An efficient P300 detection algorithm based on Kernel Principal Component Analysis-Support Vector Machine

• Published in: Computers & electrical engineering Vol. 97; p. 107608
• Main Authors: Hashmi, Mohammad Farukh, Kene, Jagdish D., Kotambkar, Deepali M., Matte, Praveen, Keskar, Avinash G.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.01.2022; Elsevier BV
• Subjects: Accuracy; Algorithms; Brain-Computer Interface Technology (BCI); Discrete Wavelet Transform (DWT); Human-computer interface; Kernel Principal Component Analysis (KPCA); Principal components analysis; Signal classification; Signal detection; Single-trial P300 detection; Support Vector Machine (SVM); Support vector machines; Brain-Computer Interface Technology (BCI); Kernel Principal Component Analysis (KPCA); Discrete Wavelet Transform (DWT); Single-trial P300 detection; Support Vector Machine (SVM)

Human-machine interaction using brain signals has been made possible by the advent of a technology popularly known as a brain-computer interface (BCI). P300 is the most studied event related potentials (ERP) and is used in many BCI systems. The existing multi-trial P300 detection methods suffer draw...