Developing Advanced AI Ecosystems to Enhance Diagnosis and Care for Patients with Depression
Franziska Klein, Frerk Müller-Von Aschwege, Patrick Elfert, Julien Räker, Alexandra Philipsen, Niclas Braun, Benjamin Selaskowski, Annika Wiebe, Matthias Guth, Johannes Spallek, Sigrid Seuss, Benjamin Storey, Leo N. Geppert, Ingo Lück, Andreas Hein
Major Depressive Disorder (MDD) has a significant impact on the daily lives of those affected. This concept paper presents a project that aims at addressing MDD challenges through innovative therapy systems. The project consists of two use cases: a multimodal neurofeedback (NFB) therapy and an AI-based virtual therapy assistant (VTA). The multimodal NFB integrates EEG and fNIRS to comprehensively assess brain function. The goal is to develop an open-source NFB toolbox for EEG-fNIRS integration, augmented by the VTA for optimized efficacy. The VTA will be able to collect behavioral data, provide personalized feedback and support MDD patients in their daily lives. This project aims to improve depression treatment by bringing together digital therapy, AI and mobile apps to potentially improve outcomes and accessibility for people living with depression.
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