The influence of acoustic and biological noise on signal quality measurements of otoacoustic emissions

Biological basis of the otoacoustic emission signal (OAE), acoustic nature of its generation and exceptional masking with various forms of interference are the starting point for the development of various methods of detection, signal processing and interpretation of OAE signal, or the effect of otoacoustic emission in light of the characterization of the cochlea functioning. OAE measurement methods differ in the way of stimulus generation, response generation mechanisms and the methods of signal processing and statistical interpretation of results. Existing methods of measurement and OAE signal processing are the basis of modern systems for OAE measurement, which have found wide application in clinical practice. However, all possibilities are not exhausted, especially the theoretical and methodological nature approaches, primarily in the field of OAE signal extraction from the noise. Improvement of the measuring conditions reduces the influence of external noise on the possibility of extraction of otoacoustic emissions, and biological noise becomes the dominant source of interference. The study of characteristics of biological noise is one of the prerequisites for successful troubleshooting OAE detection in the presence of biological noise. In carefully selected sample, in accordance with the needs of research, we analyzed the biological noise recorded in the ear canal. It turned out that there was a significant correlation of biological noise in the left and right ear and the correlation coefficient increases with the intensity of biological noise. This behavior of biological noise is a favorable circumstance from the point of application of adaptive filtering methods and adaptive noise suppression method. The dissertation analyzes the characteristics of the most important form of biological interference that are present during OAE measurement. These findings have enabled the selection of optimal adaptive methods for the detection of TEOAE in the presence of biological noise. The basic idea of suppressing biological noise consisted in e the use of biological noise from the other ear canal for adaptive suppression of biological noise in the ear canal in which OAE signal is measured. Since the OAE signal is deeply immersed in the noise it was necessary to combine several steps during preprocessing the signal to achieve good noise suppression. The applied methods are adaptive filtering, weighted averaging and estimated value of OAE signal subtraction from t