眼动跟踪

Tanu Wadhera, D. Kakkar
{"title":"眼动跟踪","authors":"Tanu Wadhera, D. Kakkar","doi":"10.4018/978-1-5225-7004-2.CH007","DOIUrl":null,"url":null,"abstract":"The high prevalence of autism spectrum disorder (ASD) has provided a spectrum of diagnostic methodologies ranging from screening scales to technological techniques. The technology-based techniques, especially eye trackers, are shifting the traditional subjective approaches to objective, leading to early ASD screening and intervention. The eye gaze deficits marked by eye trackers are the valid biomarkers of ASD, but the trackers are not clinically available. Another reason for non-availability is the limited number of methodologies which can meaningfully analyze gaze data. The assistance of new technologies into eye tracker system explored here can (1) detect gaze patterns and cognitive abilities of individuals at the single platform and (2) analyze eye movements and events automatically using deep learning system rather than manual interpretation of raw data. These types of systems, if implemented, have the potential to assist clinicians for better ASD diagnosis and intervention approaches.","PeriodicalId":102459,"journal":{"name":"Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Eye Tracker\",\"authors\":\"Tanu Wadhera, D. Kakkar\",\"doi\":\"10.4018/978-1-5225-7004-2.CH007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The high prevalence of autism spectrum disorder (ASD) has provided a spectrum of diagnostic methodologies ranging from screening scales to technological techniques. The technology-based techniques, especially eye trackers, are shifting the traditional subjective approaches to objective, leading to early ASD screening and intervention. The eye gaze deficits marked by eye trackers are the valid biomarkers of ASD, but the trackers are not clinically available. Another reason for non-availability is the limited number of methodologies which can meaningfully analyze gaze data. The assistance of new technologies into eye tracker system explored here can (1) detect gaze patterns and cognitive abilities of individuals at the single platform and (2) analyze eye movements and events automatically using deep learning system rather than manual interpretation of raw data. These types of systems, if implemented, have the potential to assist clinicians for better ASD diagnosis and intervention approaches.\",\"PeriodicalId\":102459,\"journal\":{\"name\":\"Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-5225-7004-2.CH007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-5225-7004-2.CH007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

自闭症谱系障碍(ASD)的高患病率提供了一系列诊断方法,从筛查量表到技术技术。以技术为基础的技术,特别是眼动仪,正在将传统的主观方法转变为客观方法,从而实现ASD的早期筛查和干预。眼动仪显示的眼球注视缺陷是ASD的有效生物标志物,但临床上还没有这种追踪器。不可用性的另一个原因是能够有效分析注视数据的方法数量有限。本文探索的新技术对眼动仪系统的辅助可以(1)检测单个平台上个体的凝视模式和认知能力;(2)使用深度学习系统自动分析眼动和事件,而不是人工解释原始数据。这些类型的系统,如果实施,有可能帮助临床医生更好的ASD诊断和干预方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eye Tracker
The high prevalence of autism spectrum disorder (ASD) has provided a spectrum of diagnostic methodologies ranging from screening scales to technological techniques. The technology-based techniques, especially eye trackers, are shifting the traditional subjective approaches to objective, leading to early ASD screening and intervention. The eye gaze deficits marked by eye trackers are the valid biomarkers of ASD, but the trackers are not clinically available. Another reason for non-availability is the limited number of methodologies which can meaningfully analyze gaze data. The assistance of new technologies into eye tracker system explored here can (1) detect gaze patterns and cognitive abilities of individuals at the single platform and (2) analyze eye movements and events automatically using deep learning system rather than manual interpretation of raw data. These types of systems, if implemented, have the potential to assist clinicians for better ASD diagnosis and intervention approaches.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信