VIMES : A Wearable Memory Assistance System for Automatic Information Retrieval

The advancement of artificial intelligence and wearable computing triggers the radical innovation of cognitive applications. In this work, we propose VIMES, an augmented reality-based memory assistance system that helps recall declarative memory, such as whom the user meets and what they chat. Through a collaborative method with 20 participants, we design VIMES, a system that runs on smartglasses, takes the first-person audio and video as input, and extracts personal profiles and event information to display on the embedded display or a smartphone. We perform an extensive evaluation with 50 participants to show the effectiveness of VIMES for memory recall. VIMES outperforms (90% memory accuracy) other traditional methods such as self-recall (34%) while offering the best memory experience (Vividness, Coherence, and Visual Perspective all score over 4/5). The user study results show that most participants find VIMES useful (3.75/5) and easy to use (3.46/5).Peer reviewe

Estado del arte del proyecto

The aim of REMIND is to create an International and Intersectoral network to facilitate the exchange of staff to progress developments in reminding technologies for persons with dementia that can be deployed in smart environments. The consortium is comprised of an International network of 7 academic beneficiaries, 5 nonacademic beneficiaries and 4 partners from Third Countries, all of whom are committed to progressing the notion of reminding technologies within smart environments. The focus of REMIND is to develop staff and beneficiary/partner skills in the areas of user centered design and behavioral science coupled with improved computational techniques which in turn will offer more appropriate and efficacious reminding solutions. This will be further supported through research involving user centric studies into the use of reminding technologies and the theory of behaviour change to improve compliance of usage. Research objectives will be focused within the domain of smart environments. A smart environment can be viewed as having the ability to sense its surroundings through embedded sensors and following processing of the sensed information, adjust the environment through actuators to offer an improved experience for the inhabitant. Even though the availability, cost, size and battery life of sensing technology have all improved in recent years, the uptake of real smart environments has been limited. This is mainly related to the effort required to support the technical deployments and the lack of a business model to support a service provider capable of offering support to a large number of environments. In addition, there is a limit to the amount of scenarios which can be facilitated by such environments; this limit is directly related to the number of sensors availabl

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

Pervasive assistive technology for people with dementia : a UCD case

Smart mobile and wearable technology offers exciting opportunities to support people with dementia (PwD). Its ubiquity and popularity could even benefit user adoption – a great challenge for assistive technology (AT) for PwD that calls for user-centred design (UCD) methods. This study describes a user-centred approach to developing and testing AT based on off-the-shelf pervasive technologies. A prototype is created by combining a smartphone, smartwatch and various applications to offer six support features. This is tested among five end-users (PwD) and their caregivers. Controlled usability testing was followed by field testing in a real-world context. Data is gathered from video recordings, interaction logs, system usability scale questionnaires, logbooks, application usage logs and interviews structured on the unified theory of acceptance and use of technology model. The data is analysed to evaluate usability, usefulness and user acceptance. Results show some promise for user adoption, but highlight challenges to be overcome, emphasising personalisation and familiarity as key considerations. The complete findings regarding usability issues, usefulness of support features and four identified adoption profiles are used to provide a set of recommendations for practitioners and further research. These contribute toward UCD practices for improved smart, pervasive AT for dementia

Promoting the adoption of assistive technologies to aid with spatial orientation in dementia care

Introduction: In dementia care, locating technologies are a type of assistive technology that hold the potential to improve the quality of life of persons with dementia and their care partners by assisting in the management of spatial orientation impairments and wandering. Although many products are commercially available, their adoption remains low. To better understand how to promote their adoption, we examined user experience and clinical effectiveness resulting from product use and explored barriers to their adoption. Methods: In a first user experience study, a prototype locating technology was tested for four weeks by 17 dyads composed of persons with dementia and their care partners. In a second user experience study, two similar commercially available locating technologies were tested for four weeks each by another 17 dyads. User experience was examined with ratings of product usability, product functions and product features. Clinical effectiveness, frequency of use, purchase willingness, and product satisfaction were assessed with various scales. In a third qualitative focus group interview study with 22 interdisciplinary professional stakeholders, we explored views on the barriers to their adoption, as well as views on services and information dissemination strategies. Results: In the first study, the prototype was rated fairly in terms of usability, product functions and product features. However, usability ratings significantly decreased after four weeks. In the second study, ratings of usability, as well as of several product functions and product features were significantly more favourable for one of the two tested commercial products. Clinical effectiveness was not found in either study. In the third study, the main adoption barriers were based on unclear benefits and ethical concerns, as well as limitations in awareness, technology, product characteristics, and capital investments. Key services and information dissemination strategies centred on digital autonomy support, emergency support, information dissemination actors, product acquisition, and product advertising. Discussion: Results from both user experience studies indicate that focusing on specific product functions and features might substantially improve user experience. This might translate to measurable clinical effectiveness and higher adoption rates. Results from our qualitative study indicate that not only product characteristics and the technology itself impact adoption. Indeed, focusing on services and information dissemination strategies around products warrants closer attention as they might markedly improve adoption.Einleitung: Ortungssysteme in der Demenzversorgung gelten als eine vielversprechende Art von assistierender Technologie, um die Lebensqualität von Menschen mit Demenz und ihren Pflegepartnern zu verbessern, indem sie dabei helfen räumliche Orientierungsstörungen und Wanderungen zu bewältigen. Ihre Verwendung bleibt jedoch trotz der Verfügbarkeit vieler kom-merzieller Produkte gering. Um besser zu verstehen, wie ihre Verwendung gefördert werden kann, haben wir die Nutzererfahrung und klinische Wirksamkeit, die sich aus der Produktnutzung ergeben sowie die Barrieren für ihre Einführung untersucht. Methoden: In einer ersten Nutzererfahrungsstudie wurde ein Prototyp Ortungssystem vier Wo-chen lang von 17 Dyaden bestehend aus Menschen mit Demenz und ihren Pflegepartnern ge-testet. In einer zweiten Nutzererfahrungsstudie wurden zwei ähnliche kommerziell erhältliche Or-tungssysteme jeweils vier Wochen lang von weiteren 17 Dyaden getestet. Die Nutzererfahrung wurde mit Bewertungen der Benutzerfreundlichkeit, Produktfunktionen und Produkteigenschaften untersucht. Klinische Wirksamkeit, Nutzungshäufigkeit, Kaufbereitschaft und Produktzufrieden-heit wurden mit verschiedenen Skalen bewertet. In einer dritten qualitativen Fokusgruppeninter-viewstudie mit 22 interdisziplinären professionellen Stakeholdern untersuchten wir Ansichten zu den Barrieren für ihre Verwendung sowie zu Dienstleistungen und Strategien zur Informationsverbreitung. Ergebnisse: In der ersten Studie waren die Bewertungen der Benutzerfreundlichkeit, Produkt-funktionen und Produkteigenschaften mittelmäßig. Die Bewertung der Benutzerfreundlichkeit ging jedoch nach vier Wochen deutlich zurück. In der zweiten Studie fielen die Bewertungen der Benutzerfreundlichkeit sowie einiger Produktfunktionen und Produkteigenschaften bei einem der beiden getesteten Produkte deutlich besser aus. Klinische Wirksamkeit wurde in keiner der Studien gefunden. In der dritten Studie konzentrierten sich die wichtigsten Einführungsbarrieren auf unklare Vorteile und ethische Bedenken sowie auf bewusstseins-, technologisch-, produktmerkmal- und kapitalinvestitionsbasierte Einschränkungen. Dienstleistungen und Strategien zur Informationsverbreitung konzentrierten sich auf Unterstützung von digitaler Autonomie, Notfallunterstützung, Akteure der Informationsverbreitung, Produktakquisition und Produktwerbung. Diskussion: Die Ergebnisse beider Studien zur Nutzererfahrung zeigen, dass die Nutzererfah-rung durch die Optimierung bestimmter Produktfunktionen und Produkteigenschaften erheblich verbessert werden kann. Dies könnte zu einer messbaren klinischen Wirksamkeit und höheren Verwendung führen. Die Ergebnisse unserer qualitativen Studie zeigen, dass die Verwendung durch mehr als die Produktemerkmale und die Technologie selbst bestimmt wird. Deshalb ist eine gezielte Fokussierung auf Dienstleistungen und Strategien zur Informationsverbreitung rund um Ortungssysteme notwendig, da sie die Verwendung deutlich verbessern könnte

Digital support for self-management and meaningful activities of people with mild dementia:Development, implementation and feasibility of a person-centred touch-screen intervention

This thesis reports on the research that was conducted to develop and pilot test a person-centred touchscreen-based program (FindMyApps intervention) that supports people with mild dementia and their informal carers in how to use a tablet and apps for self-management and meaningful activities. The program consists of the FindMyApps training for informal carers in supporting people with mild dementia in using a tablet and the FindMyApps selection tool designed to help people with mild dementia find apps for self-management and meaningful activities that fit their needs, wishes and abilities. The program was developed following the Medical Research Council (MRC) Framework for the design and evaluation of complex interventions and in co-creation with end users. The chapters of this thesis describe the first three phases of this framework i.e.: the preclinical or theoretical phase (0); the modelling phase (I) and the exploratory trial (II). The execution of an RCT (III), and further implementation (IV) in case the intervention proves effective, are beyond the scope of this thesis. In the first phase user needs studies were performed to identify user requirements for desired self-management and meaningful activities and to identify user-requirements related to the use of apps. Eight focus groups were performed in which people with mild cognitive impairment (MCI) or mild dementia (n=13) and informal carers (n=15) participated. We also conducted a literature review to explore which training interventions are most effective for people with mild dementia in (re)learning how to use technologies, including handheld touchscreen devices. An electronic search was conducted in the following databases: PubMed, APA PsycInfo (EBSCO) and CINAHL (EBSCO). In total 16 studies met the inclusion criteria. Our review contributed to the growing amount of promising evidence on the potential impact of Errorless learning training interventions for people with mild to moderate dementia in (re)learning how to use technology. Based on these results we developed the FindMyApps training. In the second phase of the framework we developed a first concept of the FindMyApps selection tool based on identified user requirements. To ensure its usability, the web-based tool was developed using a ‘user-participatory design’ involving the close collaboration of potential users, a development team (researchers, developers and designers) and an expert team (experts in person-centred dementia care and ICT). In three short iterative rounds – so called ‘sprints’ – the users (people with dementia (n=8) and (in)formal carers (n=10)) were invited to test whether the prototypes were in line with their needs, wishes and abilities. This generated important insights into user-interface aspects relating to (i) useful content and (ii) a user-friendly tool design. In the third phase we pilot tested the FindMyApps intervention by means of individual semi-structured interviews and a pilot randomized controlled exploratory trial. Twenty people with mild dementia and informal carer dyads were randomly assigned to the FindMyApps group (n=10), receiving either the FindMyApps training and selection tool, or a control condition (n=10), receiving only a short tablet training. Pre- and post-test measurements at a three month follow-up, consisted of questionnaires and post-test semi-structured interviews. Based on the qualitative results and the effect sizes on the outcomes measured in this study, we consider that the FindMyApps intervention has the potential to positively influence the self-management and engagement in meaningful activities in people with dementia. Future studies with a larger sample should better indicate whether this expectation can be confirmed. The intervention will be further improved and tested in a larger pilot-RCT study and its effectiveness subsequently evaluated in a definite RCT

Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials