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The Emerging Role of Advanced Technologies in Neurological Diseases: Leveraging Facial Electromyography for Enhanced Emotion Recognition in AI Systems
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Author(s): Khaoula Ben Ali (Carthage University, Tunisia)and Adnène Arbi (Carthage University, Tunisia)
Copyright: 2026
Pages: 32
Source title:
The Emerging Role of Advanced Technologies in Neurological Diseases
Source Author(s)/Editor(s): Adnène Arbi (National Institute of Applied Sciences and Technology, University of Carthage, Tunisia & Laboratory of Mathematical Engineering, Tunisia Polytechnic School, University of Carthage, Tunisia)and Walid Ben Ameur (Faculty of Sciences of Gabes, Tunisia)
DOI: 10.4018/979-8-3373-2706-8.ch007
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Abstract
Interpreting human emotional states is crucial for advanced AI in human-computer interaction. Addressing this need, we propose a comprehensive methodology centered on facial Electromyography (fEMG) signals. fEMG offers a direct, objective measure of muscle activation for genuine emotional responses. We detail a complete pipeline: from fEMG acquisition to advanced time-frequency analysis using Continuous Wavelet Transform (CWT). This robust feature extraction integrates with machine learning models for emotion classification and prediction. Leveraging fEMG's temporal dynamics, we aim to enhance emotion recognition system accuracy and real-time capability. This chapter addresses the methodology and demonstrates its effectiveness through the rigorous validation of its evaluation framework, rigorously validated, demonstrating exceptionally consistent performance in both continuous regression and discrete classification tasks with simulated data. This strong alignment between predicted and ground truth confirms the reliability and correctness of the pipeline depoloyed.
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