Title |
Application of the Stockwell Transform to Electroencephalographic Signal Analysis during Gait Cycle
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Published in |
Frontiers in Neuroscience, November 2017
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DOI | 10.3389/fnins.2017.00660 |
Pubmed ID | |
Authors |
Mario Ortiz, Marisol Rodríguez-Ugarte, Eduardo Iáñez, José M. Azorín |
Abstract |
The analysis of electroencephalographic signals in frequency is usually not performed by transforms that can extract the instantaneous characteristics of the signal. However, the non-steady state nature of these low voltage electrical signals makes them suitable for this kind of analysis. In this paper a novel tool based on Stockwell transform is tested, and compared with techniques such as Hilbert-Huang transform and Fast Fourier Transform, for several healthy individuals and patients that suffer from lower limb disability. Methods are compared with the Weighted Discriminator, a recently developed comparison index. The tool developed can improve the rehabilitation process associated with lower limb exoskeletons with the help of a Brain-Machine Interface. |
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