VNU-UET Repository

An EEG Signal Smoothing Algorithm Using Upscale and Downscale Representation

Dinh, Tran Hiep (2023) An EEG Signal Smoothing Algorithm Using Upscale and Downscale Representation. Working Paper. This work has been submitted to the IEEE for possible publication. (Submitted)

Download (1MB)


Effective smoothing of electroencephalogram (EEG) signals while maintaining the original signal’s features is important in EEG signal analysis and brain-computer interface (BCI). This paper proposes a novel EEG signal smoothing algorithm and its potential application in cognitive conflict processing. Instead of being processed in the time domain, the input signal is visualized in an increasing line width, the representation frame of which is converted into a binary image. An effective thinning algorithm is then employed to obtain a unit width skeleton as the smoothed signal. Experimental results on data fitting have verified the effectiveness of the proposed approach on different levels of signal to noise (SNR) ratio, especially on high noise levels (SNR ≤ 5 dB), where our fitting error is only 86.4%-90.4% compared to that of its best counterpart. The potential application of the proposed algorithm in EEG-based cognitive conflict processing is comprehensively evaluated in a classification and a visual inspection task. The employment of the proposed approach for data pre-processing has significantly boosted the classification performance of EEGNet on a cognitive conflict dataset, the improvement of which can go up to 4.54% and 5.36%, in terms of Accuracy and F1-score in some crossvalidation folds. The robustness of our algorithm is also evaluated via a visual inspection task, where specific cognitive conflict peaks, i.e. the prediction error negativity (PEN) and error-related positive potential (Pe), can be easily observed at multiple levels of line-width, while the noisy ones are eliminated.

Item Type: Technical Report (Working Paper)
Additional Information: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
Subjects: Electronics and Communications > Electronics and Computer Engineering
Information Technology (IT)
Divisions: Advanced Insitute of Engineering and Technology (AVITECH)
Faculty of Electronics and Telecommunications (FET)
Faculty of Engineering Mechanics and Automation (FEMA)
Depositing User: Tran Hiep Dinh
Date Deposited: 01 Feb 2023 01:03
Last Modified: 10 Feb 2023 07:48

Actions (login required)

View Item View Item