This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional ...

2018/08/13 · This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional ...

This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional ...

Highlighting mentions of paper "Intracerebral EEG Artifact Identification Using Convolutional Neural Networks" ×. EEG Artifact Removal on MayoClinic_iEEG.

Intracerebral EEG Artifact Identification Using Convolutional Neural Networks ... We show that the proposed technique can be used as a generalized model for iEEG ...

2022/02/11 · We propose a method based on the convolutional neural network (CNN) that allows the removal of eye blink artifacts from the EEG signal. The ...

The main purpose of this paper is to provide information on how to create a convolutional neural network (CNN) for extracting features from EEG signals.

A convolutional neural network enhanced by transformers using belief matching (BM) loss for automated detection of five types of artifacts: chewing, ...

The present work presents a review of existing applications of ML techniques in iEEG data, discusses the relative merits and limitations of the various ...

2021/06/10 · Nejedly et al. used a CNN in conjunction with fully automated image processing procedures to automati- cally detect artifacts in intracerebral ...