Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.Consejo Nacional de Ciencia y Tecnologia (CONACyT)Sonora Institute of Technology (ITSON) via the PROFAPI program PROFAPI_2020_0055Spanish Ministry of Science, Innovation and Universities (MICINN) project "Advanced Computing Architectures and Machine Learning-Based Solutions for Complex Problems in Bioinformatics, Biotechnology and Biomedicine" RTI2018-101674-B-I0

From eHealth to iHealth: Transition to participatory and personalized medicine in mental health

Clinical assessment in psychiatry is commonly based on findings from brief, regularly scheduled in-person appointments. Although critically important, this approach reduces assessment to cross-sectional observations that miss essential information about disease course. The mental health provider makes all medical decisions based on this limited information. Thanks to recent technological advances such as mobile phones and other personal devices, electronic health (eHealth) data collection strategies now can provide access to real-Time patient self-report data during the interval between visits. Since mobile phones are generally kept on at all times and carried everywhere, they are an ideal platform for the broad implementation of ecological momentary assessment technology. Integration of these tools into medical practice has heralded the eHealth era. Intelligent health (iHealth) further builds on and expands eHealth by adding novel built-in data analysis approaches based on (1) incorporation of new technologies into clinical practice to enhance real-Time self-monitoring, (2) extension of assessment to the patient's environment including caregivers, and (3) data processing using data mining to support medical decision making and personalized medicine. This will shift mental health care from a reactive to a proactive and personalized discipline.This research was partially support by Instituto de Salud Carlos III (PI16/01852 Grant), Plan Nacional de Drogas (20151073 Project), and American Foundation for Suicide Prevention (LSRG-1-005-16). SB’s work was supported by Fondation de l’Avenir, the French Embassy in Madrid; MMPR's work was supported by a National Alliance for Research on Schizophrenia and Depression (NARSAD) Young Investigator Award (YIA) grant and a KL2 Faculty Scholar (KL2TR001435) grant (PI: Perez-Rodriguez

Empowering patients in self-management of parkinson's disease through cooperative ICT systems

The objective of this chapter is to demonstrate the technical feasibility and medical effectiveness of personalised services and care programmes for Parkinson's disease, based on the combination of mHealth applications, cooperative ICTs, cloud technologies and wearable integrated devices, which empower patients to manage their health and disease in cooperation with their formal and informal caregivers, and with professional medical staff across different care settings, such as hospital and home. The presented service revolves around the use of two wearable inertial sensors, i.e. SensFoot and SensHand, for measuring foot and hand performance in the MDS-UPDRS III motor exercises. The devices were tested in medical settings with eight patients, eight hyposmic subjects and eight healthy controls, and the results demonstrated that this approach allows quantitative metrics for objective evaluation to be measured, in order to identify pre-motor/pre-clinical diagnosis and to provide a complete service of tele-health with remote control provided by cloud technologies. © 2016, IGI Global. All rights reserved

User engagement in mobile apps for people with schizophrenia: A scoping review

Over the past decade, there has been an increase in the number of mobile apps designed for mental health proposes and mHealth has been perceived as a promising approach to help people with schizophrenia to manage their condition. However, adoption rates are relatively low and long-term user engagement is a major issue. The aim of this study is to identify and better understand what strategies and factors may influence user engagement and facilitate prolonged use of apps for people with schizophrenia to better manage their illness. A scoping review was conducted in accordance with the Arksey and O’Malley scoping review framework and following PRISMA ScR guidelines. The sources consisted of searching four electronic databases. Rayyan software was used for this study selection process and a narrative approach was used to synthesize the extracted data. A total of 28 studies which met the inclusion criteria were identified. The engagement strategies included push notifications, message prompts, personalization, application customization, goal setting, game-like features, use of different multimedia formats, social connectedness, support (peers and professionals), reliability of content and quality of feedback received. Some demographic factors may influence adherence such as age, gender, education level and socioeconomic status. Other factors also may play a role impacting engagement: health status, data privacy and security, involvement in design process, incentives for participation, app usage fitting in the user routines, initial training, and constant technical support. Included studies present high heterogeneity in outcome measures and thresholds criteria to assess engagement. Understanding what influences engagement and how to measure it is essential to enhance the design of mobile apps and deliver scalable solutions to help people with schizophrenia better manage their illness in their real-world uptake.info:eu-repo/semantics/publishedVersio

Towards a personal at-home lab for motion video tracking in patients with Parkinson's disease

Many digital healthcare services now employ the opportunities of mobile and smart Internet technologies. The Internet is used to deliver such services as medical consultations, diagnosis, and prescriptions. The services are constructed and delivered in the ubiquitous style - anywhere, anytime, and using surrounding devices of our everyday life. In this paper, we discuss the opportunities of motion video tracking in at-home settings for a patient. Parkinson's disease (PD) serves as a case study. First, we define the problem of motion video tracking in PD patients. Then, we consider Internet-enabled methods for motion video tracking, which are essentially restricted with professional settings of a medical environment. Finally, we propose to create a personal at-home lab based on such cheap home-based cameras as any smartphone has. Our early experiment shows that such cameras provide reliable capture quality for the practical use in PD patient motion video tracking

The VESPA Project: Virtual Reality Interventions for Neurocognitive and Developmental Disorders

VESPA is a financed project supported by the Sicilian Regional Research and Development funds, and it is structured by the development, research and validation of Virtual Reality (VR) based application for the diagnosis and treatment of neurocognitive conditions. In particular, this article presents its characteristics, referred to as the first (2013-2015) and second (2021-ongoing) generations of VESPA, with particular reference to literature regarding the VR technology application and development, the VR treatment of neurocognitive conditions and prior versions of this intervention. Through a comprehensive review of the research conducted over the last 5 years, evidence has emerged supporting VESPA’s aim and scopes, highlighting how the application of VR can be considered to add value to typical rehabilitation/therapeutic paths. VESPA project generations are then presented in detail, including specific session/task battery characteristics, 2.5D, 3D and 5D typologies, system usability and architecture and pathological domain-based dynamics and features. The discussion about VESPA will highlight the current advantages along with limitations and future directions

Psychiatry in the Digital Age: A Blessing or a Curse?

Social distancing and the shortage of healthcare professionals during the COVID-19 pandemic, the impact of population aging on the healthcare system, as well as the rapid pace of digital innovation are catalyzing the development and implementation of new technologies and digital services in psychiatry. Is this transformation a blessing or a curse for psychiatry? To answer this question, we conducted a literature review covering a broad range of new technologies and eHealth services, including telepsychiatry; computer-, internet-, and app-based cognitive behavioral therapy; virtual reality; digital applied games; a digital medicine system; omics; neuroimaging; machine learning; precision psychiatry; clinical decision support; electronic health records; physician charting; digital language translators; and online mental health resources for patients. We found that eHealth services provide effective, scalable, and cost-efficient options for the treatment of people with limited or no access to mental health care. This review highlights innovative technologies spearheading the way to more effective and safer treatments. We identified artificially intelligent tools that relieve physicians from routine tasks, allowing them to focus on collaborative doctor-patient relationships. The transformation of traditional clinics into digital ones is outlined, and the challenges associated with the successful deployment of digitalization in psychiatry are highlighted

TechCare – Mobile Assessment and Therapy for Psychosis: Feasibility Study of an Intervention for Clients within the Early Intervention Service

Background: Mobile digital health technologies, mHealth, is a growing field globally with a potential to improve mental health. Technological advances have shown promise across healthcare and particularly when delivering interventions for mental health problems such as psychosis. The use of mobile devices provides greater autonomy to service users who would otherwise be seen as a ‘hard to reach group’, with complex relationships between psychotic experiences, trust and engagement with services. A non-stigmatising approach is implicit within technological developments, as many service users experience mental health stigma, which can compound problematic engagement, treatment adherence and outcomes. This study was an original piece of work and has created new insights into mHealth technologies for individuals experiencing psychosis. Aim: The aim of the project was to develop and conduct a feasibility study of the mobile phone application (App) ‘TechCare’ for individuals with psychosis in the North West of England. Methods/Design: The feasibility study followed the National Institute of Health Research (NIHR) guidance on feasibility study design and consisted of both qualitative and quantitative components. The study was conducted across three strands as follows: 1) Qualitative work & Systematic review; 2) Test-run and Intervention refinement (developing the TechCare App); 3) Feasibility trial. The TechCare App assessed participants’ symptoms and responses and provided for a personalised guided self-help based psychological intervention, with the aim of reducing participants’ symptoms. In Strand 1 of the study, 16 service users and 16 health professionals from Lancashire Care NHS Foundation Trust, Early Intervention Service (EIS) were recruited to explore their experience of psychosis and give their opinions on the existing evidence based treatment (Cognitive Behavioural Therapy (CBT)) and how the mobile App could be developed (service users and staff). In Strand 2, a test-run with a small number (n= 4) of participating service users, was conducted to refine the mobile intervention (TechCare). Finally, in Strand 3 the TechCare App was examined in a feasibility study with a total of 12 service users. The study was also registered on ClinicalTrials.gov Identifier: NCT02439619. Results: The systematic review, found 7 studies which met the inclusion criteria, from a total of 5690 records. The included studies describing the feasibility of using mHealth technologies for psychosis, functionality and access to mHealth interventions and study outcomes. Overall, the systematic review results suggested that mHealth for psychosis is acceptable and feasible in the target population. Furthermore, the TechCare App had been developed, working alongside service users who consulted on the development of the App. The qualitative result of the study showed that the TechCare App was found to be an acceptable means of receiving interventions for the service users, with key themes around, the participant’s experience of using the App, the further development and refinement of the intervention and the usability of the intervention. In addition, the Strand 3 feasibility study, results showed that out of the 12 participants, a total of 83.33% of participants completed the 6 week intervention. Overall participants responded to the App notifications on average 2.95 time per day (Range: 0-11), with a reduction in average scores on the TechCare App, from baseline to week 6 for the depression scale questions (Week 1, M=29.13 (SD=18.29); Week 6 was M=17.50 (SD=11.92)) and paranoia scale questions (Week 1 M=38.00, SD=28.27; Week 6, M=33.92, SD=27.88). Discussion: The results of the study show promise in the feasibility and acceptability of the TechCare App. Based on these results I can now take the research forward as part of a future clinical and cost effectiveness trial. It has been suggested that there is a need, for a rapid increase in the evidence base for the clinical effectiveness of digital technologies, considering mHealth research can potentially be helpful in addressing the demand on mental health services in the UK and mental health inequalities