NDLI: Online semi-supervised learning with KL distance weighting for Motor Imagery-based BCI

Content Provider	IEEE Xplore Digital Library
Author	Bamdadian, A. Cuntai Guan Kai Keng Ang Jianxin Xu
Copyright Year	2012
Description	Author affiliation: Infocomm Res., Agency for Sci., Technol. & Res. (ASTAR), Singapore, Singapore (Bamdadian, A.) \|\| Inst. for Infocomm Res., Agency for Sci., Technol. & Res. (ASTAR), Singapore, Singapore (Cuntai Guan; Kai Keng Ang) \|\| Electr. & Comput. Eng. Dept., Nat. Univ. of Singapore, Singapore, Singapore (Jianxin Xu)
Abstract	Studies had shown that Motor Imagery-based Brain Computer Interface (MI-based BCI) system can be used as a therapeutic tool such as for stroke rehabilitation, but had shown that not all subjects could perform MI well. Studies had also shown that MI and passive movement (PM) could similarly activate the motor system. Although the idea of calibrating MI-based BCI system from PM data is promising, there is an inherent difference between features extracted from MI and PM. Therefore, there is a need for online learning to alleviate the difference and improve the performance. Hence, in this study we propose an online batch mode semi-supervised learning with KL distance weighting to update the model trained from the calibration session by using unlabeled data from the online test session. In this study, the Filter Bank Common Spatial Pattern (FBCSP) algorithm is used to compute the most discriminative features of the EEG data in the calibration session and is updated iteratively on each band after a batch of online data is available for performing semi-supervised learning. The performance of the proposed method was compared with offline FBCSP, and results showed that the proposed method yielded slightly better results in comparison with offline FBCSP. The results also showed that the use of the model trained from PM for online session-to-session transfer compared to the use of the calibration model trained from MI yielded slightly better performance. The results suggest that using PM, due to its better performance and ease of recording is feasible and performance can be improved by using the proposed method to perform online semi-supervised learning while subjects perform MI.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	2732
Ending Page	2735
File Size	578222
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346529
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Calibration Accuracy Semisupervised learning Brain computer interfaces Brain modeling Filter banks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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