Spectral, phase, and their interacting components for complexity analysis of depression electroencephalogram
Depression is a severe mental disorder, and patients suffering from depression differ significantly from those in the control group in terms of electroencephalogram (EEG) signal complexity. Although most of the existing studies have focused on overall complexity analysis, very few have explored the...
Saved in:
| Main Authors: | Yuman Luo, Shumei Zhu, Jiaqi Yu, Jie Ding, Zhangyang Xia, Wei Lu, Qiong Wang, Wanyi Yi, Wenpo Yao, Jun Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-03-01
|
| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0257857 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Complexity Analysis of Electroencephalogram Dynamics in Patients with Parkinson’s Disease
by: Guotao Liu, et al.
Published: (2017-01-01) -
Night sleep electroencephalogram power spectral analysis in excessive daytime sleepiness disorders
by: Rubens Reimão
Published: (1991-06-01) -
Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease
by: Ali H. Husseen Al-Nuaimi, et al.
Published: (2018-01-01) -
Cross-Subject Motor Imagery Electroencephalogram Decoding with Domain Generalization
by: Yanyan Zheng, et al.
Published: (2025-05-01) -
Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods
by: Zhishui You, et al.
Published: (2025-05-01)