Researchers at Texas State Use Machine Learning to Help Children with Autism Identify Facial Expressions


Newswise — According to the Emotional Intelligence Academy, there are seven universal facial expressions humans possess:  happiness, sadness, fear, disgust, anger, contempt and surprise. For individuals with autism spectrum disorder (ASD), it can be difficult to distinguish among these emotions during personal interactions. 

A team of Texas State University researchers including Dr. Damian Valles, assistant professor at the Ingram School of Engineering; Dr. Maria Resendiz, associate professor for the College of Health Professions; and graduate student MD Inzamam Haque, is developing a mobile application to help children with ASD recognize facial expressions on a device screen allowing children to better interpret nonverbal ques in social settings. 

Because of recent advances in facial recognition technology, Dr. Valles says they can help lessen the communication gap for children with autism. “I don’t think even five or ten years ago, we could have had this discussion based on the technology available.”  

Using the app, parents and educators direct facial expressions toward the child, then the child can learn to identify those expressions by viewing outlines of a face indicating that need to be made in the technology. Dr. Valles suggests that this new technology can also be used for airport security. By using facial recognition, authorities could one day identify potential threats based on nonverbal cues.  

  • share-facebook-Researchers at Texas State Use Machine Learning to Help Children with Autism Identify Facial Expressions
  • share-twitter-Researchers at Texas State Use Machine Learning to Help Children with Autism Identify Facial Expressions

Comment/Share

Chat now!