使用虛擬超市遊戲進行認知障礙的執行功能智能評估方法;An intelligent executive functions assessment method for cognitive impairment using virtual supermarket game

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Title:	使用虛擬超市遊戲進行認知障礙的執行功能智能評估方法;An intelligent executive functions assessment method for cognitive impairment using virtual supermarket game
Authors:	陳俊淵;Chen, Chun-Yuan
Contributors:	資訊工程學系
Keywords:	執行功能評估;認知障礙;輕度認知障礙;阿爾茨海默氏病;超市;虛擬現實;Executive functions assessment;cognitive impairment;mild cognitive impairment;Alzheimer′s disease;supermarket;virtual reality
Date:	2020-07-29
Issue Date:	2020-09-02 18:00:59 (UTC+8)
Publisher:	國立中央大學
Abstract:	阿茲海默症對於老人的日常生活有巨大影響,不僅給患者帶來身心痛苦,更給家庭和社會帶來沉重的經濟負擔.如今這個病症尤其在無法根治的負擔下,我們需要有早期評估患病的方法,以便緩解患者的情況. 在本論文中我們製作了虛擬超市的購物互動遊戲,在虛擬現實設備上進行移動和購買的任務.透過任務的執行主要針對參與者的執行功能進行評估研究,在遊戲過程中,我們收集了移動路徑和購買商品紀錄,將參與者在與設備互動的相關資訊記錄在本地端和雲端資料庫. 在這次的研究中我們收集了四個患有認知障礙包括阿茲海默症或輕度認知障礙的老人與六個正常年輕人的資料,並使用目前擁有的所有資料進行資料增強.我們從原始數據中提取四十六筆特徵後,用統計分析的方式觀察特徵的有效性,並且畫出相關的圖表觀看操作的情形.此外,我們也使用多種機器學習的分類方式評估患者的情況,幫助臨床醫師提供良好的意見. ;Alzheimer′s disease has a huge impact on the daily life of the elderly, not only bringing physical and mental pain to patients, but also bringing a heavy financial burden to families and society.Nowadays, this condition is especially under the burden of incurability.We need to have an early method of evaluating the disease in order to alleviate the patient′s condition. In this paper, we have created a shopping interactive game in a virtual supermarket, and carried out mobile and purchasing tasks on a virtual reality device.Through the execution of tasks, we mainly evaluate and study the execution functions of the participants.During the game, we collected movement paths and purchased product records, and recorded the relevant information of the participants′ interaction with the device on the local end and the cloud database. In this study, we collected data on 4 elderly people with cognitive impairment including Alzheimer′s disease or Mild Cognitive Impairment and 6 normal young people, and used all the data currently available for data enhancement.After extracting 46 features from the row data, we use statistical analysis to observe the effectiveness of the features and draw relevant graphs to watch the operation.In addition, we also use a variety of machine learning classification methods to evaluate the patient′s condition and help clinicians provide good opinions.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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