脑电图
计算机科学
语音识别
听力学
人工智能
模式识别(心理学)
心理学
医学
神经科学
作者
Alaa Eddin Alchalabi,Mohamed Elsharnouby,Shervin Shirmohammadi,Amer Nour Eddin
出处
期刊:IEEE International Symposium on Medical Measurements and Applications
日期:2017-05-07
被引量:6
标识
DOI:10.1109/memea.2017.7985895
摘要
Attention Deficit Hyperactivity Disorder (ADHD), characterized by the lack of attention and focus, is one of the most spread cognitive disorders. Since electroencephalogram (EEG) signals carry extensive information about cognition skills, which include attention, then the potential of using EEG signals for people with low attention span can be quite significant. EEG can be read using the new wireless EEG reading devices often used by Brain-computer Interface (BCI) researchers. In parallel, serious games have been recently utilized for rehabilitating various cognitive and emotional deficits. In this paper, we put the two things together, and we investigate the integration of an EEG-controlled serious game that trains and strengthens patients' attention ability while using machine learning to detect their attention level. Our preliminary experiments with healthy individuals show an accuracy of up to 96% in classifying the EEG data to detect the correct attention state during gameplay. This promising result serves as motivation to test our models with actual ADHD patients in the future.
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