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基于眼电图的计算机书写系统的开发。

Development of a Computer Writing System Based on EOG.

作者信息

López Alberto, Ferrero Francisco, Yangüela David, Álvarez Constantina, Postolache Octavian

机构信息

Departamento de Ingeniería Eléctrica, Electrónica, Computadores y Sistemas, Universidad de Oviedo, Campus of Gijón, 33204 Gijón, Spain.

Instituto de Telecomunicações, ISCTE-IUL, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal.

出版信息

Sensors (Basel). 2017 Jun 26;17(7):1505. doi: 10.3390/s17071505.

DOI:10.3390/s17071505
PMID:28672863
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5539738/
Abstract

The development of a novel computer writing system based on eye movements is introduced herein. A system of these characteristics requires the consideration of three subsystems: (1) A hardware device for the acquisition and transmission of the signals generated by eye movement to the computer; (2) A software application that allows, among other functions, data processing in order to minimize noise and classify signals; and (3) A graphical interface that allows the user to write text easily on the computer screen using eye movements only. This work analyzes these three subsystems and proposes innovative and low cost solutions for each one of them. This computer writing system was tested with 20 users and its efficiency was compared to a traditional virtual keyboard. The results have shown an important reduction in the time spent on writing, which can be very useful, especially for people with severe motor disorders.

摘要

本文介绍了一种基于眼球运动的新型计算机书写系统的开发。具有这些特性的系统需要考虑三个子系统:(1)一种硬件设备,用于采集眼球运动产生的信号并将其传输到计算机;(2)一种软件应用程序,除其他功能外,还允许进行数据处理以最小化噪声并对信号进行分类;(3)一种图形界面,允许用户仅使用眼球运动在计算机屏幕上轻松书写文本。这项工作分析了这三个子系统,并为每个子系统提出了创新且低成本的解决方案。该计算机书写系统对20名用户进行了测试,并将其效率与传统虚拟键盘进行了比较。结果表明,书写时间显著减少,这可能非常有用,特别是对于患有严重运动障碍的人。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/f075059b0a42/sensors-17-01505-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/e5b9c1b11dd9/sensors-17-01505-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/f700ab6928af/sensors-17-01505-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/f075059b0a42/sensors-17-01505-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/8be6535248ca/sensors-17-01505-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/f4cb30e94ac7/sensors-17-01505-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/673fdcd5ef58/sensors-17-01505-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/e5b9c1b11dd9/sensors-17-01505-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/f700ab6928af/sensors-17-01505-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/29e6716ccba9/sensors-17-01505-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6691/5539738/73228c449fef/sensors-17-01505-g012.jpg
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本文引用的文献

1
Eye Tracking and Head Movement Detection: A State-of-Art Survey.眼动追踪和头部运动检测:最新研究综述。
IEEE J Transl Eng Health Med. 2013 Nov 6;1:2100212. doi: 10.1109/JTEHM.2013.2289879. eCollection 2013.
2
Direct Gaze Estimation Based on Nonlinearity of EOG.基于眼电图非线性的直接注视估计
IEEE Trans Biomed Eng. 2015 Jun;62(6):1553-62. doi: 10.1109/TBME.2015.2394409. Epub 2015 Jan 21.
3
Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.使用新型分类方法,通过眼动追踪信号控制人机交互系统。
基于眼电图的人机界面:2000-2020 年回顾。
Sensors (Basel). 2022 Jun 29;22(13):4914. doi: 10.3390/s22134914.
4
An Affordable Method for Evaluation of Ataxic Disorders Based on Electrooculography.基于眼动电图的共济失调障碍评估的一种经济方法。
Sensors (Basel). 2019 Aug 30;19(17):3756. doi: 10.3390/s19173756.
5
An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand.一种基于脑电图/肌电图/眼电图的多模态人机接口,用于软机器人手的实时控制。
Front Neurorobot. 2019 Mar 29;13:7. doi: 10.3389/fnbot.2019.00007. eCollection 2019.
IEEE Trans Biomed Eng. 2013 Aug;60(8):2133-41. doi: 10.1109/TBME.2013.2248154. Epub 2013 Feb 21.
4
Sensory system for implementing a human-computer interface based on electrooculography.用于实现基于眼动的人机接口的感觉系统。
Sensors (Basel). 2011;11(1):310-28. doi: 10.3390/s110100310. Epub 2010 Dec 29.
5
Multimodal human-machine interface based on a brain-computer interface and an electrooculography interface.基于脑机接口和眼电图接口的多模态人机界面。
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4572-5. doi: 10.1109/IEMBS.2011.6091132.
6
Electrooculogram detection of eye movements on gaze displacement.注视位移时眼动的眼电图检测
Neurosci Behav Physiol. 2010 Jun;40(5):583-91. doi: 10.1007/s11055-010-9299-z. Epub 2010 May 14.
7
Eye movement analysis for activity recognition using electrooculography.使用眼动分析进行基于眼电图的活动识别。
IEEE Trans Pattern Anal Mach Intell. 2011 Apr;33(4):741-53. doi: 10.1109/TPAMI.2010.86.
8
In the eye of the beholder: a survey of models for eyes and gaze.在观察者的眼中:眼睛和注视模型的调查。
IEEE Trans Pattern Anal Mach Intell. 2010 Mar;32(3):478-500. doi: 10.1109/TPAMI.2009.30.
9
On the use of electrooculogram for efficient human computer interfaces.利用眼电图实现高效的人机界面。
Comput Intell Neurosci. 2010;2010:135629. doi: 10.1155/2010/135629. Epub 2009 Oct 15.
10
ISCEV Standard for Clinical Electro-oculography (EOG) 2006.《国际临床视觉电生理学会(ISCEV)临床眼电图(EOG)标准(2006年版)》
Doc Ophthalmol. 2006 Nov;113(3):205-12. doi: 10.1007/s10633-006-9030-0. Epub 2006 Nov 16.