TY - GEN
T1 - EEG-based attention recognition
AU - Li, Xiaowei
AU - Hu, Bin
AU - Dong, Qunxi
AU - Campbell, William
AU - Moore, Philip
AU - Peng, Hong
PY - 2011
Y1 - 2011
N2 - Attention recognition (AR) is an essential component in many applications, however the focus of current research into AR is on face detection, eye center localization and eye center tracking techniques. This paper describes a research project conducted to investigate the use of electroencephalography (EEG) signals to extend the current approaches and enrich AR. EEG processing and classification algorithms are applied to EEG data to identify a group of features that can be used to effectively implement AR. The experimental results reported in this paper are encouraging with correct classification rates achieved being: 51.9% where attention is divided into 5 classes and 63.9% where attention id divided into 3 classes. The distribution of the training tuples and testing tuples is discussed along with their impact on the reported results. The paper concludes with an overview of outstanding issues and consideration of projected future research.
AB - Attention recognition (AR) is an essential component in many applications, however the focus of current research into AR is on face detection, eye center localization and eye center tracking techniques. This paper describes a research project conducted to investigate the use of electroencephalography (EEG) signals to extend the current approaches and enrich AR. EEG processing and classification algorithms are applied to EEG data to identify a group of features that can be used to effectively implement AR. The experimental results reported in this paper are encouraging with correct classification rates achieved being: 51.9% where attention is divided into 5 classes and 63.9% where attention id divided into 3 classes. The distribution of the training tuples and testing tuples is discussed along with their impact on the reported results. The paper concludes with an overview of outstanding issues and consideration of projected future research.
KW - Attention Recognition
KW - Classification Algrithm
KW - EEG
UR - http://www.scopus.com/inward/record.url?scp=84862911842&partnerID=8YFLogxK
U2 - 10.1109/ICPCA.2011.6106504
DO - 10.1109/ICPCA.2011.6106504
M3 - Conference contribution
AN - SCOPUS:84862911842
SN - 9781457702082
T3 - Proceedings - 2011 6th International Conference on Pervasive Computing and Applications, ICPCA 2011
SP - 196
EP - 201
BT - Proceedings - 2011 6th International Conference on Pervasive Computing and Applications, ICPCA 2011
T2 - 2011 6th International Conference on Pervasive Computing and Applications, ICPCA 2011
Y2 - 26 October 2011 through 28 October 2011
ER -
