The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Development of Eye-Tracking System Using Dual Machine Learning Structure

이중 기계학습 구조를 이용한 안구이동추적 기술개발

  • Gang, Gyeong Woo (Sch. of Information, Communications and Electronics Engineering, Catholic University of Korea) ;
  • Min, Chul Hong (Central Reserch Institute, Synopex Co., Ltd) ;
  • Kim, Tae Seon (Sch. of Information, Communications and Electronics Engineering, Catholic University of Korea)
  • Received : 2017.05.31
  • Accepted : 2017.06.29
  • Published : 2017.07.01
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Abstract

In this paper, we developed bio-signal based eye tracking system using electrooculogram (EOG) and electromyogram (EMG) which measured simultaneously from same electrodes. In this system, eye gazing position can be estimated using EOG signal and we can use EMG signal at the same time for additional command control interface. For EOG signal processing, PLA algorithms are applied to reduce processing complexity but still it can guarantee less than 0.2 seconds of reaction delay time. Also, we developed dual machine learning structure and it showed robust and enhanced tracking performances. Compare to conventional EOG based eye tracking system, developed system requires relatively light hardware system specification with only two skin contact electrodes on both sides of temples and it has advantages on application to mobile equipments or wearable devices. Developed system can provide a different UX for consumers and especially it would be helpful to disabled persons with application to orthotics for those of quadriplegia or communication tools for those of intellectual disabilities.

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References

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