HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification-Reference-Cited by-同舟云学术

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HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification

Published:2024-08 Issue: Volume:178 Page:108788
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Kim Minsu,Im Chang-Hwan^ORCID

Publisher

Elsevier BV

Reference62 articles.

1. A comprehensive review of EEG-based brain–computer interface paradigms;Abiri;J. Neural. Eng.,2019

2. Progress in brain computer interface: challenges and opportunities;Saha;Front. Syst. Neurosci.,2021

3. Emotional state classification from EEG data using machine learning approach;Wang;Neurocomputing,2014

4. Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques;Amin;Australas. Phys. Eng. Sci. Med.,2015

5. Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features;Shim;Schizophr. Res.,2016

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