Erin Solovey, Postdoctoral Fellow, Humans and Automation Lab (HAL)

MIT

Enhancing Interactive Systems with Real-time Brain Input

Monday, April 1, 4:00 PM

Packard Lab Room 466

Reception in lobby of Packard Lab prior to seminar

Abstract: Most human-computer interaction techniques cannot fully capture the richness of the user’s thoughts and intentions when interacting with a computer system. For example, when we communicate with other people, we do not simply use words, but also accompanying cues that give the other person additional insight to our thoughts. At the same time, several physiological changes occur that may or may not be detected by the other person. When we communicate with computers, we also generate these additional signals, but the computer cannot sense such signals, and therefore ignores them. Detecting these signals in real time and incorporating them into the user interface could improve the communication channel between the computer and the human user with little additional effort required of the user.

In this talk, I will discuss our research demonstrating effective use of brain sensor data to expand the bandwidth between the human and computer. Using a relatively new brain-sensing tool called functional near-infrared spectroscopy (fNIRS), we can detect signals within the brain that indicate various cognitive states. This device provides data on brain activity while remaining portable and non-invasive, which opens new doors for human-computer interaction research. The real-time cognitive state information can be used as an implicit, supplemental input channel to provide the user with a richer and more supportive environment, particularly in challenging or high workload situations such as management of unmanned aerial vehicles, driving, air traffic control, video games, healthcare, education, and anything involving information overload, interruptions or multitasking. In addition, while most of my research has focused on the broader population of healthy users, many of the results would benefit disabled users as well, by providing additional channels of communication in a lightweight manner.

Bio: Erin Solovey is a postdoctoral fellow in the Humans and Automation Lab (HAL) at MIT. Her main research area is human-computer interaction, specifically next-generation interaction techniques. Dr. Solovey has received several awards including the NSF/CRA Computing Innovation Fellowship and a CHI Best Paper Honorable Mention Award, and her work has been covered in MIT Technology Review, Slashdot, Engadget and others. She has also conducted research at MIT Lincoln Laboratory and Microsoft Research. Previously, she was a software engineer at Oracle, and also has experience at several startups. She received her bachelor’s degree in computer science from Harvard University, and her M.S. and Ph.D. in computer science from Tufts University, working in the Human-Computer Interaction Lab.

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