CPS: A Tool for Classification and Prediction of Autism with STA
Autism diagnostic procedure is a subjective, challenging and expensive procedure and relies on behavioral, historical and parental report information. In our previous research, we investigate whether it is possible to detect autism based on eye-movement sequences, in particular, we propose to use Scanpath Trend Analysis (STA) which is designed for identifying a trending path of a group of users on a web page based on their eye movements. We first identify the trending paths of people with autism and neurotypical people. To detect whether or not a person has autism, we calculate the similarity of his/her path to the trending paths of people with autism and neurotypical people. If the path is more similar to the trending path of neurotypical people, we classify the person as a neurotypical person. Otherwise, we classify her/him as a person with autism. In this capstone project, the aim is to develop an online web application to automate the process
Type of Project
- Undergraduate Graduation Project
Links
People
- Eda Sütoğlu (Undergraduate Student)
- Sena Sunar (Undergraduate Student)
- Günseli Sevinç (Undergraduate Student)
- Pınar Dilbaz (Undergraduate Student)
- Dr. Şükrü Eraslan (Supervisor)
- Dr. Yeliz Yeşilada (Supervisor)