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Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
An optimized Impulse Factor-based VMD-EMD approach to improve SSVEP accuracy for BCI Systems
Results in Engineering, Vol.25, pp.1-14
2025
Abstract
The steady-state visual evoked potential (SSVEP) is a brain response to visual stimuli, flickering at the target frequency and its harmonics, in the occipital cortex. SSVEP-based detection methods use multichannel or single channel setups. Multichannel setups are complex and can cause discomfort to the user, especially disabled individuals, during prolonged use. So, there is a need to develop accurate single channel SSVEP based detection method. In this study, we developed a novel method called impulse factor-based Variational Mode Decomposition, Empirical Mode Decomposition (IF-VMD-EMD) for single-channel SSVEP datasets. For preprocessing of recorded SSVEP signals, the Moving Average Filter (MAF) was applied to improve the Signal-to-Noise Ratio (SNR). The VMD then decomposes the SSVEP signal into harmonic Variational Mode Functions (VMFs) and noisy VMFs. Moreover, we introduced the Impulse Factor of Cross Correlation Function (IFCCF) method to optimally select harmonic VMFs. The addition of EMD with IF-VMD further enhances the SNR by selecting the contributing EMD-Intrinsic Mode Function based on the Pearson correlation coefficient, aiming to remove noise from the restored signal and extract sub-signals with rich parent signal information. The proposed method (IF-VMD-EMD) performed better than other relevant methods and achieved an average accuracy of 92.32 %, 89.62 %, 90.01 % and an Information Transfer Rate (ITR) of 64.80 bits/min, 77.56 bits/min, 63.11 bits/min for three publicly available datasets consisting of seven, twelve and seven classes, respectively. The proposed method (IF-VMD-EMD) exhibits better accuracy, improved ITR, and is user-friendly in real world applications.
Details
- Title
- An optimized Impulse Factor-based VMD-EMD approach to improve SSVEP accuracy for BCI Systems
- Authors
- Adeel Wahab (Corresponding Author) - National University of Sciences and TechnologyUmar Shahbaz Khan - National University of Sciences and TechnologyTahir Nawaz - National University of Sciences and TechnologySyed Tayyab Hussain Shah - National University of Sciences and TechnologyU. Izhar - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringAyesha Zeb - National University of Sciences and Technology
- Publication details
- Results in Engineering, Vol.25, pp.1-14
- Publisher
- Elsevier BV
- Date published
- 2025
- DOI
- 10.1016/j.rineng.2025.104203
- ISSN
- 2590-1230
- Copyright note
- © 2025 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
- Data Availability
- Data will be made available on request.
- Grant note
- Higher Education Commission of Pakistan and the National Centre of Robotics and Automation under grant number, DF-1009–31.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991127095502621
- Output Type
- Journal article
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