The Internet of Things: Impact and Implications for Health Care Delivery

Flexible triboelectric nanogenerators of Au-g-C3N4/ZnO hierarchical nanostructures for machine learning enabled body movement detection

Here we report the development of triboelectric nanogenerator (TENG) based self-powered human motion detector with chemically developed Au-g-C3N4/ZnO based nanocomposite on common cellulose paper platform. Compared to bare g-C3N4, the nanocomposite in the form of hierarchical morphology is found to exhibit higher output voltage owing to the contribution of Au and ZnO in increasing the dielectric constant and surface roughness. While generating power ∼3.5μW cm-2and sensitivity ∼3.3 V N-1, the flexible TENG, is also functional under common biomechanical stimuli to operate as human body movement sensor. When attached to human body, the flexible TENG is found to be sensitive towards body movement as well as the frequency of movement. Finally upon attaching multiple TENG devices to human body, the nature of body movement has been traced precisely using machine learning (ML) techniques. The execution of the learning algorithms like artificial neural network and random forest classifier on the data generated from these multiple sensors can yield an accuracy of 99% and 100% respectively to predict body movement with great deal of precision. The exhibition of superior sensitivity and ML based biomechanical motion recognition accuracy by the hierarchical structure based flexible TENG sensor are the prime novelties of the work.

Intelligent Digital Twins for Personalized Migraine Care

Intelligent digital twins closely resemble their real-life counterparts. In health and medical care, they enable the real-time monitoring of patients, whereby large amounts of data can be collected to produce actionable information. These powerful tools are constructed with the aid of artificial intelligence, machine learning, and deep learning; the Internet of Things; and cloud computing to collect a diverse range of digital data (e.g., from digital patient journals, wearable sensors, and digitized monitoring equipment or processes), which can provide information on the health conditions and therapeutic responses of their physical twins. Intelligent digital twins can enable data-driven clinical decision making and advance the realization of personalized care. Migraines are a highly prevalent and complex neurological disorder affecting people of all ages, genders, and geographical locations. It is ranked among the top disabling diseases, with substantial negative personal and societal impacts, but the current treatment strategies are suboptimal. Personalized care for migraines has been suggested to optimize their treatment. The implementation of intelligent digital twins for migraine care can theoretically be beneficial in supporting patient-centric care management. It is also expected that the implementation of intelligent digital twins will reduce costs in the long run and enhance treatment effectiveness. This study briefly reviews the concept of digital twins and the available literature on digital twins for health disorders such as neurological diseases. Based on these, the potential construction and utility of digital twins for migraines will then be presented. The potential and challenges when implementing intelligent digital twins for the future management of migraines are also discussed.

Pain Management in the Most Vulnerable Intellectual Disability: A Review

This review is made up of two parts; the first part discussing intellectual disability (ID) in general, while the second part covers the pain associated with intellectual disability and the challenges and practical tips for the management of pain associated with (ID). Intellectual disability is characterized by deficits in general mental abilities, such as reasoning, problem solving, planning, abstract thinking, judgment, academic learning, and learning from experience. ID is a disorder with no definite cause but has multiple risk factors, including genetic, medical, and acquired. Vulnerable populations such as individuals with intellectual disability may experience more pain than the general population due to additional comorbidities and secondary conditions, or at least the same frequency of pain as in the general population. Pain in patients with ID remains largely unrecognized and untreated due to barriers to verbal and non-verbal communication. It is important to identify patients at risk to promptly prevent or minimize those risk factors. As pain is multifactorial, thus, a multimodal approach using both pharmacotherapy and non-pharmacological management is often the most beneficial. Parents and caregivers should be oriented to this disorder, given adequate training and education, and be actively involved with the treatment program. Significant work to create new pain assessment tools to improve pain practices for individuals with ID has taken place, including neuroimaging and electrophysiological studies. Recent advances in technology-based interventions such as virtual reality and artificial intelligence are rapidly growing to help give patients with ID promising results to develop pain coping skills with effective reduction of pain and anxiety. Therefore, this narrative review highlights the different aspects regarding the current status of the pain associated with intellectual disability, with more emphasis on the recent pieces of evidence for the assessment and management of pain among populations with intellectual disability.

Trends in Passive IoT Biomarker Monitoring and Machine Learning for Cardiovascular Disease Management in the U.S. Elderly Population

It is predicted that the growth in the U.S. elderly population alongside continued growth in chronic disease prevalence will further strain an already overburdened healthcare system and could compromise the delivery of equitable care. Current trends in technology are demonstrating successful application of artificial intelligence (AI) and machine learning (ML) to biomarkers of cardiovascular disease (CVD) using longitudinal data collected passively from internet-of-things (IoT) platforms deployed among the elderly population. These systems are growing in sophistication and deployed across evermore use-cases, presenting new opportunities and challenges for innovators and caregivers alike. IoT sensor development that incorporates greater levels of passivity will increase the likelihood of continued growth in device adoption among the geriatric population for longitudinal health data collection which will benefit a variety of CVD applications. This growth in IoT sensor development and longitudinal data acquisition is paralleled by the growth in ML approaches that continue to provide promising avenues for better geriatric care through higher personalization, more real-time feedback, and prognostic insights that may help prevent downstream complications and relieve strain on the healthcare system overall. However, findings that identify differences in longitudinal biomarker interpretations between elderly populations and relatively younger populations highlights the necessity that ML approaches that use data from newly developed passive IoT systems should collect more data on this target population and more clinical trials will help elucidate the extent of benefits and risks from these data driven approaches to remote care.

Managing Security of Healthcare Data for a Modern Healthcare System

The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental challenge that the modern healthcare management system faces is storing and securely transferring data. Therefore, this research proposes a novel Lionized remora optimization-based serpent (LRO-S) encryption method to encrypt sensitive data and reduce privacy breaches and cyber-attacks from unauthorized users and hackers. The LRO-S method is the combination of hybrid metaheuristic optimization and improved security algorithm. The fitness functions of lion and remora are combined to create a new algorithm for security key generation, which is provided to the serpent encryption algorithm. The LRO-S technique encrypts sensitive patient data before storing it in the cloud. The primary goal of this study is to improve the safety and adaptability of medical professionals' access to cloud-based patient-sensitive data more securely. The experiment's findings suggest that the secret keys generated are sufficiently random and one of a kind to provide adequate protection for the data stored in modern healthcare management systems. The proposed method minimizes the time needed to encrypt and decrypt data and improves privacy standards. This study found that the suggested technique outperformed previous techniques in terms of reducing execution time and is cost-effective.

The Impact of Nutrition and Oral Function Exercise on among Community-Dwelling Older People

Oral function (OF) decline in older people is associated with nutritional deficiencies, which increases frailty risk and the need for nursing care. We investigated whether the delivery of an oral function improvement program on a tablet device was as effective as delivery through a paper-based program. We also investigated the association between tongue pressure (TP) improvement and nutritional status at the baseline. The participants involved in the study were 26 community-dwelling older people with low TP, <30 kPa, aged ≥65 years, who were enrolled in a randomized controlled trial for a month in Itoshima City, Fukuoka, Japan. Oral and physical functions and body composition were measured at the baseline and at follow-up. Two-way analysis of variance revealed that body mass index (p = 0.004) increased, and maximum masticatory performance (p = 0.010), maximum TP (p = 0.035), and oral diadochokinesis /pa/ and /ka/ (p = 0.009 and 0.017, respectively) improved in a month. Participants with higher TP improvement showed an increased intake of animal proteins at the baseline: fish (p = 0.022), meat (p = 0.029), and egg (p = 0.009). OF exercises for improving TP were associated with higher animal protein intake at the baseline. This study has been registered with the UMIN Clinical Trials Registry (UMIN 000050292).

The development of new remote technologies in disaster medicine education: A scoping review

Background

Remote teaching and online learning have significantly changed the responsiveness and accessibility after the COVID-19 pandemic. Disaster medicine (DM) has recently gained prominence as a critical issue due to the high frequency of worldwide disasters, especially in 2021. The new artificial intelligence (AI)-enhanced technologies and concepts have recently progressed in DM education.

Objectives

The aim of this article is to familiarize the reader with the remote technologies that have been developed and used in DM education over the past 20 years.

Literature scoping reviews

Mobile edge computing (MEC), unmanned aerial vehicles (UAVs)/drones, deep learning (DL), and visual reality stimulation, e.g., head-mounted display (HMD), are selected as promising and inspiring designs in DM education.

Methods

We performed a comprehensive review of the literature on the remote technologies applied in DM pedagogy for medical, nursing, and social work, as well as other health discipline students, e.g., paramedics. Databases including PubMed (MEDLINE), ISI Web of Science (WOS), EBSCO (EBSCO Essentials), Embase (EMB), and Scopus were used. The sourced results were recorded in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart and followed in accordance with the PRISMA extension Scoping Review checklist. We included peer-reviewed articles, Epubs (electronic publications such as databases), and proceedings written in English. VOSviewer for related keywords extracted from review articles presented as a tabular summary to demonstrate their occurrence and connections among these DM education articles from 2000 to 2022.

Results

A total of 1,080 research articles on remote technologies in DM were initially reviewed. After exclusion, 64 articles were included in our review. Emergency remote teaching/learning education, remote learning, online learning/teaching, and blended learning are the most frequently used keywords. As new remote technologies used in emergencies become more advanced, DM pedagogy is facing more complex problems.

Discussions

Artificial intelligence-enhanced remote technologies promote learning incentives for medical undergraduate students or graduate professionals, but the efficacy of learning quality remains uncertain. More blended AI-modulating pedagogies in DM education could be increasingly important in the future. More sophisticated evaluation and assessment are needed to implement carefully considered designs for effective DM education.

Evolution of Hybrid Intelligence and Its Application in Evidence-Based Medicine: A Review

Modern medicine, both in clinical practice and research, has become more and more based on data, which is changing equally in type and quality with the advent and development of healthcare digitalization. The first part of the present paper aims to present the steps through which data, and subsequently clinical and research practice, have evolved from paper-based to digital, proposing a possible future of this digitalization in terms of potential applications and integration of digital tools in medical practice. Noting that digitalization is no more a possible future, but a concrete reality, there is a strong need for a new definition of evidence-based medicine, which must take into account the progressive integration of artificial intelligence (AI) in all decision-making processes. So, leaving behind the traditional research concept of human intelligence versus AI, poorly adaptable to real-world clinical practice, a Human and AI hybrid model, seen as a deep integration of AI and human thinking, is proposed as a new healthcare governance system. The second part of our review is focused on some of the major challenges the digitalization process has to face, particularly privacy issues, system complexity and opacity, and ethical concerns related to legal aspects and healthcare disparities. Analyzing these open issues, we aim to present some of the future directions that in our opinion should be pursued to implement AI in clinical practice.

Assessing the Contribution of Managerial Accounting in Sustainable Organizational Development in the Healthcare Industry

Sustainability and digital transformation are two phenomena influencing the activities of all organizations. Managerial accounting is an essential component of these transformations, having complex roles in decision-making to ensure sustainable development through implementing modern technologies in the accounting process. This paper studies the roles of digitized managerial accounting in organizational sustainability drivers from a decision-making perspective. The empirical investigation assesses the influence of managerial accounting on the economic, social, and environmental drivers of sustainability from the perception of 396 Romanian accountants using an artificial neural network analysis and structural equation modeling. As a result, the research provides a holistic view of the managerial accounting roles enhanced by digital technologies in the sustainable development of healthcare organizations. From the accountants' perception, the leading managerial accounting roles on organizational sustainability are enablers and reporters of the sustainable value created in the organization. Additionally, the roles of creators and preservers are seen as relevant by a significant part of the respondents. Therefore, healthcare organizations must implement a sustainability vision in managerial accounting and accounting information systems using the capabilities offered by new digital technologies.

Big data in corneal diseases and cataract: Current applications and future directions

The accelerated growth in electronic health records (EHR), Internet-of-Things, mHealth, telemedicine, and artificial intelligence (AI) in the recent years have significantly fuelled the interest and development in big data research. Big data refer to complex datasets that are characterized by the attributes of "5 Vs"-variety, volume, velocity, veracity, and value. Big data analytics research has so far benefitted many fields of medicine, including ophthalmology. The availability of these big data not only allow for comprehensive and timely examinations of the epidemiology, trends, characteristics, outcomes, and prognostic factors of many diseases, but also enable the development of highly accurate AI algorithms in diagnosing a wide range of medical diseases as well as discovering new patterns or associations of diseases that are previously unknown to clinicians and researchers. Within the field of ophthalmology, there is a rapidly expanding pool of large clinical registries, epidemiological studies, omics studies, and biobanks through which big data can be accessed. National corneal transplant registries, genome-wide association studies, national cataract databases, and large ophthalmology-related EHR-based registries (e.g., AAO IRIS Registry) are some of the key resources. In this review, we aim to provide a succinct overview of the availability and clinical applicability of big data in ophthalmology, particularly from the perspective of corneal diseases and cataract, the synergistic potential of big data, AI technologies, internet of things, mHealth, and wearable smart devices, and the potential barriers for realizing the clinical and research potential of big data in this field.

Nurse, Give Me the News! Understanding Support for and Opposition to a COVID-19 Health Screening System

Helping the sick and protecting the vulnerable has long been the credo of the health profession. In response to the coronavirus-disease-2019 (COVID-19 pandemic), hospitals and healthcare institutions have rapidly employed public health measures to mitigate patient and staff infection. This paper investigates staff and visitor responses to the COVID-19 eGate health screening system; a self-service technology (SST) which aims to protect health care workers and facilities from COVID-19. Our study evaluates the in situ deployment of the eGate, and employs a System Usability Scale (SUS) and questionnaire (n = 220) to understand staff and visitor's acceptance of the eGate. In detailing the themes relevant to those who advocate for the system and those who oppose it, we contribute towards a more detailed understanding of the use and non-use of health-screening SSTs. We conclude with a series of considerations for the design of future interactive screening systems within hospitals.

‘The plural of silo is not ecosystem’: Qualitative study on the role of innovation ecosystems in supporting ‘Internet of Things’ applications in health and care

Background

Internet of Things (IoT) innovations such as wearables and sensors promise improved health outcomes and service efficiencies. Yet, most applications remain experimental with little routine use in health and care settings. We sought to examine the multiple interacting influences on IoT implementation, spread and scale-up, including the role of regional innovation ‘ecosystems’ and the impact of the COVID-19 context.

Methods

Qualitative study involving 20 participants with clinical, entrepreneurial and broader innovation experience in 18 in-depth interviews, focusing primarily on heart monitoring and assistive technology applications. Data analysis was informed by the NASSS (non-adoption, abandonment, scale-up, spread, sustainability) framework.

Results

Interviewees discussed multiple tensions and trade-offs, including lack of organisational capacity for routine IoT use, limited ability to receive and interpret data, complex procurement and governance processes, and risk of health disparities and inequalities without system support and funding. Although the pandemic highlighted opportunities for IoT use, it was unclear whether these would be sustained, with framings of innovation as ‘disruption’ coming at odds with immediate needs in healthcare settings. Even in an ‘ecosystem’ with strong presence of academic and research institutions, support was viewed as limited, with impressions of siloed working, conflicting agendas, fragmentation and lack of collaboration opportunities.

Conclusions

IoT development, implementation and roll-out require support from multiple ecosystem actors to be able to articulate a value proposition beyond experimental or small-scale applications. In contexts where clinical, academic and commercial worlds collide, sustained effort is needed to align needs, priorities and motives, and to strengthen potential for good value IoT innovation.

A digital innovation typology: Navigating the complexity of emerging technologies to negotiate health systems research with young people

Objective

This study aims to explore young people's perspectives of emerging technologies and health systems research in an adolescent health community of practice.

Methods

The context of this integrated knowledge translation study is the Wellbeing Health & Youth Centre of Research Excellence in Adolescent Health. A theory-building, non-systematic review was conducted to examine the concepts and interrelationships of emerging technologies associated with digital innovation and health systems. This typology informed the design of an online workshop with young people to explore their views, concerns, and ideas about health systems research.

Results

A digital innovation typology was identified to differentiate and explain emerging technology concepts and interrelationships that can be applied to the health systems context. Aligned with this typology, youth perspectives about digital health challenges and opportunities were identified to support future research, policy, and practice.

Conclusion

The integrated findings from this study can assist the navigation of complex emerging technologies, and the negotiation of equitable health systems research, between youth and adult stakeholders. Further, with these typology-related resources, mutual learning and the public involvement of young people in health systems research and priority setting agendas can be supported.

Health horizons: Future trends and technologies from the European Medicines Agency's horizon scanning collaborations

In medicines development, the progress in science and technology is accelerating. Awareness of these developments and their associated challenges and opportunities is essential for medicines regulators and others to translate them into benefits for society. In this context, the European Medicines Agency uses horizon scanning to shine a light on early signals of relevant innovation and technological trends with impact on medicinal products. This article provides the results of systematic horizon scanning exercises conducted by the Agency, in collaboration with the World Health Organization (WHO) and the European Commission's Joint Research Centre's (DG JRC). These collaborative exercises aim to inform policy-makers of new trends and increase preparedness in responding to them. A subset of 25 technological trends, divided into three clusters were selected and reviewed from the perspective of medicines regulators. For each of these trends, the expected impact and challenges for their adoption are discussed, along with recommendations for developers, regulators and policy makers.

Assessing Digital Transformation of Cost Accounting Tools in Healthcare

The expansion of digital technologies has significantly changed most economic activities and professions. Digital technologies penetrated managerial accounting and have a vast potential to transform this profession. Implementing emerging digital technologies, such as artificial intelligence, blockchain, the Internet of Things, big data, and cloud computing, can trigger a crucial leap forward, leading to a paradigm-shifting in healthcare organizations' accounting management. The paper's main objective is to investigate the perception of Romanian accountants on implementing digital technologies in healthcare organizations' accounting management. The paper implies a study based on a questionnaire among Romanian accountants who use various digital technologies implemented in traditional and innovative cost accounting tools. Based on structural equation modeling, the results emphasize the prevalence of innovative tools over traditional cost accounting tools improved through digital transformation, digital technologies assuming the most complex and time-consuming tasks. Moreover, the influence of cost accounting tools improved through digital transformation on healthcare organizations' performance is much more robust in the case of innovative tools than in the case of traditional cost accounting tools. The proposed model provides managers in healthcare organizations with information on the most effective methods in the context of digital transformation.

A Survey of Authentication in Internet of Things-Enabled Healthcare Systems

The Internet of medical things (IoMT) provides an ecosystem in which to connect humans, devices, sensors, and systems and improve healthcare services through modern technologies. The IoMT has been around for quite some time, and many architectures/systems have been proposed to exploit its true potential. Healthcare through the Internet of things (IoT) is envisioned to be efficient, accessible, and secure in all possible ways. Even though the personalized health service through IoT is not limited to time or location, many associated challenges have emerged at an exponential pace. With the rapid shift toward IoT-enabled healthcare systems, there is an extensive need to examine possible threats and propose countermeasures. Authentication is one of the key processes in a system's security, where an individual, device, or another system is validated for its identity. This survey explores authentication techniques proposed for IoT-enabled healthcare systems. The exploration of the literature is categorized with respect to the technology deployment region, as in cloud, fog, and edge. A taxonomy of attacks, comprehensive analysis, and comparison of existing authentication techniques opens up possible future directions and paves the road ahead.

Health-Related Indicators Measured Using Earable Devices: Systematic Review

BACKGROUND

Earable devices are novel, wearable Internet of Things devices that are user-friendly and have potential applications in mobile health care. The position of the ear is advantageous for assessing vital status and detecting diseases through reliable and comfortable sensing devices.

OBJECTIVE

Our study aimed to review the utility of health-related indicators derived from earable devices and propose an improved definition of disease prevention. We also proposed future directions for research on the health care applications of earable devices.

METHODS

A systematic review was conducted of the PubMed, Embase, and Web of Science databases. Keywords were used to identify studies on earable devices published between 2015 and 2020. The earable devices were described in terms of target health outcomes, biomarkers, sensor types and positions, and their utility for disease prevention.

RESULTS

A total of 51 articles met the inclusion criteria and were reviewed, and the frequency of 5 health-related characteristics of earable devices was described. The most frequent target health outcomes were diet-related outcomes (9/51, 18%), brain status (7/51, 14%), and cardiovascular disease (CVD) and central nervous system disease (5/51, 10% each). The most frequent biomarkers were electroencephalography (11/51, 22%), body movements (6/51, 12%), and body temperature (5/51, 10%). As for sensor types and sensor positions, electrical sensors (19/51, 37%) and the ear canal (26/51, 51%) were the most common, respectively. Moreover, the most frequent prevention stages were secondary prevention (35/51, 69%), primary prevention (12/51, 24%), and tertiary prevention (4/51, 8%). Combinations of ≥2 target health outcomes were the most frequent in secondary prevention (8/35, 23%) followed by brain status and CVD (5/35, 14% each) and by central nervous system disease and head injury (4/35, 11% each).

CONCLUSIONS

Earable devices can provide biomarkers for various health outcomes. Brain status, healthy diet status, and CVDs were the most frequently targeted outcomes among the studies. Earable devices were mostly used for secondary prevention via monitoring of health or disease status. The potential utility of earable devices for primary and tertiary prevention needs to be investigated further. Earable devices connected to smartphones or tablets through cloud servers will guarantee user access to personal health information and facilitate comfortable wearing.

Characteristics of Smart Health Ecosystems That Support Self-care Among People With Heart Failure: Scoping Review

BACKGROUND

The management of heart failure is complex. Innovative solutions are required to support health care providers and people with heart failure with decision-making and self-care behaviors. In recent years, more sophisticated technologies have enabled new health care models, such as smart health ecosystems. Smart health ecosystems use data collection, intelligent data processing, and communication to support the diagnosis, management, and primary and secondary prevention of chronic conditions. Currently, there is little information on the characteristics of smart health ecosystems for people with heart failure.

OBJECTIVE

We aimed to identify and describe the characteristics of smart health ecosystems that support heart failure self-care.

METHODS

We conducted a scoping review using the Joanna Briggs Institute methodology. The MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, and ACM Digital Library databases were searched from January 2008 to September 2021. The search strategy focused on identifying articles describing smart health ecosystems that support heart failure self-care. A total of 2 reviewers screened the articles and extracted relevant data from the included full texts.

RESULTS

After removing duplicates, 1543 articles were screened, and 34 articles representing 13 interventions were included in this review. To support self-care, the interventions used sensors and questionnaires to collect data and used tailoring methods to provide personalized support. The interventions used a total of 34 behavior change techniques, which were facilitated by a combination of 8 features for people with heart failure: automated feedback, monitoring (integrated and manual input), presentation of data, education, reminders, communication with a health care provider, and psychological support. Furthermore, features to support health care providers included data presentation, alarms, alerts, communication tools, remote care plan modification, and health record integration.

CONCLUSIONS

This scoping review identified that there are few reports of smart health ecosystems that support heart failure self-care, and those that have been reported do not provide comprehensive support across all domains of self-care. This review describes the technical and behavioral components of the identified interventions, providing information that can be used as a starting point for designing and testing future smart health ecosystems.

Internet of Things and healthcare system: A systematic review of ethical issues

Background and Aims

The Internet of Things (IoTs) is a set of connected objects and devices that share data and pursue a common goal in different areas. IoT technology can significantly help the healthcare system by enabling the monitoring of elderly and chronic disease patients. Along with the growth of this technology, its challenges and limitations such as Connectivity, Compatibility, Standards, cost, legal, and ethical also increase. One of the most critical and challenging issues in the IoT is ethical issues. This study aims to explore the key ethical aspects of the IoT and Categorize them based on the executive phases of IoT in healthcare.

Methods

The current study was conducted in two phases using the mixed-method approach. In the first phase, a systematic review was conducted in relevant databases to identify ethical issues of the IoT. In the second phase, a focus group discussion was conducted to classify the extracted data elements based on executive phases of IoT by medical informatics experts and computer engineerings.

Results

Among the 138 papers retrieved through the search strategy, 11 articles were selected, and 12 ethical issues related to IoT were identified. The obtained results revealed the importance of ethical issues of IoT, including security, confidentiality, privacy, anonymity, freedom to withdraw, informed consent, integrity, availability, authorization, access control, censoring, and eavesdropping. They were classified into five main categories of executive phases of IoT based on the five experts' opinions affiliated with SUMS, including data collection, data storage, data process, data transmission, and data delivery.

Conclusion

Because of the key role of the IoT in disease prevention, real-time tele-monitoring of patient's functions, testing of treatments, health management, and health research, considering the risks relating to Health care and patient data is essential. Moreover, health policymakers should be aware of the ethical commitment to using IoT technology.

Telemedicine Technologies Selection for the Posthospital Patient Care Process after Total Hip Arthroplasty

For many years, the importance of using telematic technologies in medicine has been growing, especially in the period of the coronavirus pandemic, when direct contact and supervision of medical personnel over the patient is difficult. The existing possibilities of modern information and communication technologies (ICTs) are not fully used. The aim of the study is to identify the telemedicine technologies that can be used in future implementation projects of the posthospital patient care process after total hip arthroplasty (THA). The literature search is reported according to PRISMA 2020. The search strategy included databases and gray literature. In total, 28 articles (EMBASE, PubMed, PEDro) and 24 records from gray literature (Google Search and Technology presentations) were included in the research. This multi-source study analyzes the possibilities of using different technologies useful in the patient care process. The conducted research resulted in defining visual and wearable types of telemedicine technologies for the original posthospital patient care process after THA. As the needs of stakeholders in the posthospital patient care process after THA differ, the awareness of appropriate technologies selection, information flow, and its management importance are prerequisites for effective posthospital patient care with the use of telemedicine technologies.

Enabling image optimisation and artificial intelligence technologies for better Internet of Things framework to predict COVID

Sensor technology advancements have provided a viable solution to fight COVID and to develop healthcare systems based on Internet of Things (IoTs). In this study, image processing and Artificial Intelligence (AI) are used to improve the IoT framework. Computed Tomography (CT) image‐based forecasting of COVID disease is among the important activities in medicine for measuring the severity of variability in the human body. In COVID CT images, the optimal gamma correction value was optimised using the Whale Optimisation Algorithm (WOA). During the search for the optimal solution, WOA was found to be a highly efficient algorithm, which has the characteristics of high precision and fast convergence. Whale Optimisation Algorithm is used to find best gamma correction value to present detailed information about a lung CT image, Also, in this study, analysis of important AI techniques has been done, such as Support Vector Machine (SVM) and Deep‐Learning (Deep‐Learning (DL)) for COVID disease forecasting in terms of amount of data training and computational power. Many experiments have been implemented to investigate the optimisation: SVM and DL with WOA and without WOA are compared by using confusion matrix parameters. From the results, we find that the DL model outperforms the SVM with WOA and without WOA.

Empirical investigation of e-health intervention in cervical cancer screening: A systematic literature review

Cervical cancer (CC) screening can detect the cancer early but is underutilized, especially among the developing countries and low- to middle-income countries. Electronic health (e-health) has the potential for disseminating health education and is widely used in the developed countries. This systematic literature review investigates the effectiveness of e-health intervention for improving knowledge of CC and the intention or uptake for CC screening. We followed the PRISMA 2020 guideline and registered with PROSPERO (registration ID CRD42021276036). We searched the Web of Science, Scopus and EBSCO Medline Complete databases for eligible studies. Studies that conveyed informational material through e-health intervention were selected. The results were analyzed using narrative synthesis, and the pooled estimates were calculated using meta-analysis. A total of six studies involving 1886 women were included in this review. The use of e-health aids alone led to increased knowledge. The meta-analysis demonstrated that the mixed-education method of e-health movies and video education with didactic sessions increased CC screening uptake. A random-effects model revealed that CC screening uptake following e-health interventions were almost double of that of their comparison (odds ratio = 2.29, 95% confidence interval: 1.28–4.10, p < 0.05). Various areas of study demonstrated e-health intervention effectiveness (minority communities, urban areas, rural areas). Health education through e-health intervention has huge potential for promoting CC screening in the community. Nevertheless, the use of appropriate frameworks, user engagement and culturally tailored e-health need to be prioritized.

AI-based Ethical Hacking for Health Information Systems (HIS): a simulation study (Preprint)

BACKGROUND

Health information systems (HISs) are continuously targeted by hackers, who aim to bring down critical health infrastructure. This study was motivated by recent attacks on health care organizations that have resulted in the compromise of sensitive data held in HISs. Existing research on cybersecurity in the health care domain places an imbalanced focus on protecting medical devices and data. There is a lack of a systematic way to investigate how attackers may breach an HIS and access health care records.

OBJECTIVE

This study aimed to provide new insights into HIS cybersecurity protection. We propose a systematic, novel, and optimized (artificial intelligence-based) ethical hacking method tailored specifically for HISs, and we compared it with the traditional unoptimized ethical hacking method. This allows researchers and practitioners to identify the points and attack pathways of possible penetration attacks on the HIS more efficiently.

METHODS

In this study, we propose a novel methodological approach to ethical hacking in HISs. We implemented ethical hacking using both optimized and unoptimized methods in an experimental setting. Specifically, we set up an HIS simulation environment by implementing the open-source electronic medical record (OpenEMR) system and followed the National Institute of Standards and Technology's ethical hacking framework to launch the attacks. In the experiment, we launched 50 rounds of attacks using both unoptimized and optimized ethical hacking methods.

RESULTS

Ethical hacking was successfully conducted using both optimized and unoptimized methods. The results show that the optimized ethical hacking method outperforms the unoptimized method in terms of average time used, the average success rate of exploit, the number of exploits launched, and the number of successful exploits. We were able to identify the successful attack paths and exploits that are related to remote code execution, cross-site request forgery, improper authentication, vulnerability in the Oracle Business Intelligence Publisher, an elevation of privilege vulnerability (in MediaTek), and remote access backdoor (in the web graphical user interface for the Linux Virtual Server).

CONCLUSIONS

This research demonstrates systematic ethical hacking against an HIS using optimized and unoptimized methods, together with a set of penetration testing tools to identify exploits and combining them to perform ethical hacking. The findings contribute to the HIS literature, ethical hacking methodology, and mainstream artificial intelligence-based ethical hacking methods because they address some key weaknesses of these research fields. These findings also have great significance for the health care sector, as OpenEMR is widely adopted by health care organizations. Our findings offer novel insights for the protection of HISs and allow researchers to conduct further research in the HIS cybersecurity domain.

The Impact of Digital Transformation on Inpatient Care: A Mixed Design Study (Preprint)

BACKGROUND

In the context of the digital transformation of all areas of society, health care providers are also under pressure to change. New technologies and a change in patients' self-perception and health awareness require rethinking the provision of health care services. New technologies and the extensive use of data can change provision processes, optimize them, or replace them with new services. The inpatient sector, which accounts for a particularly large share of health care spending, plays a major role in this regard.

OBJECTIVE

This study examined the influences of current trends in digitization on inpatient service delivery.

METHODS

We conducted a scoping review. This was applied to identify the international trends in digital transformation as they relate to hospitals. Future trends were considered from different perspectives. Using the defined inclusion criteria, international peer-reviewed articles published between 2016 and 2021 were selected. The extracted core trends were then contextualized for the German hospital sector with 12 experts.

RESULTS

We included 44 articles in the literature analysis. From these, 8 core trends could be deduced. A heuristic impact model of the trends was derived from the data obtained and the experts' assessments. This model provides a development corridor for the interaction of the trends with regard to technological intensity and supply quality. Trend accelerators and barriers were identified.

CONCLUSIONS

The impact analysis showed the dependencies of a successful digital transformation in the hospital sector. Although data interoperability is of particular importance for technological intensity, the changed self-image of patients was shown to be decisive with regard to the quality of care. We show that hospitals must find their role in new digitally driven ecosystems, adapt their business models to customer expectations, and use up-to-date information and communications technologies.

Adoption and Safety Evaluation of Comfortable Nursing by Mobile Internet of Things in Pediatric Outpatient Sedation

The aim of study was to explore the application effect and safety of comfortable nursing based on optimized mobile Internet of Things (MIoT) in the clinical sedation and diagnosis of mycoplasma pneumoniae pneumonia (MPP) in children. A total of 70 children with MPP admitted to the respiratory clinic of hospital were randomly selected and divided into a control group (comfortable nursing mode) and an observation group (comfortable nursing mode based on optimized MIoT), with 35 cases in each. The nursing effects and safety were compared between groups. The results showed that the node jitter rate, delivery success rate, and congestion times of the multilayered sensing algorithm were better than those of the mobile relay area segmentation algorithm and the wedge merge-energy hole elimination area segmentation algorithm. The CD-RISC resilience score of the observation group ((94.72 ± 1.58) points), the proportion of children with Frankl-3 and 4 points (90%), and the comfort level ((95.01 ± 5.68) points) were higher than those of the control group ((64.12 ± 1.62) points, (33.33%), and (55.23 ± 6.18) points) (P < 0.05). After treatment, the proportion of children with HRCT image lesions in the observation group was lower than that in the control group (P < 0.05). After treatment, the FEV1 ((85.71 ± 5.23) % vs. (68.26 ± 5.90) %) and FEV1/FVC ((74.22 ± 2.12) % vs (64.38 ± 2.34) %) of the observation group were significantly better than those of the control group (P < 0.05). The results showed that the incidence of adverse reactions in the observation group (14%) was significantly lower than that in the control group (46%) (P < 0.05). MIoT-assisted comfort nursing based on multilayer perception region segmentation algorithm can more effectively relieve the emotions of children in MPP outpatient department during sedation and diagnosis and treatment, improve the therapeutic effect and safety, and is worthy of clinical promotion.

PUFchain 2.0: Hardware-Assisted Robust Blockchain for Sustainable Simultaneous Device and Data Security in Smart Healthcare

This article presents the first-ever hardware-assisted blockchain for simultaneously handling device and data security in smart healthcare. This article presents the hardware security primitive physical unclonable functions (PUF) and blockchain technology together as PUFchain 2.0 with a two-level authentication mechanism. The proposed PUFchain 2.0 security primitive presents a scalable approach by allowing Internet of Medical Things (IoMT) devices to connect and obtain PUF keys from the edge server with an embedded PUF module instead of connecting a PUF module to each device. The PUF key, once assigned to a particular media access control (MAC) address by the miner, will be unique for that MAC address and cannot be assigned to other devices. PUFs are developed based on internal micro-manufacturing process variations during chip fabrication. This property of PUFs is integrated with blockchain by including the PUF key of the IoMT into blockchain for authentication. The robustness of the proposed Proof of PUF-Enabled authentication consensus mechanism in PUFchain 2.0 has been substantiated through test bed evaluation. Arbiter PUFs have been used for the experimental validation of PUFchain 2.0. From the obtained 200 PUF keys, 75% are reliable and the Hamming distance of the PUF module is 48%. Obtained database outputs along with other metrics have been presented for validating the potential of PUFchain 2.0 in smart healthcare.

Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches

Pain research traverses many disciplines and methodologies. Yet, despite our understanding and field-wide acceptance of the multifactorial essence of pain as a sensory perception, emotional experience, and biopsychosocial condition, pain scientists and practitioners often remain siloed within their domain expertise and associated techniques. The context in which the field finds itself today-with increasing reliance on digital technologies, an on-going pandemic, and continued disparities in pain care-requires new collaborations and different approaches to measuring pain. Here, we review the state-of-the-art in human pain research, summarizing emerging practices and cutting-edge techniques across multiple methods and technologies. For each, we outline foreseeable technosocial considerations, reflecting on implications for standards of care, pain management, research, and societal impact. Through overviewing alternative data sources and varied ways of measuring pain and by reflecting on the concerns, limitations, and challenges facing the field, we hope to create critical dialogues, inspire more collaborations, and foster new ideas for future pain research methods.

Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review

Cardiovascular diseases (CVD) are the leading cause of mortality globally. Despite improvement in therapies, people with CVD lack support for monitoring and managing their condition at home and out of hospital settings. Smart Home Technologies have potential to monitor health status and support people with CVD in their homes. We explored the Smart Home Technologies available for CVD monitoring and management in people with CVD and acceptance of the available technologies to end-users. We systematically searched four databases, namely Medline, Web of Science, Embase, and IEEE, from 1990 to 2020 (search date 18 March 2020). “Smart-Home” was defined as a system using integrated sensor technologies. We included studies using sensors, such as wearable and non-wearable devices, to capture vital signs relevant to CVD at home settings and to transfer the data using communication systems, including the gateway. We categorised the articles for parameters monitored, communication systems and data sharing, end-user applications, regulations, and user acceptance. The initial search yielded 2462 articles, and the elimination of duplicates resulted in 1760 articles. Of the 36 articles eligible for full-text screening, we selected five Smart Home Technology studies for CVD management with sensor devices connected to a gateway and having a web-based user interface. We observed that the participants of all the studies were people with heart failure. A total of three main categories—Smart Home Technology for CVD management, user acceptance, and the role of regulatory agencies—were developed and discussed. There is an imperative need to monitor CVD patients’ vital parameters regularly. However, limited Smart Home Technology is available to address CVD patients’ needs and monitor health risks. Our review suggests the need to develop and test Smart Home Technology for people with CVD. Our findings provide insights and guidelines into critical issues, including Smart Home Technology for CVD management, user acceptance, and regulatory agency’s role to be followed when designing, developing, and deploying Smart Home Technology for CVD.

A Systematic Review of Internet of Things Adoption in Organizations: Taxonomy, Benefits, Challenges and Critical Factors

Despite the evident growth of the Internet of Things (IoT) applications, IoT deployments in organizations remain in their early stages. This paper aims to systematically review and analyze the existing literature on IoT adoption in organizations. The extant literature was identified using five electronic databases from 2015 to July 2021. Seventy-seven articles have met the eligibility criteria and were analyzed to answer the research questions. This study produced a coherent taxonomy that can serve as a framework for future research on IoT adoption in organizations. This paper presents an overview of the essential features of this emerging technology in terms of IoT adoption benefits and challenges in organizations. Existing theoretical models have been analyzed to identify the factors that influence IoT adoption and to understand the future requirements for widespread IoT adoption in organizations. Six critical factors affecting and playing a key role in IoT adoption in organizations were identified based on the critical review findings: technological, organizational, environmental, human, benefit, and value. Decision-makers and developers can prioritize these critical factors and progressively improve their development to enhance IoT adoption efficiency. This review also includes an in-depth analysis to bridge gaps and provide a comprehensive overview to further understand this research field.

The digital transformation of hepatology: The patient is logged in

The rise in innovative digital health technologies has led a paradigm shift in health care toward personalized, patient-centric medicine that is reaching beyond traditional brick-and-mortar facilities into patients' homes and everyday lives. Digital solutions can monitor and detect early changes in physiological data, predict disease progression and health-related outcomes based on individual risk factors, and manage disease intervention with a range of accessible telemedicine and mobile health options. In this review, we discuss the unique transformation underway in the care of patients with liver disease, specifically examining the digital transformation of diagnostics, prediction and clinical decision-making, and management. Additionally, we discuss the general considerations needed to confirm validity and oversight of new technologies, usability and acceptability of digital solutions, and equity and inclusivity of vulnerable populations.

A Platform and Multisided Market for Translational, Software-Defined Medical Procedures in the Operating Room (OP 4.1): Proof-of-Concept Study

Background

Although digital and data-based technologies are widespread in various industries in the context of Industry 4.0, the use of smart connected devices in health care is still in its infancy. Innovative solutions for the medical environment are affected by difficult access to medical device data and high barriers to market entry because of proprietary systems.

Objective

In the proof-of-concept project OP 4.1, we show the business viability of connecting and augmenting medical devices and data through software add-ons by giving companies a technical and commercial platform for the development, implementation, distribution, and billing of innovative software solutions.

Methods

The creation of a central platform prototype requires the collaboration of several independent market contenders, including medical users, software developers, medical device manufacturers, and platform providers. A dedicated consortium of clinical and scientific partners as well as industry partners was set up.

Results

We demonstrate the successful development of the prototype of a user-centric, open, and extensible platform for the intelligent support of processes starting with the operating room. By connecting heterogeneous data sources and medical devices from different manufacturers and making them accessible for software developers and medical users, the cloud-based platform OP 4.1 enables the augmentation of medical devices and procedures through software-based solutions. The platform also allows for the demand-oriented billing of apps and medical devices, thus permitting software-based solutions to fast-track their economic development and become commercially successful.

Conclusions

The technology and business platform OP 4.1 creates a multisided market for the successful development, implementation, distribution, and billing of new software solutions in the operating room and in the health care sector in general. Consequently, software-based medical innovation can be translated into clinical routine quickly, efficiently, and cost-effectively, optimizing the treatment of patients through smartly assisted procedures.

A gamified app for supporting undergraduate students’ mental health: A feasibility and usability study

Resilience, a person's mental ability to deal with challenging situations adaptively, is an important life skill. Supporting students in building psychological resilience and coping during crises (with the COVID-19 pandemic being a prime example) is crucial. Very few mobile applications (apps) for mental health explicitly report behavioral change techniques. Moreover, only a handful of the apps that support resilience are gamified, or use smartphone sensors readily available in modern smartphones for health self-management, or were designed for use by a nonclinical population. This study describes the design of a prototype for a gamified, theory-based mobile app that utilizes the Internet of Things to provide personalized data and enhance undergraduate students’ resilience. A total of 74 participants evaluated the prototype and completed an online questionnaire during the COVID-19 lockdowns. The questionnaire included questions examining the design's feasibility for supporting resilience and questions on the System Usability Scale evaluating its usability. Regarding the evaluation of the prototype on improving psychological resilience, positive responses (M = 3.76 out of 5, SD = 0.82) were received for all functions (goal setting for studying, socializing and physical exercise, progress monitoring using sensors or self-reporting, reflection, motivational badges). The System Usability Scale returned an evaluation score of 72.9, indicating a satisfactory degree of usability. The resilience app is a promising proof of concept. Combining Internet of Things capabilities with active user interaction while incorporating behavior change techniques in a gamified environment was well accepted by students. Implications for the design of gamified environments for well-being are drawn. Future research will empirically validate its design using quasi-experimental methods.

From Syndemic Lesson after COVID-19 Pandemic to a "Systemic Clinical Risk Management" Proposal in the Perspective of the Ethics of Job Well Done

The syndemic framework proposed by the 2021-2030 World Health Organization (WHO) action plan for patient safety and the introduction of enabling technologies in health services involve a more effective interpretation of the data to understand causation. Based on the Systemic Theory, this communication proposes the "Systemic Clinical Risk Management" (SCRM) to improve the Quality of Care and Patient Safety. This is a new Clinical Risk Management model capable of developing the ability to observe and synthesize different elements in ways that lead to in-depth interventions to achieve solutions aligned with the sustainable development of health services. In order to avoid uncontrolled decision-making related to the use of enabling technologies, we devised an internal Learning Algorithm Risk Management (LARM) level based on a Bayesian approach. Moreover, according to the ethics of Job Well Done, the SCRM, instead of giving an opinion on events that have already occurred, proposes a bioethical co-working because it suggests the best way to act from a scientific point of view.

Play the Pain: A Digital Strategy for Play-Oriented Research and Action

The value of understanding patients' illness experience and social contexts for advancing medicine and clinical care is widely acknowledged. However, methodologies for rigorous and inclusive data gathering and integrative analysis of biomedical, cultural, and social factors are limited. In this paper, we propose a digital strategy for large-scale qualitative health research, using play (as a state of being, a communication mode or context, and a set of imaginative, expressive, and game-like activities) as a research method for recursive learning and action planning. Our proposal builds on Gregory Bateson's cybernetic approach to knowledge production. Using chronic pain as an example, we show how pragmatic, structural and cultural constraints that define the relationship of patients to the healthcare system can give rise to conflicted messaging that impedes inclusive health research. We then review existing literature to illustrate how different types of play including games, chatbots, virtual worlds, and creative art making can contribute to research in chronic pain. Inspired by Frederick Steier's application of Bateson's theory to designing a science museum, we propose DiSPORA (Digital Strategy for Play-Oriented Research and Action), a virtual citizen science laboratory which provides a framework for delivering health information, tools for play-based experimentation, and data collection capacity, but is flexible in allowing participants to choose the mode and the extent of their interaction. Combined with other data management platforms used in epidemiological studies of neuropsychiatric illness, DiSPORA offers a tool for large-scale qualitative research, digital phenotyping, and advancing personalized medicine.

Internet of Things (IoT) Technology Research in Business and Management Literature: Results from a Co-Citation Analysis

In coherence with the progressive digitalization of all areas of life, the Internet of Things (IoT) is a flourishing concept in both research and practice. Due to the increasing scholarly attention, the literature landscape has become scattered and fragmented. With a focus on the commercial application of the IoT and corresponding research, we employ a co-citation analysis and literature review to structure the field. We find and describe 19 research themes. To consolidate the extant research, we propose a research framework, which is based on a theoretical implementation process of IoT as a concept, specific IoT applications, or architectures integrated in an adapted input–process–output model. The main variables of the model are an initial definition and conceptualization of an IoT concept (input), which goes through an evaluation process (process), before it is implemented and can have an impact in practice (output). The paper contributes to interdisciplinary research relating to a business and management perspective on IoT by providing a holistic overview of predominant research themes and an integrative research framework.

Developing a Risk Governance Framework on Radiological Emergency, Preparedness, and Response for Emergency Responders: Protocol for a Mixed Methods Study

Background

Risk governance involves processes and mechanisms to understand how risk decisions are taken and executed. This concept has gained a reputation over time as being essential for emerging comprehensive management that defines the success of an organization. While guiding documents that explain the use of risk management related to nuclear safety and security are available worldwide, few locally conducted studies have explained risk governance practices in areas where hazard usage is known, such as in radiological emergencies.

Objective

This paper describes a protocol that was used to determine several factors that influence emergency responders’ perceptions toward radiological risk practices and visualize the risk radiological framework for emergency preparedness and response.

Methods

A mixed methods study with a convergent design was performed. A qualitative analysis was performed using a case study approach where 6 key informants were purposely sampled for in-depth interview, and a cross-sectional study involving a self-administered questionnaire was conducted among approximately 260 emergency respondents from national regulatory, research, and services organizations. NVivo (version 12, QSR International) was used to analyze the interview transcripts and emerging themes were identified through abductive coding. Simultaneously, multiple logistic regression analysis was used to determine significant predictors that form the equation model.

Results

The study is still underway. Qualitative findings were based on transcript-coding that informed the relevant thematic analysis, while statistical analyses including multiple logistic regression analysis measured the adjusted odds ratio of significant variables for the equation model. The study is expected to conclude in late 2021.

Conclusions

Important emerging themes and significant factors that are related to the emergency responders’ perceptions regarding radiological governance practices were determined through the convergent design. This potentially facilitated the development of a plausible radiological risk governance framework. Furthermore, our results will provide key insights that can be used in future studies.

International Registered Report Identifier (IRRID)

DERR1-10.2196/25877

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital

Background

Caregivers of patients who wear conventional diapers are required to check for voiding every hour because prolonged wearing of wet diapers causes health problems including diaper dermatitis and urinary tract infections. However, frequent checking is labor intensive and disturbs patients’ and caregivers’ sleep. Furthermore, assessing patients’ urine output with diapers in an acute care setting is difficult. Recently, a smart diaper system with wetness detection technology was developed to solve these issues.

Objective

We aimed to evaluate the applicability of the smart diaper system for urinary detection, its accuracy in measuring voiding volume, and its effect on incontinence-associated dermatitis (IAD) occurrence in an acute care hospital.

Methods

This prospective, observational, single-arm pilot study was conducted at a single tertiary hospital. We recruited 35 participants aged ≥50 years who were wearing diapers due to incontinence between August and November 2020. When the smart diaper becomes wet, the smart diaper system notifies the caregiver to change the diaper and measures voiding volume automatically. Caregivers were instructed to record the weight of wet diapers on frequency volume charts (FVCs). We determined the voiding detection rate of the smart diaper system and compared the urine volume as automatically calculated by the smart diaper system with the volume recorded on FVCs. Agreement between the two measurements was estimated using a Bland-Altman plot. We also checked for the occurrence or aggravation of IAD and bed sores.

Results

A total of 30 participants completed the protocol and 390 episodes of urination were recorded. There were 108 records (27.7%) on both the FVCs and the smart diaper system, 258 (66.2%) on the FVCs alone, 18 (4.6%) on the smart diaper system alone, and 6 (1.5%) on the FVCs with sensing device lost. The detection rate of the smart diaper system was 32.8% (126/384). When analyzing records concurrently listed in both the FVCs and the smart diaper system, linear regression showed a strong correlation between the two measurements (R²=0.88, P<.001). The Bland-Altman assessment showed good agreement between the two measurements, with a mean difference of –4.2 mL and 95% limits of agreement of –96.7 mL and 88.3 mL. New occurrence and aggravation of IAD and bed sores were not observed. Bed sores improved in one participant.

Conclusions

The smart diaper system showed acceptable accuracy for measuring urine volume and it could replace conventional FVCs in acute setting hospitals. Furthermore, the smart diaper system has the potential advantage of preventing IAD development and bed sore worsening. However, the detection rate of the smart diaper system was lower than expected. Detection rate polarization among participants was observed, and improvements in the user interface and convenience are needed for older individuals who are unfamiliar with the smart diaper system.

Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors, namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in the wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.

COVID-19 Is a Crisis in Planetary Health and Politics of Expertise: Time to Think Critically and Innovate Both

This expert review offers an analysis of the global governance of the COVID-19 pandemic. The pandemic is not only a health crisis but also a crisis of global governance. For example, the nation states in dealing with the crises of the pandemic have turned inwards, toward native and national solutions, and therefore away from the much-needed global cooperation to respond to the pandemic. This is an important concern for systems medicine and integrative biology in both normative and instrumental sense. Moreover, if we are to "pandemic-proof" the planet and the life science innovation ecosystem, new ways of understanding global governance are called for. This article examines the ways in which national governments have reacted to the crises triggered and embodied by the COVID-19 pandemic, surfaces the different approaches and conflicts between scientific experts and policy makers, and reveals the failure of science and politics. I analyze the uneven and disjointed way Western democratic governments have responded to the crisis and the way unchecked normative values and ideas have influenced the pandemic policy and prevented effective measures to contain the pandemic. Finally, the complex relationships between politics, knowledge, science, and governments are explored and clarified, and the way the COVID-19 crisis highlighted the long-standing tensions between technocracy and democracy. In conclusion, it is time to think critically and reflexively for all knowledge actors in systems science and innovate both planetary health and its global governance.

Health Care Cybersecurity Challenges and Solutions Under the Climate of COVID-19: Scoping Review

BACKGROUND

COVID-19 has challenged the resilience of the health care information system, which has affected our ability to achieve the global goal of health and well-being. The pandemic has resulted in a number of recent cyberattacks on hospitals, pharmaceutical companies, the US Department of Health and Human Services, the World Health Organization and its partners, and others.

OBJECTIVE

The aim of this review was to identify key cybersecurity challenges, solutions adapted by the health sector, and areas of improvement needed to counteract the recent increases in cyberattacks (eg, phishing campaigns and ransomware attacks), which have been used by attackers to exploit vulnerabilities in technology and people introduced through changes to working practices in response to the COVID-19 pandemic.

METHODS

A scoping review was conducted by searching two major scientific databases (PubMed and Scopus) using the search formula "(covid OR healthcare) AND cybersecurity." Reports, news articles, and industry white papers were also included if they were related directly to previously published works, or if they were the only available sources at the time of writing. Only articles in English published in the last decade were included (ie, 2011-2020) in order to focus on current issues, challenges, and solutions.

RESULTS

We identified 9 main challenges in cybersecurity, 11 key solutions that health care organizations adapted to address these challenges, and 4 key areas that need to be strengthened in terms of cybersecurity capacity in the health sector. We also found that the most prominent and significant methods of cyberattacks that occurred during the pandemic were related to phishing, ransomware, distributed denial-of-service attacks, and malware.

CONCLUSIONS

This scoping review identified the most impactful methods of cyberattacks that targeted the health sector during the COVID-19 pandemic, as well as the challenges in cybersecurity, solutions, and areas in need of improvement. We provided useful insights to the health sector on cybersecurity issues during the COVID-19 pandemic as well as other epidemics or pandemics that may materialize in the future.

Ethical Challenges of Using Virtual Environments in the Assessment and Treatment of Psychopathological Disorders

Clinicians are increasingly interested in the potential of virtual environments for research and praxes. Virtual environments include both immersive and non-immersive simulations of everyday activities. Moreover, algorithmic devices and adaptive virtual environments allow clinicians a medium for personalizing technologies to their patients. There is also increasing recognition of social virtual environments that connect virtual environments to social networks. Although there has been a great deal of deliberation on these novel technologies for assessment and treatment, less discourse has occurred around the ethical challenges that may ensue when these technologies are applied clinically. In this paper, some of the ethical issues involved in the clinical use of novel technologies are discussed.