Neurofeedback Scheduling in Skill Learning

Biofeedback technologies readily provide massive amounts of biometric data to individuals, but less is known about how frequently such feedback should be delivered for optimal learning or health outcomes. In this internally funded work in collaboration with i-BrainTech, we are investigating the impact of different neurofeedback schedules on skill learning in i-Braintech's brain-computer interface (BCI).

Movement-Assistive Robotics in Motor Learning

Movement-assistive robotics such as exoskeletons hold great promise for rehabilitation contexts, but they have primarily been studied with walking, which can be categorized as a highly complex movement skill that most users are already skilled at. In this NSF-funded collaborative work with FAMU-FSU College of Engineering (Dr. Taylor Higgins) and Georgia Tech (Dr. Shreyas Kousik), we simplify the problem space by studying how intelligent movement-assistive robotics can be used to improve the learning of a unicycle (a balance-related skill like walking, but few people are skilled at).

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Measuring Technological Savviness

Given the rapid advancement of intelligent technologies in modern society, the ability to effectively learn new technologies (“tech-savviness”) is growing into an essential 21st-century skill. Artificial intelligence (AI) is also reshaping learning environments, and consequently, it is important to understand what technological experiences shape optimal learning in AI-assisted contexts. This funded, collaborative program of work examines psychophysiological indices of learning in contexts with digital tools, as well as technology experiences and behaviors associated with adaptive use of available assistive tools for learning (e.g., AI).

Neural Mechanisms of Balance-Related Anxiety

In humans, balance and emotion are highly integrated processes. Many balance-related disorders are accompanied by anxiety-related disorders due to proximal neural circuitry between the vestibular and limbic system. Thus, uncovering neural mechanisms involved in balance-related anxiety would provide important clinical markers for balance disorders and injury recovery. In this work, we use EEG to study neural markers associated with losing balance.