Investigator:
Archna Bhatia, Institute for Human & Machine Cognition, George Sperling, UCI.
MassAITC Cohort: Year 2 (AD/ADRD)
Word retrieval issues, experienced by aging adults in general, severely affect those with Alzheimer’s Disease and Related Dementias (ADRD), leading to frustration, embarrassment, loss of confidence, anxiety and avoidance of social interactions, thus influencing their personal, psychological and social life activities and increasing burden on their caregivers. This project aims to develop an Intelligent Cognitive Assistant (ICA) that provides support to these individuals in real-time word retrieval and personalized training to enhance their word retrieval, in order to support key activities of daily living involving communication and social connectivity and thus improve their QoL and lower their caregivers’ burden.
The proposed one-year project’s objectives include developing the proposed Intelligent Cognitive Assistant, testing it’s usability and evaluating its appropriateness/relevance of responses/training to the individual users. Usability testing will involve alpha-testing the participatory design of ICA with 10-20 volunteers for six months who will iteratively provide design feedback to inform further developments/improvements in usability of the ICA interfaces. For a robust performance of the ICA system, a wide range of participants with incipient ADRD and/or MCI (n=20) will evaluate its response appropriateness/relevance to them longitudinally for three months through a pilot study. The outcome measures will include items such as participants’ satisfaction with ICA in different modes (data acquisition, assistance and training), ease of use, interfaces working as expected, appropriateness of responses and training, and improvements in these measures with longitudinal use of ICA.
The developed ICA application will provide cognitive orthosis to elderly individuals with ADRD in terms of real-time word retrieval support and automated individualized training to strengthen their word-context associations for retrieval, which will support them in their key activities of daily living, cognitive skills as well as communication and social connectivity, thus improving their QoL and reducing caregivers’ burden. Additionally, the usability testing and the pilot study will advance our understanding of aspects of AI-enabled mobile technologies that interact with users in ways that make such technologies more accessible and responsive to users’ needs.