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Artificial intelligence as therapeutic support - Video

Published On 2024-01-01T09:30:04+05:30  |  Updated On 1 Jan 2024 2:12 PM IST
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Overview

Artificial intelligence as therapeutic support

The face is a mirror for a person's emotional state. The interpretation of facial expressions as part of psychotherapy or psychotherapeutic research, for example, is a very effective way of characterizing how a person is feeling in that particular moment. Back in the 1970s, psychologist Paul Ekmann developed a standardized coding system to assign basic emotions such as happiness, disgust or sadness to a facial expression in an image or video sequence.

“Ekman’s system is very widespread, and represents a standard in psychological emotion research,” says Dr. Martin Steppan, psychologist at the Faculty of Psychology at the University of Basel.

But the process of analyzing and interpreting recorded facial expressions as part of research projects or psychotherapy is extremely time-consuming, which is why psychiatry specialists often use less reliable, indirect methods such as skin conductance measurements, which can also be a measure of emotional arousal.

“We wanted to find out whether AI systems can reliably determine the emotional states of patients in video recordings,” says Martin Steppan, who developed the study together with emeritus Professor Klaus Schmeck, Dr. Ronan Zimmermann and Dr. Lukas Fürer from the UPK. The researchers published their findings in the journal Psychopathology.

The researchers used freely available artificial neural networks that were trained in the detection of six basic emotions (happiness, surprise, anger, disgust, sadness and fear) using over 30,000 facial photos. This AI system then analyzed video data from therapy sessions with a total of 23 patients with borderline personality pathology at the Center for Scientific Computing at the University of Basel. The high-performance computer had to process over 950 hours of video recordings for this study.

The results were astonishing: statistical comparisons between the analysis of three trained therapists and the AI system showed a remarkable level of agreement. The AI system assessed the facial expressions as reliably as a human but was also able to detect even the most fleeting of emotions within the millisecond range, such as a brief smile or expression of disgust.

The results were astonishing: statistical comparisons between the analysis of three trained therapists and the AI system showed a remarkable level of agreement. The AI system assessed the facial expressions as reliably as a human but was also able to detect even the most fleeting of emotions within the millisecond range, such as a brief smile or expression of disgust.

Reference: Artificial intelligence as therapeutic support; Psychopathology, DOI: 10.1159/000534811

Speakers

Anshika Mishra

Anshika Mishra is a dedicated scholar pursuing a Masters in Biotechnology, driven by a profound passion for exploring the intersection of science and healthcare. Having embarked on this academic journey with a passion to make meaningful contributions to the medical field, Anshika joined Medical Dialogues in 2023 to further delve into the realms of healthcare journalism.

Dr. Kamal Kant Kohli

Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751
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