3 papers
eess.SP2025
A Statistical Mixture-of-Experts Framework for EMG Artifact Removal in EEG: Empirical Insights and a Proof-of-Concept Application
Benjamin J. Choi, Griffin Milsap, Clara A. Scholl +2
Effective control of neural interfaces is limited by poor signal quality. While neural network-based electroencephalography (EEG) denoising methods for electromyogenic (EMG) artifa…
q-bio.NC2025
EEG Foundation Models for BCI Learn Diverse Features of Electrophysiology
Mattson Ogg, Rahul Hingorani, Diego Luna +3
Brain computer interface (BCI) research, as well as increasing portions of the field of neuroscience, have found success deploying large-scale artificial intelligence (AI) pre-trai…
cs.LG2025
Targeted Adversarial Denoising Autoencoders (TADA) for Neural Time Series Filtration
Benjamin J. Choi, Griffin Milsap, Clara A. Scholl +2
Current machine learning (ML)-based algorithms for filtering electroencephalography (EEG) time series data face challenges related to cumbersome training times, regularization, and…