High accuracy classification of EEG signal
Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accuracy EEC signal classification method using single trial EEC signal to detect left and right finger movement. We apply an...
Saved in:
Main Authors: | XU, Wenjie, GUAN, Cuitai, SIONG, Chng Eng, RANGANATHA, S., THULASIDAS, Manoj, WU, Jiankang |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2004
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/3496 https://ink.library.smu.edu.sg/context/sis_research/article/4497/viewcontent/HighAccuracyClassificationEEGSignal_2004_ICPR.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Effect of ocular artifact removal in brain computer interface accuracy
by: THULASIDAS, Manoj, et al.
Published: (2004) -
Robust classification of EEG signal for brain-computer interface
by: THULASIDAS, Manoj, et al.
Published: (2006) -
High performance P300 speller for brain-computer interface
by: GUAN, Cuntai, et al.
Published: (2004) -
EEG-video emotion-based summarization: Learning with EEG auxiliary signals
by: LEW, Wai-Cheong L., et al.
Published: (2022) -
Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface
by: Sitaram, R., et al.
Published: (2007)