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The objective of this subproject is to validate the efficacy of the fNIRS real-time anxiety monitoring and neurofeedback system. In the first year, the cerebral hemodynamics measured by commercial fNIRS during resting state and cognitive tasks from 60 generalized anxiety disorder (GAD) patients and 30 healthy subjects will be processed and analyzed using AI algorithms. The novel anxiety fNIRS biomarker will be identified and correlated to clinical anxiety scales (such as HARS and STAI). In the second year, the validity and responsiveness of the AI-fNIRS biomarker will be validated. The accuracy of using AI-fNIRS biomarker to predict the diagnosis of GAD (according to DSM-5) and anxiety rating scales will be calculated from 60 GAD patients and 30 healthy subjects. In the third year, a neurofeedback method using AI-fNIRS biomarkers to guide digital cognitive behavior therapy (dCBT) through
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