AQMFB-DWT: A Preprocessing Technique for Removing Blink Artifacts Before Extracting Pain-evoked Potential EEG
Wenjia Gao1 · Dan Liu1 · Qisong Wang1 · Yongping Zhao1 · Jinwei Sun1
1 Harbin Institute of Technology, Harbin 150001, China
Abstract
The pain-evoked potential electroencephalogram (EEG) is an effective electrophysiological indicator for pain assessment, yet its extraction is challenging due to interference from background activity and involuntary blinks. Although existing blink artifact-removal methods show efficacy, they face limitations such as the need for reference signals, neglect of individual differences, and reliance on user input, hindering their practical application in clinical pain assessments. In this paper, we propose a novel framework applying adaptive quadrature mirror filter banks (AQMFB) with discrete wavelet transform (DWT) to remove blink artifacts in pain EEG. Unlike traditional DWT methods that apply fixed wavelets across subjects, our method adapts wavelet construction based on the characteristics of EEG. Experimental results demonstrate that AQMFB-DWT outperforms four leading methods in removing blink artifacts with minimal distortion of pain information, all within an acceptable processing time. This technique is a valuable preprocessing step for enhancing the extraction of pain-evoked potentials.
Keywords
Blink artifact removal; Pain-evoked potential electroencephalography; Adaptive quadrature mirror flter banks; Discrete wavelet transformation
