標題: Controlling a Human-Computer Interface System With a Novel Classification Method that Uses Electrooculography Signals
作者: Wu, Shang-Lin
Liao, Lun-De
Lu, Shao-Wei
Jiang, Wei-Ling
Chen, Shi-An
Lin, Chin-Teng
影像與生醫光電研究所
電控工程研究所
腦科學研究中心
Institute of Imaging and Biomedical Photonics
Institute of Electrical and Control Engineering
Brain Research Center
關鍵字: Biosignal processing;classification methods;electrooculography (EOG);eye movement detection;human-computer interface (HCI)
公開日期: 1-Aug-2013
摘要: Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.
URI: http://dx.doi.org/10.1109/TBME.2013.2248154
http://hdl.handle.net/11536/22139
ISSN: 0018-9294
DOI: 10.1109/TBME.2013.2248154
期刊: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume: 60
Issue: 8
起始頁: 2133
結束頁: 2141
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