Removal of Physiological Artifacts from Electroencephalogram Signals: A Review and Case Study

Mahmood, Danyal; Nisar, Humaira; Voon, Yap Vooi

doi:10.1109/icspc53359.2021.9689094

Cited by 9 publications

(1 citation statement)

References 29 publications

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“…A case study was performed on various artefact removal techniques such as adaptive filtering, regression, ICA, CCA, WT etc. for removal of ocular artefact by Danyal Mahmood et al, [25] and concluded that regression is suitable for ocular artefact removal. An improved masking-aided minimum arclength empirical mode decomposition (MAMA-EMD) was proposed by Mingai Li et al [26] for removal of ocular artefact, which was later combined with kernel independent component analysis (KICA).…”

Section: Literature Reviewmentioning

confidence: 99%

Removal of EOG Artefact from EEG – A Review

Anand

Radharapu

Pradhan

et al. 2022

Advances in Transdisciplinary Engineering

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An electroencephalogram (EEG) is a medical examination that records the electrical activity of the human brain. In order to record these signals, electrodes are placed on the scalp, and these electrodes detect any activity of the brain cells. This result is used to diagnose patients with epilepsy, sleep disorders, brain tumors, seizure disorders, and brain disorders. However, these signals are often corrupted by various artefacts either generated from the human body(physiological) or the electrical apparatus used(non-physiological). The removal of these artefacts is vital as their presence may result in the wrong diagnosis of a disease. One of these artefacts is generated because of various kinds of eye movements, i.e. EOG. In this paper, we will be focusing on how ocular artefacts occur and how they affect the EEG signal. Later we will look into different types of artefact removal techniques and how they perform differently from each other on the basis of different factors such as signal-to-noise-ratio etc. The aim of this study is to get a detailed understanding of various ocular artefact removal techniques, challenges related to them and finding an efficient way to obtain an uncorrupted EEG signal.

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Section: Literature Reviewmentioning

confidence: 99%