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TOWARDS AN ADAPTIVE MENTAL HEALTH THERAPY: A WEARABLE EEG-BASED DECODED NEUROFEEDBACK SYSTEM USING TRANSFORMER TECHNOLOGY

Paulino Salmon, M.Sc. and Jaymar Soriano, D.Sc.

Solution

Decoded neurofeedback harnesses machine learning to interpret brain activity patterns in real-time from which neurofeedback therapy is specifically tailored to the user's mental state. By leveraging pretrained data from other mental health conditions, the use of transformers can improve its predictive capabilities and tailor interventions more effectively.

Problem Statement

With growing diversity and complexity of mental health issues, there is an urgent need for adaptable and personalized therapeutic approaches. Adaptive therapy aims to create interventions that can respond dynamically to specific mental health challenges, thereby improving outcomes and accessibility.

Features

• Use of Wearable EEG technology. This modality is particularly significant for developing countries like the Philippines.
• Transformer technology enables continuous adaptation of therapeutic strategies drawing on insights from closely related mental health conditions.