Development and Evaluation of Body-Worn Sensors to Identify Functions of Stereotypical Behaviors for Children with Autism
PI: Youjia Hua, Ph.D. Associate Professor Department of Curriculum, Instruction and Special Education Curry School of Education [email protected]
PI: Matthew S. Gerber, Ph.D. Assistant Professor, Department of Systems and Information, Engineering School of Engineering and Applied Science [email protected]
Stereotypy affects 44% of children with autism spectrum disorder (ASD) and negatively impacts learning, adaptive behavior, and inclusion. Treatment of stereotypy requires educators to conduct functional behavior assessment (FBA) to identify variables that maintain stereotypy. This proposal brings together autism and engineering researchers to develop and pilot test an innovative FBA data collection system for treatment of stereotypical behaviors of children with ASD. The innovation has two components: a) body-worn sensors for data collection and b) sensor-initiated prompts for educators to conduct FBA. The proposed research will increase reliability of FBA data and provide support for future development of the data collection system under external funding. Over three phases of investigation, quasi-experimental studies, and a culminating pilot deployment, we will explore the effectiveness and feasibility of this assessment tool with the goal of developing and extending its application as an effective intervention for children with ASD.