Spatial Cognitive EEG Feature Extraction and Classification Based on MSSECNN and PCMI
With the aging population rising, the decline in spatial cognitive ability has become a critical issue affecting the quality of life among the elderly. Electroencephalogram (EEG) signal analysis presents substantial potential in spatial cognitive assessments. However, conventional methods struggle t...
Saved in:
Main Authors: | Xianglong Wan, Yue Sun, Yiduo Yao, Wan Zuha Wan Hasan, Dong Wen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Bioengineering |
Subjects: | |
Online Access: | https://www.mdpi.com/2306-5354/12/1/25 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing plant disease detection through deep learning: a Depthwise CNN with squeeze and excitation integration and residual skip connections
by: Asadulla Y. Ashurov, et al.
Published: (2025-01-01) -
Squeeze-and-Excitation Vision Transformer for Lung Nodule Classification
by: Xiaozhong Xue, et al.
Published: (2025-01-01) -
Load recognition method based on convolutional neural network and attention mechanism
by: ZHAO Yitao, et al.
Published: (2025-01-01) -
A composite improved attention convolutional network for motor imagery EEG classification
by: Wenzhe Liao, et al.
Published: (2025-02-01) -
A Pre-Activation Residual Convolutional Network With Attention Modules for High-Resolution Segmented EEG Emotion Recognition
by: Ioannis Charalampous, et al.
Published: (2025-01-01)