Next Article in Journal
Context Relevant Prediction Model for COPD Domain Using Bayesian Belief Network
Next Article in Special Issue
The Role of Visual Noise in Influencing Mental Load and Fatigue in a Steady-State Motion Visual Evoked Potential-Based Brain-Computer Interface
Previous Article in Journal
Relationship between Remote Sensing Data, Plant Biomass and Soil Nitrogen Dynamics in Intensively Managed Grasslands under Controlled Conditions
Previous Article in Special Issue
Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(7), 1485; doi:10.3390/s17071485

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

1
Interdisciplinary Program of Bioengineering, Seoul National University, Seoul 03080, Korea
2
Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea
*
Author to whom correspondence should be addressed.
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)
View Full-Text   |   Download PDF [3831 KB, uploaded 23 June 2017]   |  

Abstract

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
Figures

Figure 1

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).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top