Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3397391.3397410acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicbetConference Proceedingsconference-collections
research-article

Environmental Control System for Locked-in Syndrome Patients Using Eye Tracker

Published: 15 September 2020 Publication History

Abstract

Locked-in syndrome or LIS is a whole body voluntary muscles paralysis excluding muscles that control the eye movements but they are awake and conscious. The cognitive function is usually not affected and they can communicate through blinking or eye movements. LIS patient loses his productivity since their everyday living are greatly affected and needs a continuous help. Nowadays, assistive technology is widely used to compensate for the impairments they experience. The main objective of this research is to design and develop an assistive technology controlled by an eye tracker to help improve the lives of those patients suffering from LIS in controlling some electrical/electronic devices. The study utilized the experimental research design and the creation of a functional prototype for its hardware and software requisites. The researchers were able to successfully develop an environmental control system that is made through designing an appliance controller and a software where user can switch on or off four appliances through the use of eye gaze as their input. Statistical treatment of t-test was applied and the results showed that there is no significance difference between the user's actual gaze point coordinate to the center coordinate of the appliances buttons.

References

[1]
Alva M., Castellino N., Deshpande R., Sonawane K. & Lopes M. (2017). An Image Based Eye Controlled Assistive System for Paralytic Patients. 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA), 178--183.
[2]
Anacan, R., Alcayde, J., Antegra, R., & Luna, L. (2013). Eye-GUIDE (Eye-Gaze User Interface Design) Messaging for Physically-Impaired People, 4(1), 41--44.
[3]
Bacher, D., Jarosiewicz, B., Masse, N. Y., Stavisky, S. D., Simeral, J. D., Newell, K., ... & Hochberg, L. R. (2015). Neural point-and-click communication by a person with incomplete locked-in syndrome. Neurorehabilitation and neural repair, 29(5), 462--47.
[4]
Boustany, G. I.-F. (2016). Design and development of a rehabilitative eye-tracking based home automation system. In Biomedical Engineering (MECBME), IEEE.
[5]
Deravi, F. A.-W. (2015). Usability and performance measure of a consumer-grade brain computer interface system for environmental control by neurological patients. International Journal of Engineering and Technology Innovation, 5(3), 165--177.
[6]
Juhong, A., Treebupachatsakul, T., & Pintavirooj, C. (2018). Smart eye-tracking system, IEEE.
[7]
Lugo, Z. R., Bruno, M. A., Gosseries, O., Demertzi, A., Heine, L., Thonnard, M., ... & Laureys, S. (2015). Beyond the gaze: communicating in chronic locked-in syndrome. Brain injury, 29(9), 1056--1061.
[8]
Meesad, P. & Janthanasub, V. (2015). Evaluation of a Low-cost Eye Tracking System for Computer Input. KMUTNB Int J Appl Sci Technol.Shneiderman. (2010). Designing the user interface: strategies for effective human-computer interaction. Pearson Education India.
[9]
Middendorp, J., Watkins, F., Park, C., & Landymore, H. (2015). Eye-tracking computer systems for inpatients with tetraplegia: findings from a feasibility study, 53(2), 221--225.
[10]
Padilla, D. et al (2017). Implementation of eye gaze tracking technique on FPGA-based on-screen keyboard system using verilog and MATLAB.
[11]
Park, S. W., Yim, Y. L., Yi, S. H., Kim, H. Y., & Jung, S. M. (2012). Augmentative and alternative communication training using eye blink switch for locked-in syndrome patient. Annals of rehabilitation medicine, 36(2), 268--272.
[12]
Schettini, F., Riccio, A., Simione, L., Liberati, G., Caruso, M., Frasca, V., ... & Mattia, D. (2015). Assistive device with conventional, alternative, and brain-computer interface inputs to enhance interaction with the environment for people with amyotrophic lateral sclerosis: a feasibility and usability study. Archives of physical medicine and rehabilitation, 96(3), S46-S53.
[13]
Shneiderman. (2010). Designing the user interface: strategies for effective human-computer interaction. Pearson Education India.
[14]
Zhang, X., Liu, X., Yuan, S., & Lin, S. (2017). Eye Tracking Based Control System for Natural Human-Computer Interaction. Computational Intelligence and Neuroscience, vol 2017.

Cited By

View all
  • (2024)Self-Applicable Eye Strain Detection Through the Measurement of Blink Rate Using Raspberry Pi2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)10.1109/IICAIET62352.2024.10730733(13-17)Online publication date: 26-Aug-2024

Index Terms

  1. Environmental Control System for Locked-in Syndrome Patients Using Eye Tracker

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICBET '20: Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology
    September 2020
    350 pages
    ISBN:9781450377249
    DOI:10.1145/3397391
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 15 September 2020

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Environmental control system
    2. Eye tracking
    3. Locked-in syndrome
    4. Tobii eye tracker 4C

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICBET 2020

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)15
    • Downloads (Last 6 weeks)4
    Reflects downloads up to 03 Jan 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Self-Applicable Eye Strain Detection Through the Measurement of Blink Rate Using Raspberry Pi2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)10.1109/IICAIET62352.2024.10730733(13-17)Online publication date: 26-Aug-2024

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media