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The 2010 International Joint Conference on Neural Networks (IJCNN)

DOI: 10.1109/ijcnn.2010.5596933

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Concatenated trial based Hilbert-Huang transformation on event-related potentials

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Time-frequency analysis is critical to study event-related potentials (ERPs) now. ERPs are usually generated through averaging over a number of trials, and such averaging limits the application of a nonlinear time-frequency analysis method-Hilbert-Huang transformation (HHT). This is because HHT usually requires very long recordings to sufficiently decompose the complicated signal into oscillations and the averaged ERP trace tends to possess only hundreds of samples. Thus, this study designs the concatenated trial based HHT to release the limitation on the decomposition. Such a paradigm may reveal better temporal and spectral properties of an ERP than the conventional wavelet transformation does. Moreover, under the proposed method, it is found that the children with attention deficit hyperactivity disorders may have more temporally, spectrally and spatially distributed brain activities than the control children do.