Klein Franziska, Müller-Von Aschwege Frerk, Elfert Patrick, Räker Julien, Philipsen Alexandra, Braun Niclas, Selaskowski Benjamin, Wiebe Annika, Guth Matthias, Spallek Johannes, Seuss Sigrid, Storey Benjamin, Geppert Leo N, Lück Ingo, Hein Andreas
R&D Division Health, OFFIS e.V., Oldenburg, Germany.
Department for Psychiatry, Psychotherapy and Psychosomatics, RWTH University Hospital Aachen, Germany.
Stud Health Technol Inform. 2023 Oct 20;309:18-22. doi: 10.3233/SHTI230731.
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.
重度抑郁症（MDD）对患者的日常生活有重大影响。本概念文件介绍了一个旨在通过创新治疗系统应对MDD挑战的项目。该项目包括两个用例：多模态神经反馈（NFB）疗法和基于人工智能的虚拟治疗助手（VTA）。多模态NFB整合脑电图（EEG）和功能近红外光谱（fNIRS）以全面评估脑功能。目标是开发一个用于EEG-fNIRS整合的开源NFB工具箱，并由VTA增强以优化疗效。VTA将能够收集行为数据，提供个性化反馈并在日常生活中支持MDD患者。该项目旨在通过整合数字疗法、人工智能和移动应用程序来改善抑郁症治疗，从而有可能改善抑郁症患者的治疗效果和可及性。
