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Kabupaten Nias Selatan

Badan Riset dan Inovasi Nasional

Informasi Dataset

07-11-2022

12-08-2024

c90a75a5-e41e-4b71-829e-49ed70699047

Dataset Serupa
Extraction of Mental Task in Recorded EEG Signal using ICA-JADE Algorithm

An instrument that has special function to record electrical brain activity in s...

Adaptive Principal Component Analysis based Recursive Least Squares for Artifact...

Artifacts or noise sources increase the difficulty in analyzing the EEG and to o...

Artifacts Removal of EEG Signals using Adaptive Principal Component Analysis

Analysis of EEG activity usually raises the problem of differentiating between g...

Automatic Artifacts Removal of EEG Signals using Robust Principal Component Anal...

Analysis of EEG activity usually raises the problem of differentiating between g...

Blind Source Separation for Ocular Artifacts Elimitation from EEG Signals

In the modern world of automation, biological signals, especially Electroencepha...

INFORMASI: Data berikut ini masih dalam proses pemenuhan Prinsip SDI.

JADE-ICA Algorithm for EOG Artifact Removal in EEG Recording

Terbatas

In EEG recording, the signal obtained is not entirely derived from the brain, but maybe contaminated by other signals called artifacts, such as Electrooculogram (EOG), Electrocardiogram (ECG) and Electromyogram (EMG). While EEG signals were recorded, especially electrodes located near the eyes, will be affected by EOG artifacts. These artifacts or noise may affect the outcome of the EEG recording. In this paper, an independent component analysis algorithm, i.e. JADE algorithm, is proposed to remove the artifacts. The proposed method was tested in real EEG records acquired from seven healthy subjects. The experimental result show that the JADE method was effectively remove the artifacts from all subjects. International Conferences on Technology, Informatics, Management, Engineering & Environtment, 19-21 August 2014, Bandung Indonesia.

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