In a new study from Simon Fraser University, researchers found using artificial intelligence (AI) could detect behavioral signs of anxiety with more than 90% accuracy.
The findings suggest that AI could have future applications for addressing mental health and well-being.
Anxiety disorder is the most common form of mental disorder, according to the American Psychiatric Association (APA), impacting 30 percent of the adult population at some point in their lives.
In the study, the team collected an extensive range of data from adult participants. Participants performed a series of activities in a specific order while wearing sensors that recorded their movements.
The researchers created a dataset of activities of typical anxiety-displaying behaviors for the sensors to detect, including idle sitting, nail-biting, knuckle cracking and hand tapping.
Their behaviors were analyzed using deep learning algorithms and computational hybrid models.
The researchers suggest AI could help in the analysis, diagnosis, treatment and monitoring of psychological disorders such as anxiety disorder (AD).
They hope this method can help to provide more accurate data for clinical research and practitioners.
The team says the rapid development in the field of AI and sensor technology has made it possible to access and process the data related to mental, emotional and behavior disorders.
It can be further researched and explored to understand unspoken behaviors and improve mental health at large.
If you care about anxiety, please read studies about this TB medication may help fight anxiety and fear and findings of this blood pressure drug may help reduce anxiety and pain.
For more information about anxiety and your health, please see recent studies about anxiety and depression: Why doctors are prescribing gardening rather than drugs and results showing that common depression drug may reduce anxiety more than depressive symptoms.
The study is published in the journal Pervasive and Mobile Computing. One author of the study is Gulnaz Anjum.
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