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Electronics 2018, 7(3), 38; https://doi.org/10.3390/electronics7030038

Development of EOG-Based Human Computer Interface (HCI) System Using Piecewise Linear Approximation (PLA) and Support Vector Regression (SVR)

1
School of Computer Science and Information Engineering, Catholic University of Korea, Bucheon 14662, Korea
2
School of Information, Communications and Electronics Engineering, Catholic University of Korea, Bucheon 14662, Korea
*
Author to whom correspondence should be addressed.
Received: 1 February 2018 / Revised: 20 February 2018 / Accepted: 8 March 2018 / Published: 9 March 2018
(This article belongs to the Special Issue Open-Source Electronics Platforms: Development and Applications)
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Abstract

Electrooculogram (EOG)-based human-computer interfaces (HCIs) are widely researched and considered to be a good HCI option for disabled people. However, conventional systems can only detect eye direction or blinking action. In this paper, we developed a bio-signal-based HCI that can quantitatively estimate the horizontal position of eyeball. A designed bio-signal acquisition system can measure EOG and temporalis electromyogram (EMG) signals simultaneously without additional electrodes. For real-time processing for practical application, modified sliding window algorithms are designed and applied for piecewise linear approximation (PLA). To find the eyeball position, support vector regression (SVR) is applied as a curve-fitting model. The average tracking error for target circle with a diameter of 3 cm showed only 1.4 cm difference on the screen with a width of 51 cm. A developed HCI system can perform operations similar to dragging and dropping used in a mouse interface in less than 5 s with only eyeball movement and bite action. Compare to conventional EOG-based HCI that detects the position of the eyeball only in 0 and 1 levels, a developed system can continuously track the eyeball position in less than 0.2 s. In addition, compared to conventional EOG-based HCI, the reduced number of electrodes can enhance the interface usability. View Full-Text
Keywords: human-computer interface (HCI); electrooculogram (EOG); electromyogram (EMG); modified sliding window algorithm; piecewise linear approximation (PLA); support vector regression; eye tracking human-computer interface (HCI); electrooculogram (EOG); electromyogram (EMG); modified sliding window algorithm; piecewise linear approximation (PLA); support vector regression; eye tracking
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Yang, J.-J.; Gang, G.W.; Kim, T.S. Development of EOG-Based Human Computer Interface (HCI) System Using Piecewise Linear Approximation (PLA) and Support Vector Regression (SVR). Electronics 2018, 7, 38.

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