Caregiver Assessment Using Smart Gaming Technology: A Preliminary Approach

Using technology to assist both dementia patients and caregivers is of interest to caregivers, professionals, and treatment providers. This study looks to develop a system for detecting task performance of caregivers for dementia patients. In this interdisciplinary study, we create CAST (Caregiver Assessment using Smart Technology), a mobile application that personalizes a traditional word scramble game using a Fuzzy Inference System (FIS) optimized using Genetic Algorithms (GA). The FIS is implemented for assigning individualized difficulties to words for each user independently. Using CAST, we match the relative level of difficulty with the individual’s ability and functions of the word for evaluation. In this study, we build an FIS for measuring word difficulty, determine how well does such a system perform, and finally check the feasibility of categorizing words that have similar discriminating capabilities. We report our preliminary analysis on the use of the FIS, with responses in a word scramble game from 48 participants. Such a system can be used as an assessment tool to evaluate the task performance of the caregiver. With a personalized difficulty system in place, we can detect negative decline of task performance which can be linked to stress levels, and thus can be a factor to detecting caregiver burnout.