FBLPF-ABOW: An Effective Method for Blink Artifact Removal in Single-Channel EEG Signal

Objective:
The latest development in low-cost single-channel Electroencephalography (EEG) devices is gaining widespread attention because it reduces hardware complexity. Discrete wavelet transform (DWT) has been a popular solution to eliminate the blink artifacts in EEG signals. However, the existing DWT-based methods share the same wavelet function among subjects, which ignores the individual difference. To remedy this deficiency, this article proposes a novel approach to eliminate the blink artifacts in single-channel EEG signals.
Methods:
Firstly, the forward-backward low-pass filter (FBLPF) and a fixed-length window are used to detect blink artifact intervals. Secondly, the adaptive bi-orthogonal wavelet (ABOW) is constructed based on the most representative blink signal. Thirdly, these detected signals are filtered by ABOW-DWT. The DWT's decomposition depth is automatically chosen by a similarity-based method.
Results:
Compared to eight state-of-the-art methods, experiments on semi-simulated and real EEG signals demonstrate the proposed method's superiority in removing the blink artifacts with less neural information loss.
Significance:
To filter the blink artifacts in single-channel EEG signals, the innovative idea of constructing an adaptive wavelet function based on the signal characteristics rather than using the conventional wavelet is proposed for the first time.