Related Experiment Video
Updated: Jan 9, 2026

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
Published on: July 31, 2016
Artificial intelligence techniques applied to anxiety disorders recognition: a systematic review
Edgar Degante-Aguilar1, Roberto Angel Melendez-Armenta1, Giovanni Luna-Chontal1
1Affective Computing and Educational Innovation Laboratory, Division of Graduate Studies and Research, Tecnológico Nacional de México-Instituto Tecnológico Superior de Misantla, Misantla, Veracruz, Mexico.
Objective:
This Systematic Review aims to provide a comprehensive analysis of the current state of anxiety disorder detection methods using Artificial Intelligence (AI), focusing on their accuracy and the scope of research. This review is tailored for researchers, clinicians, and technology developers seeking to understand the advancements in AI-driven mental health diagnostics.
Methodology:
A Systematic Review was conducted following the PRISMA Statement guidelines, utilizing databases such as IEEE Xplore, PubMed, ScienceDirect, and SpringerLink. The review included studies focusing on the diagnosis of anxiety disorders using quantitative data and AI techniques, excluding those solely focused on depression or lacking experimental datasets.
Results:
A total of 119 studies were analyzed, revealing the application of Machine Learning and Deep Learning techniques in detecting anxiety disorders from diverse data sources, including self-reports, physiological data, and social network data. The findings indicate that AI-driven methods demonstrate higher accuracy compared to traditional anxiety disorder detection tests, providing valuable insights for clinicians and researchers exploring improved diagnostic tools.
Conclusions:
This review highlights the critical role of AI in optimizing the detection and treatment of anxiety disorders. It offers a current and detailed overview of advancements in this field, making it a key resource for researchers, healthcare professionals, and technology developers aiming to integrate AI into mental health practices. The synthesis of findings provides a clear understanding of the current landscape and potential future directions in AI-based anxiety detection.
Systematic Review Registration:
https://www.crd.york.ac.uk/PROSPERO/view/CRD420251026205, identifier CRD420251026205.
Related Concept Videos
Behavior Therapy
Exposure therapy is a cornerstone of behavioral treatment for anxiety disorders. It involves systematic exposure to feared stimuli, either in real...
Anxiety: Overview
Individuals with anxiety often experience a range of physical and emotional symptoms, including sweating, trembling, tachycardia, and disturbances in sleep patterns. These symptoms vary in intensity and frequency but are generally disruptive and distressing.
Generalized Anxiety Disorder
Anxiolytic Drugs: Overview
Primary Types of Anxiolytic Drugs
1. Benzodiazepines:
Benzodiazepines bind to the GABA-A receptor in the brain, enhancing GABA's interaction. This action reduces neurotransmission, effectively blocking anxiety-associated limbic...
Modeling in Therapy
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
Social Anxiety Disorder

