Deep VMD-attention network for arrhythmia signal classification based on Hodgkin-Huxley model and multi-objective crayfish optimization algorithm.
Recent research for arrhythmia classification is increasingly based on AI-driven approaches, which are primarily grounded in ECG data, but often neglect the mathematical foundations of cardiac electrophysiology. A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) mod...
Saved in:
| Main Authors: | Hang Zhao, Xiongfei Yin |
|---|---|
| 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.0321484 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition
by: Yihang Zhang, et al.
Published: (2025-02-01) -
The what and where of adding channel noise to the Hodgkin-Huxley equations.
by: Joshua H Goldwyn, et al.
Published: (2011-11-01) -
Weak Quasiperiodic Signal Propagation through Multilayer Feed-Forward Hodgkin–Huxley Neuronal Network
by: Yuangen Yao, et al.
Published: (2020-01-01) -
Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model
by: Yihong Wang, et al.
Published: (2017-01-01) -
A multi-base harmonic balance method applied to Hodgkin-Huxley model
by: Aymen Balti, et al.
Published: (2018-05-01)