Analysis and Evaluation of the Audiological Test Process from EEG signals Using Wavelet Entropy Approaches

Özdinç Polat L. N., Özen Ş.

NEUROREHABILITATION AND NEURAL REPAIR, vol.37, no.5, pp.167-168, 2023 (SCI-Expanded)

  • Publication Type: Article / Abstract
  • Volume: 37 Issue: 5
  • Publication Date: 2023
  • Doi Number: 10.1177/15459683231159499
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, EMBASE, MEDLINE
  • Page Numbers: pp.167-168
  • Akdeniz University Affiliated: Yes


In this study, it is aimed to determine the effects of the audiological test process from EEG(Electroencephalogram) signals on individuals by using wavelet entropy. In this context, the effects of different wavelet entropy types were examined and which channel was more effective. Wavelet entropy is a method capable of analyzing the temporal properties of nonstationary signals and combines wavelet decomposition and entropy to estimate the order/ disorder degree of a signal with high time-frequency resolution. In the study, recordings were taken from 39 healthy volunteers with a 4-channel (from channels AF7, AF8, TP9, TP10) mobile EEG headband for approximately one minute of rest before and during the audiological test phase. The effects of 'Shannon', 'log energy' and 'norm' entropy types were investigated, and the entropy values of 'Shannon' and 'log energy' in the audiological test phase were found to be higher for all channels in absolute terms. As the power level increased for the 'norm' entropy type, differences began to occur between channels, and a significant difference emerged in AF8 entropy values for both the audiological test and resting state for the tenth power compared to other channels. The results obtained show that the wavelet entropy approach can determine in which region of the brain the activity of the audiological test is higher in individuals, and also in which region the audiological test process shows higher differences compared to the resting state.