Prompting Systems for older adults with dementia/MCI

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Assistive prompting technologies have the potential to support older adults in early stages of dementia, or Mild Cognitive Impairment (MCI), in activities they usually find difficult to complete by themselves. Successful adoption of prompting technologies (e.g., audio, video) can contribute to independence in executing Activities of Daily Living (ADL), such as laundry and cooking, for such people with dementia (PwDM). However, existing prompting systems are proof of concepts developed in controlled lab settings. Needed are prompting technologies that adapt to the actual context of use and needs of older adults with MCI without having to adjust settings, change versions or use hacks. My research team will respond to the novel usability challenge through field research with older adults with MCI. We will use the research in and through design method, a variant of Research through Design (RtD), by which a researcher develops interactive elements to generate insights into how to carry out the design itself, while also iterating user observations, codesign, focus groups and interviews to study resulting prompts and actions; and developing a series of artefacts, such as sketches and prototypes of interactive prompting systems. The research setting will centre on blended environments (BE), in which the virtual environment integrates with the user's physical world. Qualitative data (verbal protocols, surveys, behaviour observation, facial expressions, body movements and gaze) and quantitative data (technology familiarity scores, cognitive assessment scores, time taken to complete a task) will be analyzed. HQP will work in a multidisciplinary environment (Health, Occupational Therapy, Design, Computer Science) that ensures HQP equity, diversity and inclusion (EDI) by recruiting through the York University-TD Community Engagement Centre and the highly diverse Black Creek community of university learners in Toronto. This research program will drive pivotal real-world advances in interactive prompting. Building on my lab's work in designing BE for and with older adults and children, my research team will study task sequencing to inform when and how prompts should be generated and interaction modalities that 1) contribute to continuous perception-action loops; 2) respond to older adults' technology needs and comfort levels and in the context of their impairments; and 3) that will detect/adjust automatically to impairment level and type of activity. The outcomes under the DG--prototypes and frameworks that will be representative of types of gestural actions and multimodal prompts needed, along with an understanding of when and how these prompts should be generated--will be integrated after the DG into a high-fidelity prototype that will ultimately be developed into whole new assistive/prompting systems. Outcomes may also be transferrable to development of technologies in outdoor settings, such as in accident avoidance while driving.