VME-DWT: An efficient algorithm for detection and elimination of eye blink from short segments of single EEG channel

M Shahbakhti, M Beiramvand, M Nazari… - … on Neural Systems …, 2021 - ieeexplore.ieee.org
Objective: Recent advances in development of low-cost single-channel
electroencephalography (EEG) headbands have opened new possibilities for applications …

A segmentation-denoising network for artifact removal from single-channel EEG

Y Li, A Liu, J Yin, C Li, X Chen - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
As an important neurorecording technique, electroencephalography (EEG) is often
contaminated by various artifacts, which obstructs subsequent analysis. In recent years …

Wavelet based waveform distortion measures for assessment of denoised EEG quality with reference to noise-free EEG signal

M Saini, U Satija, MD Upadhayay - IEEE Signal Processing …, 2020 - ieeexplore.ieee.org
An objective distortion measure is very crucial to accurately quantify the distortion introduced
in the electroencephalogram (EEG) signal during the denoising process. Most of the existing …

Automated CCA-MWF algorithm for unsupervised identification and removal of EOG artifacts from EEG

M Miao, W Hu, B Xu, J Zhang… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Affective brain computer interface (ABCI) enables machines to perceive, understand,
express and respond to people's emotions. Therefore, it is expected to play an important role …

Ocular artifacts elimination from multivariate EEG signal using frequency-spatial filtering

A Bhattacharyya, A Verma, R Ranta… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The electroencephalogram (EEG) signals record electrical activities generated by the brain
cells and are used as a state-of-the-art diagnosis tool for various neural disorders. However …

A multimodal fusion depression recognition assisted decision-making system based on EEG and speech signals

X Wang, X Wan, Z Ning, Z Qie, J Li… - … , and Informatics (CCCI), 2023 - ieeexplore.ieee.org
Depression, as a widely prevalent mental disorder, significantly impacts the psychological
well-being of a substantial portion of the global population. However, existing diagnostic …

Edge of medical things implementation for deep learning-based cognitive task recognition

M Saini, D Kumar, U Satija - IEEE Internet of Things Magazine, 2022 - ieeexplore.ieee.org
The emergence of edge devices for the Internet of Medical Things (IoMT) has enabled the
integration of low-power resource-limited hardware units with communication technologies …

Eyeblink detection algorithm based on joint optimization of VME and morphological feature extraction

Y Jiang, D Wu, J Cao, L Jiang, S Zhang… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Eyeblink detection is critical in areas such as electroencephalography (EEG) artifact removal
and health monitoring. In this article, we propose a single-channel automatic eyeblink …

Swarm intelligence-based improved Adaptive chirp mode decomposition algorithm for suppression of ocular artifacts from EEG signal

B Silpa, MK Hota - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Electroencephalogram (EEG) signals are mostly contaminated with ocular artifacts (OAs)
due to eye movements and eye blinks. These artifacts make the EEG recordings difficult to …

Pembersihan Artefak EOG dari Sinyal EEG menggunakan Denoising Autoencoder

HF PERDHANA, H ZAKARIA - ELKOMIKA: Jurnal Teknik Energi …, 2022 - ejurnal.itenas.ac.id
Elektroensefalografi (EEG) adalah teknik perekaman yang merekam aktivitas elektrik pada
otak menggunakan elektroda yang ditempelkan pada kulit kepala. Artefak elektrookulografi …