Title | ||
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Towards Enhanced Information Transfer Rate: A Comparative Study Based On Classification Techniques |
Abstract | ||
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One of the most important performance parameters for Assistive Devices (AD's) based on Brain Computer Interfaces (BCIs) is the Information Transfer Rate (ITR). This study compares a hybrid BCI to a Steady State Visually Evoked Potential (SSVEP) based BCI, along with a comparison of classification techniques used for translation of user intentions. The hybrid BCI paradigm combined SSVEP & P300, where SSVEP decodes user intentions and P300 is used for Time Division Multiplexing (TDM). The classification protocols were categorised as single-step supervised classifiers and two-step unsupervised classifier. It was observed that the classification accuracy for translation of human intentions for the traditional SSVEP paradigm (93.78%) was higher than the hybrid BCI (90.76%) proposed, but still the hybrid BCI is paradigm option for development of ADs (high ITR of 81.10 bits/minute). The study compared the two classification protocols using the statistical t-value test, which concluded that (99.9% confidence level) the mean classification accuracy and mean ITR were greater for the single-step supervised classification and also that the mean FAR was lower for the single-step supervised classification. The proposed hybrid BCI with single-step supervised learning classification protocol emerged as best BCI option for the development of AD's. |
Year | DOI | Venue |
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2020 | 10.1080/21681163.2020.1727775 | COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION |
Keywords | DocType | Volume |
BCI, P300, SSVEP, hybrid BCI, ITR, SVM | Journal | 8 |
Issue | ISSN | Citations |
4 | 2168-1163 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
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Akshay Katyal | 1 | 0 | 0.34 |
Rajesh Singla | 2 | 6 | 1.98 |