Analysis of attention deficit hyperactivity disorder and control participants in EEG using ICA and PCA

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Abstract

This paper presents our preliminary EEG brain signals of children with attention deficit hyperactivity disorder (ADHD) in order to support a computer assisted diagnostic system. The EEG signals were recorded from 4 children including normal and children diagnosed with ADHD while performing Continuous Performance Test (CPT). Independent component analysis (ICA) was used as the preprocessing steps to remove artifacts associated with eye blinks, eye-movements and muscle noise. Then the Principal Component Analysis (PCA) was employed to select a subset of channels for EEG signals which are to preserve as much information present as compared to the full set of 128 channels as possible. The results would be used to classify ADHD study and lay the foundation of ADHD clinical diagnoses study. © 2012 Springer-Verlag.

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Zou, L., Pu, H., Sun, Q., & Su, W. (2012). Analysis of attention deficit hyperactivity disorder and control participants in EEG using ICA and PCA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7367 LNCS, pp. 403–410). https://doi.org/10.1007/978-3-642-31346-2_46

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