February 2022
Intermediate to advanced
392 pages
13h 2m
English
Content preview from Artificial Intelligence-Based Brain-Computer Interface
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12: Variational mode decomposition-based finger flexion detection using ECoG signals
Shivam Sharma; Rishi Raj Sharma Department of Electronics Engineering, Defence Institute of Advanced Technology, Pune, Maharashtra, India
Abstract
The finger flexion movement prediction is a challenging problem of the brain-computer interface. This chapter focuses on decoding the finger flexion movement using electrocorticogram (ECoG) signals. The variational mode decomposition (VMD) is applied to obtain the subcomponents of each channel ECoG recording. Various correlation-based and other parameters such as correntropy, cross-information potential, and entropy estimation by Kozachenko-Leonenko are evaluated to categorize the flexion movement. The ...
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