• DocumentCode
    599267
  • Title

    EEG based hearing perception level estimation for normal hearing persons

  • Author

    Paulraj, M.P. ; Bin Yaccob, Sazali ; Bin Adom, Abdul Hamid ; Hema, C.R. ; Subramaniam, Kamalraj

  • Author_Institution
    Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Arau, Malaysia
  • fYear
    2012
  • fDate
    23-26 Sept. 2012
  • Firstpage
    160
  • Lastpage
    162
  • Abstract
    Auditory evoked potential (AEP) is a type of EEG signal emanated from the scalp of the brain by an acoustical stimulus. AEP response reflects the auditory ability level of an individual. In this paper, AEP signals were recorded by stimulating repetive click-sound of 1000 Hz at different stimulus intensity levels of 25 dB, 40 dB, 50 dB and 70 dB. Spectral entropy features of four distinct bands were extracted from the recorded AEP signal. The extracted features were associated to the hearing perception level of an individual and a neural network models was developed. The maximum classification accuracy of the developed neural network model was observed as 91.4 per cent in discriminating the specified stimulus intensity levels. From the result, it is clear that a different auditory stimuli level reflects corresponding hearing perception level of a person. This study might lead to a real-time practical system for non-invasively estimating the hearing perceptional level of a person.
  • Keywords
    acoustic signal processing; auditory evoked potentials; electroencephalography; feature extraction; medical signal processing; neural nets; signal classification; AEP response; AEP signal; EEG based hearing perception level estimation; EEG signal; acoustical stimulus; auditory ability level; auditory evoked potential; auditory stimuli level; brain scalp; feature exraction; frequency 1000 Hz; maximum classification accuracy; neural network model; normal hearing person; repetive click-sound stimulation; spectral entropy feature; stimulus intensity level; Electroencephalography; Feature extraction; Manuals; Neural networks; Neurons; Standards; Time frequency analysis; EEG; auditory evoked potential; auditory stimuli level; hearing perception; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Systems & Industrial Informatics (ICCSII), 2012 IEEE Conference on
  • Conference_Location
    Bandung
  • Print_ISBN
    978-1-4673-1022-2
  • Type

    conf

  • DOI
    10.1109/CCSII.2012.6470493
  • Filename
    6470493