A Gamified Approach to Cognitive Assessment with Machine Learning Based Predictions
认知
计算机科学
认知评估系统
认知障碍
人工智能
机器学习
心理学
神经科学
作者
Alexander I. F. Simpson,Yongjie An,Jacob Estep,Abhijeet Saraf,John Raiti
标识
DOI:10.1109/ghtc55712.2022.9910615
摘要
Cognitive Assessment is an important method for identifying cognitive impairment in individuals, and diagnosing diseases such as Alzheimer’s disease. However, it is usually performed using paper-based assessment, which can be frustrating and unengaging for patients. Low engagement can lead to inaccuracies and anomalous results. This paper aims to address this issue by taking a gamified approach to cognitive assessment. Using a physical prototype of a wack-a-mole inspired game, we accurately predicted cognitive ability of players using an SVR Machine Learning model. This model used inputs from participants playing the game including reaction times, in-game scores and heart rate, achieving an R-squared of 0.689 (3sf).