Enhanced signal processing using modified cyclic shift tree denoising

Hadri Hussain, W. S.N.A. Wan Abd Aziz, Ting Chee-Ming, Fuad M. Noman, A. L. Ahmad Zubaidi, S. B. Samdin, Hadrina Sh, M. A. Jalil, Yusmeera Yusoff, Kavikumar Jacob, Kanad Ray, M. Shamim Kaiser, Sheikh Hussain Shaikh Salleh, Jalil Ali

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch


The cortical pyramidal neurons in the cerebral cortex, which are positioned perpendicularly to the brain’s surface, are assumed to be the primary source of the electroencephalogram (EEG) reading. The EEG reading generated by the brainstem in response to auditory impulses is known as the Auditory Brainstem Response (ABR). The identification of wave V in ABR is now regarded as the most efficient method for audiology testing. The ABR signal is modest in amplitude and is lost in the background noise. The traditional approach of retrieving the underlying wave V, which employs an averaging methodology, necessitates more attempts. This results in a protracted length of screening time, which causes the subject discomfort. For the detection of wave V, this paper uses Kalman filtering and Cyclic Shift Tree Denoising (CSTD). In state space form, we applied Markov process modeling of ABR dynamics. The Kalman filter, which is optimum in the mean-square sense, is used to estimate the clean ABRs. To save time and effort, discrete wavelet transform (DWT) coefficients are employed as features instead of filtering the raw ABR signal. The results show that even with a smaller number of epochs, the wave is still visible and the morphology of the ABR signal is preserved.

Original languageEnglish
Title of host publicationApplied Intelligence and Informatics - First International Conference, AII 2021 Nottingham, UK, July 30–31, 2021 Proceedings
EditorsMufti Mahmud, M. Shamim Kaiser, Nikola Kasabov, Khan Iftekharuddin, Ning Zhong
Place of PublicationCham Switzerland
Number of pages11
ISBN (Electronic)9783030822699
ISBN (Print)9783030822682
Publication statusPublished - 2021
EventInternational Conference on Applied Intelligence and Informatics 2021 - Online, Nottingham, United Kingdom
Duration: 30 Jul 202131 Jul 2021
Conference number: 1st
https://link.springer.com/book/10.1007/978-3-030-82269-9 (Proceedings)
https://www.proconf.org/conferences/details.php?conference_name=International-Conference-on-Applied%20Intelligence-and-Informatics-2021 (Website)

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


ConferenceInternational Conference on Applied Intelligence and Informatics 2021
Abbreviated titleAII 2021
Country/TerritoryUnited Kingdom
Internet address


  • Auditory Brainstem Response
  • Cyclic Shift Tree
  • EEG
  • Inter-wave intervals
  • Wave V
  • Wavelet Kalman Filter

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