Ocular Artifacts realization through optimized scheme

Author:

Sahoo Santosh KumarORCID,Mohapatra Sumant Kumar

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Reference38 articles.

1. Betta M, Gemignani A, Landi A, Laurino M, Piaggi P, Menicucci D (2013) Detection and removal of ocular artifacts from EEG signals for an automated REM sleep analysis. IEEE Eng Med Biol Soc 2013:5079–5082

2. De Fallani FV, Astolfi L, Cincotti F, Mattia D, la Rocca D, Maksuti E, Salinari S, Babiloni F, Vegso B, Kozmann G, Nagy Z (2009) Evaluation of the brain network organization From EEG signals: a preliminary evidence in stroke patient. Neuroplast Neurogen 292(12):2023–2031

3. Gajbhiye P, Tripathy RK, Bhattacharyya A, Pachori RB (2019) Novel approaches for the removal of motion artifact from EEG recordings. IEEE Sensors J 19(22):10600–10608

4. Jafarifarmand A, Badamchizadeh MA, Khanmohammadi S, Nazari MA, Tazehkand BM (2017) Real-time ocular artifacts removal of EEG data using a hybrid ICA-ANC approach. Biomed Signal Process Control 31:199–210

5. Jaffino G, Jose JP, Sundaram M (2021) Grey wolf optimization with deep recurrent neural network for epileptic seizure detection in EEG signals. In: 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp 1–5

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