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A supervised machine-learning method for detecting steady-state visually evoked potentials for use in brain computer interfaces: A comparative assessment
It is hypothesised that supervised machine learning on the estimated parameters output by a model for visually evoked potentials (VEPs), created by Kremlácek et al. (2002), could be used to classify steady-state visually evoked potentials (SSVEP) by frequency of stimulation. Classification of SSVEPs...
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| Format: | Thesis |
| Language: | English |
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Division of Biomedical Engineering
2018
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