009 to September 2019 for studies that evaluated wearable wireless devices for continuous monitoring of vital signs in adults. Outcomes were structured by validation, feasibility, clinical outcomes, and costs. Risk of bias was determined by using the Mixed Methods Appraisal Tool, quality assessment of diagnostic accuracy studies 2nd edition, or quality of health economic studies tool. RESULTS: In this review, 27 studies evaluating 13 different wearable wireless devices were included. These studies predominantly evaluated the validation or the feasibility outcomes of these devices. Only a few studies reported the clinical outcomes with these devices and they did not report a significantly better clinical outcome than the standard tools used for measuring vital signs. Cost outcomes were not reported in any study. The quality of the included studies was predominantly rated as low or moderate. CONCLUSIONS: Wearable wireless continuous monitoring devices are mostly still in the clinical validation and feasibility testing phases. To date, there are no high quality large well-controlled studies of wearable wireless devices available that show a significant clinical benefit or cost-effectiveness. Such studies are needed to help health care professionals and administrators in their decision making regarding implementation of these devices on a large scale in clinical practice or in-home monitoring.

Needs for aids and equipment for the management of epilepsy in an Australian cohort.

AIM: This paper investigated the bases of needs for a range of epilepsy aids and equipment and expressed concerns about the use of such devices. METHOD: There was a 29.6% response rate (n = 393 of 1328) to Wave 4 of the Australian Epilepsy Longitudinal Study (AELS). The focus of Wave 4 was on the expressed needs and affordability of aids and equipment for people with epilepsy (PWE) and quality of life (QoL). Quantitative analysis was used to examine the association between self-reported need for aids and equipment, sociodemographic information, and QoL. Open-ended responses were subject to qualitative analysis. RESULTS: Approximately one-fifth of the sample felt that they needed specific aids, including emergency ID bracelets, seizure alarms, and seizure monitors. Those respondents who felt that they needed aids had more frequent seizures, had been recently injured by a seizure, and were less prosperous. The QoL of those in need of equipment was lower than that of those who felt that they did not need it. Qualitative analysis revealed a need for more information about the aids available, issues associated with affordability, and some concern about the utility of these aids for those who lived alone. DISCUSSION: Much research to date has focussed on the development and validation of devices for PWE and standards for testing. Fewer studies deal with the needs and experiences of PWE with regard to the use of such equipment. The development of these devices needs to ensure patient comfort and acceptability. In addition, there is a need to canvas the views of family, caregivers, and primary care providers on the usability of epilepsy aids and equipment. CONCLUSION: Further person-centered research is needed in assessing the need for and usability of aids and equipment for the management of epilepsy.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications.

By providing blood glucose (BG) concentration measurements in an almost continuous-time fashion for several consecutive days, wearable minimally-invasive continuous glucose monitoring (CGM) sensors are revolutionizing diabetes management, and are becoming an increasingly adopted technology especially for diabetic individuals requiring insulin administrations. Indeed, by providing glucose real-time insights of BG dynamics and trend, and being equipped with visual and acoustic alarms for hypo- and hyperglycemia, CGM devices have been proved to improve safety and effectiveness of diabetes therapy, reduce hypoglycemia incidence and duration, and decrease glycemic variability. Furthermore, the real-time availability of BG values has been stimulating the realization of new tools to provide patients with decision support to improve insulin dosage tuning and infusion. The aim of this paper is to offer an overview of current literature and future possible developments regarding CGM technologies and applications. In particular, first, we outline the technological evolution of CGM devices through the last 20 years. Then, we discuss about the current use of CGM sensors from patients affected by diabetes, and, we report some works proving the beneficial impact provided by the adoption of CGM. Finally, we review some recent advanced applications for diabetes treatment based on CGM sensors.

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices.

BACKGROUND: With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable, and extensible platform is of high interest to the open source mHealth community. The European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field. OBJECTIVE: Wide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was to build a platform that would cater for large-scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security, and privacy. METHODS: RADAR-base is developed as a modular application; the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided. RESULTS: General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy, and Depression cohorts. CONCLUSIONS: RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.

Assessment of Physical Activity by Wearable Technology During Rehabilitation After Cardiac Surgery: Explorative Prospective Monocentric Observational Cohort Study.

BACKGROUND: Wearable technology is finding its way into clinical practice. Physical activity describes patients' functional status after cardiac surgery and can be monitored remotely by using dedicated trackers. OBJECTIVE: The aim of this study was to compare the progress of physical activity in cardiac rehabilitation by using wearable fitness trackers in patients undergoing coronary artery bypass surgery by either the conventional off-pump coronary artery bypass (OPCAB) or the robotically assisted minimally invasive coronary artery bypass (RA-MIDCAB). We hypothesized faster recovery of physical activity after RA-MIDCAB in the first weeks after discharge as compared to OPCAB. METHODS: Patients undergoing RA-MIDCAB or OPCAB were included in the study. Each patient received a Fitbit Charge HR (Fitbit Inc, San Francisco, CA) physical activity tracker following discharge. Rehabilitation progress was assessed by measuring the number of steps and physical activity level daily. The physical activity level was calculated as energy expenditure divided by the basic metabolic rate. RESULTS: A total of 10 RA-MIDCAB patients with a median age of 68 (min, 55; max, 83) years and 12 OPCAB patients with a median age of 69 (min, 50; max, 82) years were included. Baseline characteristics were comparable except for body mass index (RA-MIDCAB: 26 kg/m²; min, 22; max, 28 versus OPCAB: 29 kg/m²; min, 27; max, 33; P<.001). Intubation time (P<.05) was significantly lower in the RA-MIDCAB group. A clear trend, although not statistically significant, was observed towards a higher number of steps in RA-MIDCAB patients in the first week following discharge. CONCLUSIONS: RA-MIDCAB patients have an advantage in recovery in the first weeks of revalidation, which is reflected by the number of steps and physical activity level measured by the Fitbit Charge HR, as compared to OPCAB patients. However, unsupervised assessment of daily physical activity varied widely and could have consequences with regard to the use of these trackers as research tools.

Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol.

INTRODUCTION: Rapid advancements in technology and the ubiquity of personal mobile digital devices have brought forth innovative methods of acquiring healthcare data. Smartphones can capture vast amounts of data both passively through inbuilt sensors or connected devices and actively via user engagement. This scoping review aims to evaluate evidence to date on the use of passive digital sensing/phenotyping in assessment and prediction of mental health. METHODS AND ANALYSIS: The methodological framework proposed by Arksey and O'Malley will be used to conduct the review following the five-step process. A three-step search strategy will be used: (1) Initial limited search of online databases namely, MEDLINE for literature on digital phenotyping or sensing for key terms; (2) Comprehensive literature search using all identified keywords, across all relevant electronic databases: IEEE Xplore, MEDLINE, the Cochrane Database of Systematic Reviews, PubMed, the ACM Digital Library and Web of Science Core Collection (Science Citation Index Expanded and Social Sciences Citation Index), Scopus and (3) Snowballing approach using the reference and citing lists of all identified key conceptual papers and primary studies. Data will be charted and sorted using a thematic analysis approach. ETHICS AND DISSEMINATION: The findings from this systematic scoping review will be reported at scientific meetings and published in a peer-reviewed journal.

Technology-Enabled Assessment of Functional Health.

The maturation of pervasive computing technologies has dramatically altered the face of healthcare. With the introduction of mobile devices, body area networks, and embedded computing systems, care providers can use continuous, ecologically valid information to overcome geographic and temporal barriers and thus provide more effective and timely health assessments. In this paper, we review recent technological developments that can be harnessed to replicate, enhance, or create methods for assessment of functional performance. Enabling technologies in wearable sensors, ambient sensors, mobile technologies, and virtual reality make it possible to quantify real-time functional performance and changes in cognitive health. These technologies, their uses for functional health assessment, and their challenges for adoption are presented in this paper.

A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study.

BACKGROUND: Stair ascent is one of the most important and challenging activities of daily living to maintain mobility and independence in elderly adults. Recently, various types of wearable walking assist robots have been developed to improve gait function and metabolic efficiency for elderly adults. Several studies have shown that walking assist robots can improve cardiopulmonary metabolic efficiency during level walking in elderly. However, there is limited evidence demonstrating the effect of walking assist robots on cardiopulmonary metabolic efficiency during stair walking in elderly adults. Therefore, the aim of this study was to investigate the assistance effect of a newly developed wearable hip assist robot on cardiopulmonary metabolic efficiency during stair ascent in elderly adults. METHODS: Fifteen healthy elderly adults participated. The Gait Enhancing Mechatronic System (GEMS), developed by Samsung Electronics Co., Ltd., Korea, was used in the present study. The metabolic energy expenditure was measured using a K4b2 while participants performed randomly assigned two conditions consecutively: free ascending stairs without the GEMS or robot-assisted ascending stair with the GEMS. RESULTS: There were significant differences in the oxygen consumption per unit mass (ml/min/kg), metabolic power per unit mass (W/kg) and metabolic equivalents (METs) values between the GEMS and NoGEMS conditions. A statistically significant difference was found between the two conditions in net oxygen consumption and net metabolic power, with a reduction of 8.59% and 10.16% respectively in GEMS condition (p < 0.05). The gross oxygen consumption while climbing stairs under the GEMS and NoGEMS conditions was equivalent to 6.38 METs and 6.85 METs, respectively. CONCLUSION: This study demonstrated that the GEMS was helpful for reducing cardiopulmonary metabolic energy expenditure during stair climbing in elderly adults. The use of the GEMS allows elderly adults to climb stairs with less metabolic energy, therefore, they may experience more endurance in stair climbing while using the GEMS. TRIAL REGISTRATION: NCT03389165 , Registered 26 December 2017 - retrospectively registered.

Electronics and orthopaedic surgery.

Over the past few decades, sensors have been gaining a lot of popularity in the medical field. These sensors have helped shift the paradigm in medicine from having things done manually to digitalizing them. In the medical field, sensors have been manufactured in different forms and shapes including wearable and implantable wireless devices. With the aid of these sensors, healthcare professionals hope to revolutionize the system in a cost-effective way. In fact, this is already evident in most healthcare systems with the use of sensors for blood pressure, oxygen saturation, and arrhythmias on a daily basis. Also, more sophisticated sensors have made way into the medical field with a feedback loop, such as insulin pumps. On the other hand, similar technologies have been introduced in the orthopaedics world in the past decade. In this paper we summarize some of the sensors used in the medical field in general, and in orthopaedics in particular.