Caregiver Assessment Using Smart Gaming Technology: A Preliminary Approach
This work addresses the need for accessible pre-diagnostic tools to improve care quality for dementia patients and caregivers, but it is incremental as it builds on existing gaming and optimization methods.
The researchers tackled the problem of non-invasively assessing task performance for dementia caregivers by developing CAST, a mobile app that personalizes a word scramble game using a Fuzzy Inference System optimized with a Genetic Algorithm, with preliminary results analyzed for determining task difficulty in their participant cohort.
As pre-diagnostic technologies are becoming increasingly accessible, using them to improve the quality of care available to dementia patients and their caregivers is of increasing interest. Specifically, we aim to develop a tool for non-invasively assessing task performance in a simple gaming application. To address this, we have developed Caregiver Assessment using Smart Gaming Technology (CAST), a mobile application that personalizes a traditional word scramble game. Its core functionality uses a Fuzzy Inference System (FIS) optimized via a Genetic Algorithm (GA) to provide customized performance measures for each user of the system. With CAST, we match the relative level of difficulty of play using the individual's ability to solve the word scramble tasks. We provide an analysis of the preliminary results for determining task difficulty, with respect to our current participant cohort.