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A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

Interdisciplinary Program of Bioengineering, Seoul National University, Seoul 03080, Korea
Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea
Author to whom correspondence should be addressed.
Sensors 2017, 17(7), 1485;
Received: 2 May 2017 / Revised: 18 June 2017 / Accepted: 20 June 2017 / Published: 23 June 2017
(This article belongs to the Special Issue Biomedical Sensors and Systems 2017)
PDF [3831 KB, uploaded 23 June 2017]


Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain–computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles. View Full-Text
Keywords: human computer interface; HCI; electrooculogram; EOG; forehead; eye movement human computer interface; HCI; electrooculogram; EOG; forehead; eye movement

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Heo, J.; Yoon, H.; Park, K.S. A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces. Sensors 2017, 17, 1485.

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