Sliding HDCA: Single-Trial EEG Classification to Overcome and Quantify Temporal Variability

Abstract

Patterns of neural data obtained from electroencephalography (EEG) can be classified by machine learning techniques to increase human-system performance. In controlled laboratory settings this classification approach works well; however, transitioning these approaches into more dynamic, unconstrained environments will present several significant challenges… (More)
DOI: 10.1109/TNSRE.2014.2304884

Topics

9 Figures and Tables

Statistics

02040201520162017
Citations per Year

Citation Velocity: 10

Averaging 10 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.

Slides referencing similar topics