Researchers at Duke University have developed an automated video analysis software tool that identifies early childhood symptoms in children with autism by tracking and documenting children's activities. The results show that software can be like a test done to detect autism experts as marking behavior, and better than the non-professional clinical training medical personnel and medical students do.
Jordan Hashemi, a graduate student in computer and electrical engineering at Duke University, said that they did not attempt to replace experts, but extended the knowledge that only a few autistic experts possessed to all classrooms and homes through analytical tools. "We want to provide people with the tools they currently lack, because research shows that early intervention can have a major impact on the severity of the symptoms that autism can cause."
The study focused on three behavioral tests that can help diagnose autistic evidence for young children.
Video tracking test for clinical medicine
In the first experiment, the child's attention was drawn by a vibrating toy placed on the left side, and then the toy was repositioned and the shock was transferred to the right side of the child. The clinician will calculate how long the child's response to the constant change can be sustained. The second test used a toy placed in the child's line of sight to observe the delays that children had when tracking a moving toy. In the last test, the clinician rolled a ball to the child and observed the child's participation in the game.
In traditional tests, the person responsible for testing is not just a child's reaction, they must also know how long the reaction is normal. With video analysis tools, testers don't have to be distracted, and all records and analysis can be handed over to video surveillance software.
Amy Esler, assistant professor of pediatrics and autism research at the University of Minnesota, who participated in the program, pointed out that the biggest advantage of video and software is the ability to accurately detect subtle early signs of autism. The software analyzes signs of behavior such as gaze, walking patterns or movements in young children's eyes. These signs are an important basis for diagnosis.
Since video surveillance systems and analysis software are not invasive, it is expected to be used in general homes and small clinics. The Duke University research team also plans to test a new tablet app that can be completed with just one tester. The app will be able to monitor the physical and facial responses of the target objects displayed on the screen, analyze the data and automatically report all possible potential problems. Any parent, teacher, or doctor simply downloads the app and analyzes it a few minutes before the child sits.
But the development of this app will cover multiple areas, including computers, medicine, and sociology. Guillermo Sapiro, a professor of electrical and computer engineering and bioengineering at Duke University, said they are working with autism experts at Duke University School of Medicine to determine which simplified tests can identify and identify potential problems through a computer or tablet. . He pointed out that the goal of this development is to imitate social interactions and to intervene in the treatment of children with autism through early detection.
electronic thermometer,thermometers electronic digital,non contact thermometer
Shenzhen Urion Technology Co., Ltd. , https://www.urionhealth.com