SPECTRA: a tool for enhanced brain wave signal recognition.
File version
Version of Record (VoR)
Author(s)
Tsunoda, Tatsuhiko
Sharma, Alok
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
Size
File type(s)
Location
Abstract
BACKGROUND: Brain wave signal recognition has gained increased attention in neuro-rehabilitation applications. This has driven the development of brain-computer interface (BCI) systems. Brain wave signals are acquired using electroencephalography (EEG) sensors, processed and decoded to identify the category to which the signal belongs. Once the signal category is determined, it can be used to control external devices. However, the success of such a system essentially relies on significant feature extraction and classification algorithms. One of the commonly used feature extraction technique for BCI systems is common spatial pattern (CSP). RESULTS: The performance of the proposed spatial-frequency-temporal feature extraction (SPECTRA) predictor is analysed using three public benchmark datasets. Our proposed predictor outperformed other competing methods achieving lowest average error rates of 8.55%, 17.90% and 20.26%, and highest average kappa coefficient values of 0.829, 0.643 and 0.595 for BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, respectively. CONCLUSIONS: Our proposed SPECTRA predictor effectively finds features that are more separable and shows improvement in brain wave signal recognition that can be instrumental in developing improved real-time BCI systems that are computationally efficient.
Journal Title
BMC Bioinformatics
Conference Title
Book Title
Edition
Volume
22
Issue
Suppl 6
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
© The Author(s), 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Item Access Status
Note
Access the data
Related item(s)
Subject
Mathematical sciences
Biological sciences
Brain computer interface (BCI)
Common spatial pattern (CSP)
Common spatio-spectral pattern (CSSP)
Electroencephalography (EEG)
Motor imagery (MI)
Persistent link to this record
Citation
Kumar, S; Tsunoda, T; Sharma, A, SPECTRA: a tool for enhanced brain wave signal recognition., BMC Bioinformatics, 2021, 22 (Suppl 6), pp. 195