Abstract:
Objectives: The result of auditory brainstem response is used worldwide for detecting hearing
impairments or hearing aids. This study aimed to introduce the superiority of mathematical
innovation algorithm toward subjective evaluation by an audiologist. The automatic algorithm
method is encouraged for detecting the waves of Auditory Brainstem Response (ABR), because
it can reduce subjective evaluation biases and visual analysis errors. This article portrays another
technique for automatic detection of the peaks. Finally, by obtaining the standard pattern with this
automatic algorithm for Persian speakers, we will compare it with the English speakers whose
information was obtained by subjective method in Northwestern University. This article describes
the effect of different factors on brainstem responses by performing a new automatic method.
Methods: Auditory evoked potentials of brainstem activity were recorded by Electro
encephalogram (EEG) of 27 Persian speaker adults with normal hearing. Three stimulus /ga/, /
da/, and /ba/ were presented. This strategy depends on the utilization of reference wave forms,
time latencies, and peaks adjusted and comparison with the ABR. Brainstem response latencies
of brainstem peaks were extracted by the automatic method in temporal and spectral domains.
This step provides language patterns for Persian speakers. Finally, the results of Persian speakers
were compared with the results of a previous study done in Northwestern University by the
same recording protocol as our own study on 22 English speaker children. Intraclass correlation
coefficients and paired t test were used for evaluating and comparing the results.
Results: According to the results, the performance of automatic method is high and reliable.
Automatic and visual analysis methods had significant interaction. Latency of auditory
brainstem response to the same stimulus in the two study groups was different and had a
significant latency. The significance of these discoveries and clinical outcomes of this target
strategy are featured in this paper.
Discussion: This simple innovative algorithm could find the correct location of ABR peaks.
Because of different acoustic signs and symptoms in the brainstem, the time latencies for all three
stimulus used in this study are completely different
Machine summary:
Research Paper: Objective Peak-Detection in Complex Auditory Brainstem Response to /ba/, /da/, /ga/: A Novel Technique Negar Amirian1 , Farhad Tabatabai Ghomsheh2 , Mohsen Vahedi3 , Nematollah Rouhbakhsh4 , Amir Salar Jafarpisheh5* 1.
3. 219 Funding: See Page 230 Copyright: The Author(s) A B S T R A C T Article info: Received: 10 Jan 2018 Accepted: 25 May 2018 Available Online: 01 Sep 2018 Keywords: Auditory evoked potentials, Stimulus-specific adaptation, Linguistic effect, Speech perception, Hearing loss, Auto peak detection Objectives: The result of auditory brainstem response is used worldwide for detecting hearing impairments or hearing aids.
The automatic algorithm method is encouraged for detecting the waves of Auditory Brainstem Response (ABR), because it can reduce subjective evaluation biases and visual analysis errors.
Methods: Auditory evoked potentials of brainstem activity were recorded by Electro encephalogram (EEG) of 27 Persian speaker adults with normal hearing.
Latency of auditory brainstem response to the same stimulus in the two study groups was different and had a significant latency.
ir 219 September 2018, Volume 16, Number 3 Highlights I ranian Rehabilitation Journal ● Automatic central auditory brainstem response (cABR) peak detection is possible.
The range of 400-720 Hz referring to F0 frequency was chosen, then all 10 harmonic peaks marked for each stimulus by MATLAB software via Intraclass Correla- tion Coefficients (ICC), and Paired t test for evaluating frequency bin difference were performed in each stimu- lus.
5. Conclusion The automatic algorithm could detect all 16 peaks in brainstem response signals, and extract latency time with high accuracy.