Entropy difference-based EEG channel selection technique for automated detection of ADHD.
Attention deficit hyperactivity disorder (ADHD) is one of the common neurodevelopmental disorders in children. This paper presents an automated approach for ADHD detection using the proposed entropy difference (EnD)-based encephalogram (EEG) channel selection approach. In the proposed approach, we s...
Saved in:
| Main Authors: | Shishir Maheshwari, Kandala N V P S Rajesh, Vivek Kanhangad, U Rajendra Acharya, T Sunil Kumar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0319487 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MLAR-Net: A Multilevel Attention-Based ResNet Module for the Automated Recognition of Emotions Using Single-Channel EEG Signals
by: M. Maithri, et al.
Published: (2025-01-01) -
Methylphenidate Effects on EEG and ADHD
by: J Gordon Millichap
Published: (1998-05-01) -
Biological Markers in Diagnosis of ADHD: EEG Theta/Beta Ratio in Diagnosis of ADHD
by: J Gordon Millichap, et al.
Published: (2014-08-01) -
Optimal Multivariate Transfer Entropy to Determine Differences in Short and Long-Range EEG Connectivity in Children with ADHD and Healthy Children
by: Ali Ekhlasi, et al.
Published: (2025-03-01) -
Channel and model selection for multi-channel EEG input to neural networks
by: Kento Harachi, et al.
Published: (2024-12-01)