Real-Time “Eye-Writing” Recognition Using Electrooculogram

Eye movements can be used as alternative inputs for human-computer interface (HCI) systems such as virtual or augmented reality systems as well as new communication ways for patients with locked-in syndrome. In this study, we developed a real-time electrooculogram (EOG)-based eye-writing recognition system, with which users can write predefined symbolic patterns with their volitional eye movements. For the “eye-writing” recognition, the proposed system first reconstructs the eye-written traces from EOG waveforms in real-time; then, the system recognizes the intended symbolic inputs with a reliable recognition rate by matching the input traces with the trained eye-written traces of diverse input patterns. Experiments with 20 participants showed an average recognition rate of 87.38% (F1 score) for 29 different symbolic patterns (26 lower case alphabet characters and three functional input patterns representing Space, Backspace, and Enter keys), demonstrating the promise of our EOG-based eye-writing recognition system in practical scenarios.

[1]  Bjoern M. Eskofier,et al.  A wearable real-time activity tracker , 2015 .

[2]  W. Sardha Wijesoma,et al.  EOG based control of mobile assistive platforms for the severely disabled , 2005, 2005 IEEE International Conference on Robotics and Biomimetics - ROBIO.

[3]  Carlos Hitoshi Morimoto,et al.  Eye gaze tracking techniques for interactive applications , 2005, Comput. Vis. Image Underst..

[4]  Gerhard Tröster,et al.  Wearable EOG goggles: eye-based interaction in everyday environments , 2009, CHI Extended Abstracts.

[5]  Manuel Mazo,et al.  Wheelchair Guidance Strategies Using EOG , 2002, J. Intell. Robotic Syst..

[6]  Chun-Liang Hsu,et al.  EOG-based Human-Computer Interface system development , 2010, Expert Syst. Appl..

[7]  Chung-Hsien Kuo,et al.  Eyeglasses based electrooculography human-wheelchair interface , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[8]  Toshiharu Mukai,et al.  Drifting and Blinking Compensation in Electro-oculography (EOG) Eye-gaze Interface , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[9]  S. Honda,et al.  Electro-oculography mouse for amyotrophic lateral sclerosis patients , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Guang Li,et al.  Development of an EOG (Electro-Oculography) Based Human-Computer Interface , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[11]  Kati Pettersson,et al.  Algorithm for automatic analysis of electro-oculographic data , 2013, BioMedical Engineering OnLine.

[12]  Chang-Hwan Im,et al.  An unsupervised eye blink artifact detection method for real-time electroencephalogram processing , 2016, Physiological measurement.

[13]  Chang-Hwan Im,et al.  Detection of eye blink artifacts from single prefrontal channel electroencephalogram , 2016, Comput. Methods Programs Biomed..

[14]  Arie E. Kaufman,et al.  An eye tracking computer user interface , 1993, Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium.

[15]  Alan C. Bovik,et al.  Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures , 2009, IEEE Signal Processing Magazine.

[16]  Dinesh Kumar,et al.  Classification of EOG for human computer interface , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[17]  Min Han,et al.  A fully automatic ocular artifact removal from EEG based on fourth-order tensor method , 2014 .

[18]  Gerhard Tröster,et al.  Eye Movement Analysis for Activity Recognition Using Electrooculography , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Jang-Zern Tsai,et al.  A Feasibility Study of an Eye-writing System Based on E1ectro-oculography , 2008 .

[20]  D. Thurman,et al.  How common are the “common” neurologic disorders? , 2007, Neurology.

[21]  Eamonn J. Keogh,et al.  Making Time-Series Classification More Accurate Using Learned Constraints , 2004, SDM.

[22]  L. Lindstrom,et al.  Muscular fatigue and action potential conduction velocity changes studied with frequency analysis of EMG signals. , 1970, Electromyography.

[23]  Junichi Hori,et al.  Development of EOG-Based Communication System Controlled by Eight-Directional Eye Movements , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[24]  Kenneth R. Anderson,et al.  Dynamic waveform matching , 1983, Inf. Sci..

[25]  Hong Hua,et al.  Video-based eyetracking methods and algorithms in head-mounted displays. , 2006, Optics express.

[26]  H D Crane,et al.  Generation-V dual-Purkinje-image eyetracker. , 1985, Applied optics.

[27]  R. Krauzlis.  The Control of Voluntary Eye Movements: New Perspectives , 2005, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[28]  Franco Simini,et al.  Gaze tracker by electrooculography (EOG) on a head-band , 2011, 2011 10th International Workshop on Biomedical Engineering.

[29]  Neil D. Lawrence,et al.  Unravelling the enigma of selective vulnerability in neurodegeneration: motor neurons resistant to degeneration in ALS show distinct gene expression characteristics and decreased susceptibility to excitotoxicity , 2012, Acta Neuropathologica.

[30]  Gerhard Tröster,et al.  Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments , 2009, J. Ambient Intell. Smart Environ..

[31]  D G Pelli,et al.  The VideoToolbox software for visual psychophysics: transforming numbers into movies. , 1997, Spatial vision.

[32]  D. Zee,et al.  Electrooculography: technical standards and applications. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.

[33]  Tommy Strandvall,et al.  Eye Tracking in Human-Computer Interaction and Usability Research , 2009, INTERACT.