Machine-based classification of ADHD and nonADHD participants using time/frequency features of event-related neuroelectric activity

Author:

Öztoprak Hüseyin,Toycan Mehmet,Alp Yaşar Kemal,Arıkan Orhan,Doğutepe Elvin,Karakaş Sirel

Funder

Scientific Research Unit of Hacettepe University

Publisher

Elsevier BV

Subject

Physiology (medical),Clinical Neurology,Neurology,Sensory Systems

Reference62 articles.

1. Wavelet-synchronization methodology: a new approach for EEG-based diagnosis of ADHD;Ahmadlou;Clin EEG Neurosci,2010

2. Time–frequency analysis of signals using support adaptive Hermite-Gaussian expansions;Alp;Digit Signal Process,2012

3. Improving accuracy of source localization by a new time-frequency preprocessing technique. 14th World congress of psychophysiology. The Olympics of the brain;Alp;Int J Psychophysiol,2008

4. American Psychiatric Association. Attention deficit and disruptive behavior disorder. In: Attention-deficit/hyperactivity disorder. Diagnostic and statistical manual of mental disorders. 4th ed. Washington DC: American Psychiatric Association; 2000. p. 134–35.

5. Anuradha J, Ramachandran V, Arulalan KV, Tripathy BK. Diagnosis of ADHD using SVM algorithm. In: Proceedings of the third annual ACM Bangalore conference. ACM; 2010.

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