Neural Interfaces and Signal Processing (NISP) Lab

Welcome to Dr. Jihye Bae's Neural Interfaces and Signal Processing Lab!

Research in Neural Interfaces and Signal Processing Lab aims to develop systems and methods to assist patients with neuromuscular disabilities and neurological disorders. NISP Lab’s research includes the areas of signal processing, machine learning, and their applications in medicine. Dr. Bae’s work focuses on the use of brain signals, from microscopic to mesoscopic-scales, to develop neural decoders in brain machine interfaces to help create upper limb prosthetics for patients with neuromuscular disabilities. In addition, Dr. Bae is interested in investigating electroencephalography (EEG) signal processing and source imaging techniques to localize seizure-onset zones in epilepsy. NISP lab members are investigating signal processing and machine learning techniques to ultimately provide daily life assistance to patients with neuromuscular disabilities and neurological disorders.

News

Publication: in Frontiers in Systems Neuroscience

I delightfully announce Benton Girdler and William Caldbeck's jounal publication in Frontiers in System Neuroscience! 

The article is entitled “Neural Decoders Using Reinforcement Learning in Brain Machine Interfaces: A Technical Review.”

This paper is accessible on the following link: https://doi.org/10.3389/fnsys.2022.836778

Publication: in Frontiers in Human Neuroscience

I delightfully announce William Plucknett's jounal publication in Frontiers in Human Neuroscience! The article is entitled “Metric Learning in Freewill EEG Pre-Movement and Movement Intention Classification for Brain Machine Interfaces.”

This paper is accessible on the following link: https://doi.org/10.3389/fnhum.2022.902183

Publication: in International Forum of Allergy and Rhinology by Benton Girdler

I delightfully announce Benton Girdler's jounal publication in International Forum of Allergy and Rhinology! The article is entitled “Feasibility of a deep learning-based algorithm for automated detection and classification of nasal polyps and inverted papillomas on nasal endoscopic images.”

This paper is accessible on the following link: https://onlinelibrary.wiley.com/doi/10.1002/alr.22854