Analysis of the variability of auditory brainstem response components through linear regression

Kheline F. P. Naves, Adriano A. Pereira, Slawomir J. Nasuto, Ieda P. C. Russo, Adriano O. Andrade

Catholic University of Sao Paulo, Sao Paulo, Brazil.
Cybernetic Intelligence Research Group, School of Systems Engineering, University of Reading, Reading, UK.
Laboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia, Brazil.

DOI: 10.4236/jbise.2012.59064                

Abstract

The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behavior, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analyzing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. In this context, the aim of this research is to compare ABR manual/visual analysis provided by different examiners. Methods: The ABR data were collected from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). A total of 160 data samples were analyzed and a pair- wise comparison between four distinct examiners was executed. We carried out a statistical study aiming to identify significant differences between assessments provided by the examiners. For this, we used Linear Regression in conjunction with Bootstrap, as a method for evaluating the relation between the responses given by the examiners. Results: The analysis suggests agreement among examiners however reveals differences between assessments of the variability of the waves. We quantified the magnitude of the obtained wave latency differences and 18% of the investigated waves presented substantial differences (large and moderate) and of these 3.79% were considered not acceptable for the clinical practice. Conclusions: Our results characterize the variability of the manual analysis of ABR data and the necessity of establishing unified standards and protocols for the analysis of these data. These results may also contribute to the validation and development of automatic systems that are employed in the early diagnosis of hearing loss.

Keywords

Auditory Brainstem Response; Hearing Loss; Linear Regression

Conflicts of Interest

The authors declare no conflicts of interest.

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