STUDY OF EEG SIGNALS USING THE WAVELET TRANSFORM TO IDENTIFY ADHD IN SCHOOL-AGE CHILDREN

• DOI: https://doi.org/10.22533/at.ed.3174272407111

• Palavras-chave: Electroencephalography. Wavelet transform. ADHD.

• Keywords: Electroencephalography. Wavelet transform. ADHD.

• Abstract:

  Attention Deficit/Hyperactivity Disorder (ADHD) is a neurobiological disorder characterized by a persistent pattern of inattention/hyperactivity-impulsivity. In school-age children, the influence of this disorder can lead to low academic performance, but the main factor is the interference in the individual's social, academic and professional life. Therefore, this study aims to develop an analysis system based on the Electroencephalogram (EEG) signal to encourage the development of tools to identify signs suggestive of ADHD in school children. To this end, the classifier is based on the Threshold technique using the Redundant Discrete Wavelet Transform to extract signal characteristics. The simulation environment used was MATLAB (2015a). The data set analyzed was from the IEEE Dataport database. To achieve the objective of the work, the delta and theta frequency ranges of the wavelet coefficients were used as parameters for the threshold method, and the electrodes analyzed were from the frontal region of the brain. The proposed model performed with a sensitivity of 88.58 % and positive predictivity of 73.26 % for a set of 40 analyzed data. Among the aspects identified, it can be seen that the algorithm's performance was satisfactory, however, for a small volume of data.