Flower Automata Pattern-Based Discrimination of Fibromyalgia From Control Subjects Using Fusion of Sleep EEG and ECG Signals

Flower Automata Pattern-Based Discrimination of Fibromyalgia From Control Subjects Using Fusion of Sleep EEG and ECG Signals

Electroencephalogram (EEG) and electrocardiogram (ECG) signals provide vital insights into brain and heart activity and are widely used in automated medical diagnostics. This study introduces a novel, multimodal fibromyalgia detection system developed by the fusion of EEG and ECG signals recorded du...

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Bibliographic Details
Main Authors: Prabal Datta Barua, Makiko Kobayashi, Sengul Dogan, Mehmet Baygin, Turker Tuncer, Jose Kunnel Paul, Thomas Iype, U. R. Acharya
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Attention maximum pooling
automata-based dynamic patterns
EEG and ECG signal classification
fibromyalgia detection
flower automata pattern
intersection-based feature selection
Online Access:https://ieeexplore.ieee.org/document/11014066/
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