COLAEVA: Visual Analytics and Data Mining Web-Based Tool for Virtual Coaching of Older Adult Populations

The global population is aging in an unprecedented manner and the challenges for improving the lives of older adults are currently both a strong priority in the political and healthcare arena. In this sense, preventive measures and telemedicine have the potential to play an important role in improving the number of healthy years older adults may experience and virtual coaching is a promising research area to support this process. This paper presents COLAEVA, an interactive web application for older adult population clustering and evolution analysis. Its objective is to support caregivers in the design, validation and refinement of coaching plans adapted to specific population groups. COLAEVA enables coaching caregivers to interactively group similar older adults based on preliminary assessment data, using AI features, and to evaluate the influence of coaching plans once the final assessment is carried out for a baseline comparison. To evaluate COLAEVA, a usability test was carried out with 9 test participants obtaining an average SUS score of 71.1. Moreover, COLAEVA is available online to use and explore.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 769830

RAISE Scientific Community

<p>This presentation showcases the importance of RAISE's Scientific Community, as a beacon of Open Science practices and knowledge sharing tools. Furthermore, the presentation highlights the benefits of the RAISE System for the scientific community such as addressing the conceerns of the user rather than creating new, being intuitive, easy to be used, useful and in accordance with the current culture. </p> <p>The presentation was made during the RAISE Webinar: Unveiling the Power and Functionality of the RAISE System, which was held on January 16th 2024 and organized by <a href="https://www.openaire.eu/">OpenAIRE</a> and <a href="https://medphys.med.auth.gr/">AUTH</a>, with the invaluable support of the <a href="https://raise-science.eu/consortium-1/">RAISE consortium</a>.</p> <p>Participants were given an exclusive opportunity to delve into the inner workings of the RAISE system and experience its unique approach firsthand. Unlike traditional methods, RAISE brings the processing algorithm, compact in size, directly to the dataset, eliminating the need to download extensive datasets to the local computer where the algorithm resides. This innovative approach promises efficiency and convenience, marking a significant stride in data processing methodologies.</p> <p>The event facilitated an open discussion that allowed participants to share their perspectives and provide valuable insights for the ongoing improvement of the RAISE system. </p&gt

Harmonizing Living Lab Services: Towards consolidated service portfolio

Living labs share common elements but have multiple different implementations. Prior studies have revealed a lack of research on effective management approaches for living labs. Service harmonization is suggested as an approach to improve efficiency and to ensure the consistency of services and results regardless of the service provider. This study evaluates the living lab service portfolio and proposes a harmonized service categorization to contribute to ongoing discussions on living lab harmonization. The suggested framework consists of 18 services for Customer acquisition, 13 for Detailed project planning and 29 for Project implementation and dissemination phase as well as 9 repositories in Innovation ecosystem orchestration. Services are also classified into Back-office (N=29), R&D services (N=21), and 3) Auxiliary services (N=4)

Categorizing digital data collection and intervention tools in health and wellbeing living lab settings: A modified Delphi study

Background: Health and Wellbeing Living Labs are a valuable research infrastructure for exploring innovative solutions to tackle complex healthcare challenges and promote overall wellbeing. A knowledge gap exists in categorizing and understanding the types of ICT tools and technical devices employed by Living Labs. Aim: Define a comprehensive taxonomy that effectively categorizes and organizes the digital data collection and intervention tools employed in Health and Wellbeing Living Lab research studies. Methods: A modified consensus-seeking Delphi study was conducted, starting with a pre-study involving a survey and semistructured interviews (N=30) to gather information on existing equipment. The follow-up three Delphi rounds with a panel of living lab experts (R1 N=18, R2 - 3 N=15) from 10 different countries focused on achieving consensus on the category definitions, ease of reading, and included subitems for each category. Due to the controversial results in the 2nd round of qualitative feedback, an online workshop was organized to clarify the contradictory issues. Results: The resulting taxonomy included 52 subitems, which were divided into three levels as follows: The first level consists of ’devices for data monitoring and collection’ and ’technologies for intervention.’ At the second level, the ’data monitoring and collection’ category is further divided into ’environmental’ and ’human’ monitoring. The latter includes the following third-level categories: ’biometrics,’ ’activity and behavioral monitoring,’ ’cognitive ability and mental processes,’ ’electrical biosignals and physiological monitoring measures,’ ’(primary) vital signs,’ and ’body size and composition.’ At the second level, ’technologies for intervention’ consists of ’assistive technology,’ ’extended reality – XR (VR & AR),’ and ’serious games’ categories. Conclusion: A common language and standardized terminology are established to enable effective communication with living labs and their customers. The taxonomy opens a roadmap for further studies to map related devices based on their functionality, features, target populations, and intended outcomes, fostering collaboration and enhancing data capture and exploitation

Towards a Taxonomy for Health Living Lab Data Collection Devices

Living Labs in the Health and Wellbeing domain have the ability to integrate ICT tools and other technical devices into the research and innovation withing this domain. However, there is there is no systematic understanding what kind of ICT tools and other technical devices are used by living labs and how they can be categorized. This study presents the creation of a taxonomy for systematically grouping data and devices used in living lab concept, as well as the technical representation framework. The analysis concluded with 8 categories and 63 subcategories of data that are gathered from Living Labs using various technologies. The taxonomy and the included data model enables Living Lab researchers and customers quickly find what tools they need for their research while supporting open data movement among the living labs

Harmonizing the evaluation of living labs: a standardized evaluation framework

Candidate LLs joining LL associations and networks (ENoLL, Forum LLSA...) undergo qualityassessment processes based on specific criteria and evaluation frameworks to guarantee members meet their LL standards. Currently, limited attention is paid on how such evaluation methods can contribute to future LL-performance. The need to deeper understand the architectural aspects of LLs and further study effective management-approaches has been raised by other authors. Schuurman (2015) proposed a macro–meso-micro-level approach for classifying LLs. Despite its potential value, this three-level analysis approach has not yet been fully recognized in existing LL evaluation frameworks. The adoption of a harmonized macro-meso-micro evaluation approach, with a clear focus on the macro-level could support the development of LL towards sustainability, impact and efficacy. This paper aims to define a set of harmonized weighted criteria for a comprehensive LL evaluation framework to be used for assessing LLs on all three levels based on multi-method research approaches

A secure data publishing and access service for sensitive data from Living Labs: enabling collaboration with external researchers via shareable data

Intending to enable a broader collaboration with the scientific community while maintaining privacy of the data stored and generated in Living Labs, this paper presents the Shareable Data Publishing and Access Service for Living Labs, implemented within the framework of the H2020 VITALISE project. Building upon previous work, significant enhancements and improvements are presented in the architecture enabling Living Labs to securely publish collected data in an internal and isolated node for external use. External researchers can access a portal to discover and download shareable data versions (anonymised or synthetic data) derived from the data stored across different Living Labs that they can use to develop, test, and debug their processing scripts locally, adhering to legal and ethical data handling practices. Subsequently, they may request remote execution of the same algorithms against the real internal data in Living Lab nodes, comparing the outcomes with those obtained using shareable data. The paper details the architecture, data flows, technical details and validation of the service with real-world usage examples, demonstrating its efficacy in promoting data-driven research in digital health while preserving privacy. The presented service can be used as an intermediary between Living Labs and external researchers for secure data exchange and to accelerate research on data analytics paradigms in digital health, ensuring compliance with data protection laws.This research was partly funded by the VITALISE (Virtual Health and Wellbeing Living Lab Infrastructure) project, funded by the Horizon 2020 Framework Program of the European Union for Research Innovation (grant agreement 101007990)

A New Approach for Ageing at Home: The CAPTAIN System

Our work exhibits how previous projects on the Active and Healthy Ageing field have advanced to the conception of CAPTAIN, a radically new approach towards increased enduser acceptance. The goal is to create intuitive technology that does not require specific skills for interaction and blends in with real life. CAPTAIN will be co-designed by all types of stakeholders, including older adults, involved in all stages, from the initial design to delivery of the final syste

First Workshop on Multimodal e-Coaches

This preprint follows ACM policy: “Authors who publish with ACM have the freedom to post peer-reviewed pre-print versions of their papers to personal websites and institutional repositories. They can add a single-click link to their final published papers, and re-use any portion of their published work with the inclusion of a citation and DOI link. Authors can also post on any repository legally mandated by the agency funding the research on which the work is based, and on any non-commercial repository or aggregation that does not duplicate ACM tables of contents/substantially duplicate an ACM-copyrighted volume or issue” (https://authors.acm.org/author-resources/author-rights.) 2e-Coaches are promising intelligent systems that aims at supporting human everyday life, dispatching advice through different interfaces, such as apps, conversational interfaces and augmented reality interfaces. This workshop aims at exploring how e-coaches might benefit from spatially and timemultiplexed interfaces and from different communication modalities (e.g., text, visual, audio, etc.) according to the context of the interaction.The NESTORE, SAAM, CAPTAIN, HOLOBALANCE, EMPATHIC, MENHIR, vCare projects are supported by the European Commission under the Horizon 2020 programmes SC1-PM-15-2017 H2020-MSCA-RISE-2018, and H2020-1.3.3, respectively through the project grants N.769643, 769661, 769830, 769574, 769872, 823907, 769807. The authors want to thank their respective Consortia. The opinions expressed in this paper are those of the authors and are not necessarily those of the project partners or the European Commission