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Application of the Stockwell Transform to Electroencephalographic Signal Analysis during Gait Cycle
- Source :
- Frontiers in Neuroscience, Vol 11 (2017), Frontiers in Neuroscience
- Publication Year :
- 2017
- Publisher :
- Frontiers Media SA, 2017.
-
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.
- Subjects :
- Discriminator
Computer science
Speech recognition
Stockwell transform
Fast Fourier transform
fast fourier transform
EEG analysis
02 engineering and technology
Signal
Hilbert–Huang transform
lcsh:RC321-571
03 medical and health sciences
0302 clinical medicine
0202 electrical engineering, electronic engineering, information engineering
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Continuous wavelet transform
Constant Q transform
Original Research
Signal processing
Hilbert-Huang transform
business.industry
General Neuroscience
020206 networking & telecommunications
Pattern recognition
gait intention
Artificial intelligence
Harmonic wavelet transform
business
brain-machine interface
030217 neurology & neurosurgery
Neuroscience
Subjects
Details
- ISSN :
- 1662453X
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Frontiers in Neuroscience
- Accession number :
- edsair.doi.dedup.....41b945c72a921d827d64366e67718d4b