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D4.1 Device Selection Report D4.1 Device Selection 806999 – RADAR-AD Remote Assessment of Disease and Relapse: Alzheimer’s disease WP4 - Development of a technology-enabled system to measure identified functional domains via smartphone, wearable and fixed home-based sensors D4.1 Device Selection Report Publishable Summary Wearables and smart devices are increasingly integrated into our lives, flooding the retail market and literature research. Besides lifestyle applications, they could be utilized as digital biomarkers in elderly care, through activity and behavioral monitoring. In this deliverable, we selected the most appropriate choices of wearable and smart devices, available in literature and the market, considering the three Tiers of trials that will be carried out for the RADAR-AD project. Consequently, we first examined the available sources for all current wearables, smart home (ambient) devices and smartphone apps. Their most important criteria, pros and cons and specs are fully listed for each Tier and category. Then, we produced a shortlist table of suggestions, including devices and apps that match the project’s needs. In the end, all partners conversed through biweekly WP4 device selection track calls, biweekly WP4-wide calls and several WP5 and cross- WP calls, as well as physical and remote Project Steering Board meetings, so as to unanimously make a final selection to be used in each respective Tier of the project. The selection also takes into account functional domains from WP2 as well as Patient Advisory Board suggestions and probe test outcomes. 1 D4.1 Device Selection DoW Extract Task 4.1: Device Evaluation, Selection and Refinement to Digitally Measure Functional Tasks (months 1 - 18, CERTH, OXF, JANSSEN, Takeda, Lilly, Novartis) The task entails two main subtasks, closely connected to one another, in order to select, bench test, extract features and realistically configure pilot devices according to instructions from WP2 - for WP5. Device selection Device selection entails: a) the creation and rigorous update of a prioritised list of devices from the market and literature, b) initial selection from the list by ICT and clinical experts to meet functional task requirements of WP2, c) an initial laboratory assessment bench-test by experts and testers to adjust priorities and shortlist devices for the Tier 3 pilot, d) systematic refinement according to the Tier 3 pilot and delivery of the final selection to WP5. In detail, a) a list of devices with vendor, programmability (API), measurement type and scale, battery life, performance and comfort parameters will be organized, continuously populated and extended with both wearable and ambient devices. R & D devices, usually larger and less comfortable but also retail devices will be considered, such as presence, motion, object & utility usage, beacons, as they can be repurposed in a medical context for behavioural, cognitive and functional monitoring. Sources utilized will include the IMI ROADMAP review, interest groups such as those organized by C-Path, and databases like Vandrico. Given the list, b) experts will choose an initial set of devices by rating them based on knowledge and experience (including RADAR-CNS) with criteria such as: comfort, usefulness, functionality, unobtrusiveness, security and privacy features, programmability, robustness and accuracy to determine suitability. They will additionally assign a study tier (1, 2, or 3) to each device. The initial list will be c) bench-tested to pragmatically evaluate the above criteria in short trials with experts and testers, which will also provide standardized usability and user acceptance feedback1 that will be used to shortlist devices for the pilot in this Task (see next section). After this pilot, this task will iteratively d) incorporate full technological (precision, response time etc.) and clinical (suitability for the functional tasks, acceptance, usability2) feedback and metadata into the list and produce the final selection for WP5, ensuring that not only data science, but also a deep clinical understanding of the disease have contributed towards the outcome. Lightweight Piloting of Candidate Devices with Health Age-matched An important part of device selection will be the evaluation of their suitability through a lightweight piloting exercise. This can use healthy age-matched controls and would take place in free-living environments. This short evaluation exercise would provide the opportunity to understand the user experience provided by each device and gather data from a real free-living situation. Ethical considerations will be explored, and guidance will be sought for the pilot. This application of this guidance will then be extended to cover the Tier 3 study in WP5 also to be undertaken by CERTH. Related Deliverables: D4.1.1 Device Selection Report for Tiers 1, 2 & 3 of the WP5 study (M12): Presents the device selection process, criteria and outcomes with the final choice of devices for pilots of all tiers. D4.1.2 Device Selection Trials, clinical and ethical protocol for Tier 3 study to be used in WP5. (M18) According to the DoW, this report, namely D4.1.1., refers to Device Selection activities while lightweight piloting will be reported in D4.1.2. 1 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982- 1003. 2 Brooke, J. (1996). "SUS: a "quick and dirty" usability scale". In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & A. L. McClelland. Usability Evaluation in Industry, London: Taylor and Francis 2 D4.1 Device Selection Contents 1 Introduction ........................................................................................................... 3 2 Search and Selection Methods................................................................................ 5 3 Results.................................................................................................................... 5 3.1 Literature Search ............................................................................................ 5 3.2 Tier 1 – Wearable Sensors ............................................................................... 7 Tier 1 – Final Selection ............................................................................................ 8 3.3 Tier 2 – Home Sensors .................................................................................. 11 Tier 2 – Final Selection .......................................................................................... 12 3.4 Tier 3 – Smart Home ..................................................................................... 13 Tier 3 – Final Selection .......................................................................................... 14 4 Conclusions .......................................................................................................... 16 5 References ........................................................................................................... 17 Appendix ...................................................................................................................... 22 1. A – Tier 1: Wearable Market Search ...................................................................... 22 1. B – Tier 1: Wearables Listed Market Selection ...................................................... 24 1. C – Tier 1: Apps Market Search ............................................................................. 25 1. D – Tier 1: Apps Listed Market Selection ............................................................... 27 1. E – Tier 1: Wearable Cameras Market Search ........................................................ 28 1. F – Tier 1: Wearable Sensors Categorization ......................................................... 30 1. G – Tier 1: Wearable Literature Search.............................................................. 31 1. H – Tier 1: Apps Literature Search ......................................................................... 33 1. I – Tier 1: Wearable Cameras Literature Search..................................................... 34 2. A – Tier 2 & 3: Smart Home Devices Market Search .............................................. 35 2. B – Tier 2 & 3: Smart Home Apps Market Search................................................... 39 2. C – Tier 2 & 3: Ambient Sensors Categories ........................................................... 40 2. D – Tier 2 & 3: Literature Search Regarding IoT Wearable Sensors and Devices for Eldercare. ................................................................................................................. 41 2. E – Tier 2 & 3: Apps for Dementias Literature Search ............................................ 42 2. F – Tier 2 & 3: Review of Case Studies of IoT Wearable Sensors and Devices for Eldercare .................................................................................................................. 44 2. G – Tier 2 & 3: Smart Home Apps Literature Search .............................................. 45 1 Introduction When assessing the level of difficulty and lack of function in daily living, we usually rely on feedback from family caregivers. This assessment may be influenced by subjective, imperfect recall and, thus, is not reliable to estimate the level of impairment across individuals. This absence of objective data could be mitigated following the advances in digital technology. Smartphones, currently owned by 9 out of 10 people, can help
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