Electrooculogram based system for computer control using a multiple feature classification model

被引:0
|
作者
Kherlopian, Armen R. [1 ]
Gerrein, Joseph P. [1 ]
Yue, Minerva
Kim, Kristina E.
Kim, Ji Won [2 ]
Sukumaran, Madhav [3 ]
Sajda, Paul
机构
[1] Univ Calif San Diego, Dept Bioengn, San Diego, CA USA
[2] New York Med Coll, Valhalla, NY USA
[3] Columbia Univ, Dept Biolog Sci, New York, NY USA
关键词
electrooculography; computer control; hands free speller; eye movement analysis; amyotrophic lateral sclerosis; ALS; Lou Gehrig's disease; sensorimotor and neuromuscular systems;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper discusses the creation of a system for computer-aided communication through automated analysis and processing of electrooculogram signals. In situations of disease or trauma, there may be an inability to communicate with others through standard means such as speech or typing. Eye movement tends to be one of the last remaining active muscle capabilities for people with neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS) also known as Lou Gehrig's disease. Thus, there is a need for eye movement based systems to enable communication. To meet this need, the Telepathix system was designed to accept eye movement commands denoted by looking to the left, looking to the right, and looking straight ahead to navigate a virtual keyboard. Using a ternary virtual keyboard layout and a multiple feature classification model, a typing speed of 6 letters per minute was achieved.
引用
收藏
页码:6033 / +
页数:2
相关论文
共 50 条
  • [31] Multiple integrators control based on feature data of controlled system with random disturbance
    Qiao, Guihua
    MECHATRONICS AND INTELLIGENT MATERIALS II, PTS 1-6, 2012, 490-495 : 2464 - 2469
  • [32] Leaf classification using multiple feature analysis based on semi-supervised clustering
    Li Longlong
    Garibaldi, Jonathan M.
    He Dongjian
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2015, 29 (04) : 1465 - 1477
  • [33] Hardware and Software Implementation of Real Time Electrooculogram (EOG) Acquisition System to Control Computer Cursor with Eyeball Movement
    Hossain, Zakir
    Shuvo, Md. Maruf Hossain
    Sarker, Prionjit
    2017 4TH INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2017, : 132 - 137
  • [34] Feature Enhancement Based Text Sentiment Classification using Deep Learning Model
    Janardhana, D. R.
    Vijay, C. P.
    Swamy, G. B. Janardhana
    Ganaraj, K.
    PROCEEDINGS OF THE 2020 5TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND SECURITY (ICCCS-2020), 2020,
  • [35] A Multiple Learning Model Based Voting System for News Headline Classification
    Zhu, Fenhong
    Dong, Xiaozheng
    Song, Rui
    Hong, Yu
    Zhu, Qiaoming
    NATURAL LANGUAGE PROCESSING AND CHINESE COMPUTING, NLPCC 2017, 2018, 10619 : 797 - 806
  • [36] Feature extraction for a multiple pattern classification neural network system
    Murphey, YL
    Luo, Y
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS, 2002, : 220 - 223
  • [37] Multiple power quality disturbance classification feature optimization based onmulti-granularity feature selection and model fusion
    Ruan Z.
    Xiao X.
    Hu W.
    Zheng Z.
    Wang Y.
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2022, 50 (14): : 1 - 10
  • [38] MULTIPLE COMPUTER SYSTEM FOR DIRECT DIGITAL CONTROL
    不详
    PROCESS CONTROL AND AUTOMATION, 1966, 13 (02): : 46 - &
  • [39] A feature fusion based localized multiple kernel learning system for real world image classification
    Fatemeh Zamani
    Mansour Jamzad
    EURASIP Journal on Image and Video Processing, 2017
  • [40] Model and Feature Selection for the Classification of Dark Field Pollen Images using the Classifynder System
    Pedersen, Ben
    Bailey, Donald G.
    Hodgson, Robert M.
    Holt, Katherine
    Marsland, Stephen
    2017 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ), 2017,