Chestek, Cynthia - cchestek
Methodologies: Data, Statistics and Stochastic Methods, Machine Learning

Cynthia Chestek

Assistant Professor, Biomedical Engineering


Electrical Engineering and Computer Science, ECE, Center for Network and Storage-Enabled Collaborative Computational Science

Cynthia Chestek is an Assistant Professor of Biomedical Engineering, Electrical Engineering – Electrical and Computer Engineering Division, and the Neurosciences Graduate Program.

The Chestek lab focuses on brain machine interface (BMI) systems using 100 channel arrays implanted in motor and pre-motor cortex. The goal of this research is to eventually develop clinically viable systems to enable paralyzed individuals to control prosthetic limbs, as well as their own limbs using functional electrical stimulation and assistive exoskeletons. The lab apply a variety of machine learning algorithms to large-scale neural datasets obtained from spiking activity or field potentials in order to decode the motor commands. This is done both offline, and in real-time during experiments. Other computational challenges include mitigating non-stationarities in neural recordings over time. Over the next few decades, the size of these datasets is most likely to increase with the development of larger electrode arrays, and novel surgical techniques for implanting them.