Enhanced EEG-Based Mental State Classification : A novel approach to eliminate data leakage and improve training optimization for Machine Learning

Maxime Girard; Rémi Nahon; Enzo Tartaglione; Van-Tam Nguyen

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arXiv · 2312.09379

Enhanced EEG-Based Mental State Classification : A novel approach to eliminate data leakage and improve training optimization for Machine Learning

Maxime Girard·Rémi Nahon·Enzo Tartaglione·Van-Tam Nguyen

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Abstract

In this paper, we explore prior research and introduce a new methodology for classifying mental state levels based on EEG signals utilizing machine learning (ML). Our method proposes an optimized training method by introducing a validation set and a refined standardization process to rectify data leakage shortcomings observed in preceding studies. Furthermore, we establish novel benchmark figures for various models, including random forest and deep neural networks.

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Maxime Girard, Rémi Nahon, Enzo Tartaglione, Van-Tam Nguyen. 2023-12-14. Enhanced EEG-Based Mental State Classification : A novel approach to eliminate data leakage and improve training optimization for Machine Learning. https://arxiv.org/abs/2312.09379

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