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A new algorithm for blink correction adaptive to inter- and intra-subject variability.

E Guttmann-Flury¹, X Sheng¹, D Zhang¹

¹State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai, 200240, PR China.

Computers in Biology and Medicine

|September 25, 2019

Summary

This summary is machine-generated.

A novel algorithm for blink correction (ABC) in electroencephalographic (EEG) signals significantly improves brain-computer interface (BCI) classification accuracy compared to Independent Component Analysis (ICA). ABC offers superior data reconstruction and real-time implementation advantages.

Failed At:

2026-06-19T13:38:23.135634+00:00

Keywords:

Artifact removal BCI Brain computer interface EEG Electroencephalography ICA Independent component analysis Riemannian geometry Sample size calculation Spontaneous blinking Standardized low-resolution electromagnetic tomography sLORETA

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