AI can detect anxiety, depression in child’s speech

8
Spread the love

AI can detect anxiety, depression in child’s speech

New York: Researchers have developed an artificial intelligence (AI)-based system that can detect signs of anxiety and depression in the speech patterns of young children.

The research published in the Journal of Biomedical and Health Informatics suggests a machine learning algorithm might provide a fast and easy way of diagnosing anxiety and depression –conditions that are difficult to spot and often overlooked in young people.

“We need quick, objective tests to catch kids when they are suffering,” said study lead author Ellen McGinnis, PhD candidate at the University of Vermont in the US.

“The majority of kids under eight are undiagnosed,” McGinnis added.

Early diagnosis of these conditions is critical because children respond well to treatment while their brains are still developing, but if they are left untreated they are at greater risk of substance abuse and suicide later in life.

For the study, the researchers used an adapted version of a mood induction task called the Trier-Social Stress Task, which is intended to cause feelings of stress and anxiety in the participant.

The researchers picked a group of 71 children between ages 3 and 8 who were asked to improvise a three-minute story, and told that they would be judged based on how interesting it was.

The researcher acting as the judge remained stern throughout the speech, and gave only neutral or negative feedback.

After 90 seconds, and again with 30 seconds left, a buzzer would sound and the judge would tell them how much time was left.

“The task is designed to be stressful, and to put them in the mindset that someone was judging them,” McGinnis said.

The children were also diagnosed using a structured clinical interview and parent questionnaire, both well-established ways of identifying internalising disorders in children.

The researchers then used a Machine Learning algorithm to analyse statistical features of the audio recordings of each kid’s story and relate them to the child’s diagnosis.

They found the algorithm was highly successful at diagnosing children.

“The algorithm was able to identify children with a diagnosis of an internalizing disorder with 80% accuracy, and in most cases that compared really well to the accuracy of the parent checklist,” said senior study author Ryan McGinnis from the University of Vermont.

It can also give the results much more quickly — the algorithm requires just a few seconds of processing time once the task is complete to provide a diagnosis, the study said.


Spread the love

Leave a Reply

Please enter your comment!

The opinions, views, and thoughts expressed by the readers and those providing comments are theirs alone and do not reflect the opinions of www.mangalorean.com or any employee thereof. www.mangalorean.com is not responsible for the accuracy of any of the information supplied by the readers. Responsibility for the content of comments belongs to the commenter alone.  

We request the readers to refrain from posting defamatory, inflammatory comments and not indulge in personal attacks. However, it is obligatory on the part of www.mangalorean.com to provide the IP address and other details of senders of such comments to the concerned authorities upon their request.

Hence we request all our readers to help us to delete comments that do not follow these guidelines by informing us at  info@mangalorean.com. Lets work together to keep the comments clean and worthful, thereby make a difference in the community.

Please enter your name here