Caregiver Assessment Using Smart Gaming Technology: A Feasibility Study

Garrett Goodman, Tanvi Banerjee, William Romine, Cogan Shimizu, Jennifer Hughes

Research output: Contribution to journalArticlepeer-review

Abstract

© 2019 IEEE. 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 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.

Original languageAmerican English
JournalIEEE International Conference on Fuzzy Systems
DOIs
StatePublished - Jun 1 2019

Keywords

  • dementia caregiver, fuzzy inference system, gaming technology, machine learning, task performance

Disciplines

  • Computer Sciences
  • Engineering

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