Brain-Computer Interface (BCI) systems convert central nervous system (CNS) activity to artificial output that is then used to replace, restore, enhance, supplement, or improve natural CNS output. BCI functions through acquiring brain signals, identifying patterns, and producing actions based on the observed CNS patterns. This process allows users to interact with their environment without having to use their peripheral nerves and muscles. Output produced by a BCI system can be used to interact with applications ranging from wheelchairs to video games. In this talk, Dr. Crawford will discuss his brain-robot interaction research that examines the use of BCI to control robots. This presentation will also cover his related work that investigates leveraging block-based programming for neurofeedback application development.
Dr. Chris S. Crawford is an Assistant Professor at the University of Alabama’s Department of Computer Science. He directs the Human-Technology Interaction Lab (HTIL). His research focuses on human-robot interaction and Brain-Computer Interfaces (BCIs). He has investigated systems that provide computer applications and robots with information about a user’s cognitive state. He previously developed a brain-drone racing system that was featured on over 800 news outlets including Discovery, USA Today, and the New York Times, and Forbes. Along with investigating brain-robot interaction applications, Dr. Crawford also developed Neuroblock, a tool designed to engage K-12 student in neurofeedback applications development. He recently won a NSF CAREER award for his research.