NDLI: A general aggregate model for improving multi-class brain-computer interface systems' performance

Content Provider	IEEE Xplore Digital Library
Author	Tuan Hoang Dat Tran Xu Huang Wanli Ma
Copyright Year	2013
Description	Author affiliation: Fac. of Educ., Sci., Technol. & Math., Univ. of Canberra, Canberra, ACT, Australia (Tuan Hoang; Dat Tran; Xu Huang; Wanli Ma)
Abstract	This paper proposes a general aggregate model for improving performance of multi-class Brain-Computer Interface (BCI) systems. In BCI systems, activation and delay are well known issues in conducting experiments. The delay of meaningful brain signal depends on subjects, tasks and experimental design. Therefore, within a trial it is not easy to identify where meaningful brain signal starts and ends. Most of current methods estimate the delay and extract a portion of meaningful brain signal in a trial and use this signal as a representative for the whole trial. Instead of doing so, our proposed aggregate model divides a trial into overlapping frames and treat them equally. These frames are classified and their results are then aggregated together to form classification result of the trial. From the general aggregate model, we derive two specific aggregate models using two state-of-the-art Common Spatial Patterns (CSP)-based methods for feature extraction. We performed experiments on Dataset 2a used in BCI Competition IV to evaluate the proposed models. This dataset was designed for motor imagery classification with 4 classes. Preliminary experimental results show that our proposed aggregate models are up to 8% better than the original CSP-based methods. Furthermore, we show that our aggregate model can be easily extended to online BCI systems.
Starting Page	1
Ending Page	5
File Size	376365
Page Count	5
File Format	PDF
ISSN	21614407
e-ISBN	9781467361293
DOI	10.1109/IJCNN.2013.6706889
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Aggregates Delays Brain modeling Feature extraction Covariance matrices Accuracy Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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
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