Mathematical Sciences

Lund University

Title Time Frequency Spectral Representation of Auditory Brainstem Response (ABR) Data
Authors Amare Terefe Gashaye
Full-text Available as PDF
Year 2012
Document type StudentPublicationsH2
Language eng
Abstract Swedish The time-frequency (TF) spectral representation of Auditory Brainstem Response (ABR) signal data<br> provides information about their spectral contents. We apply the Spectrogram, Thomson Multitaper and<br> Peak Matched Multiple Window (PM MW) spectral estimation methods to four different number of clicks<br> per average (i.e., 1313, 300, 100 and 50 number of clicks per average) of a simulated signal data. For the<br> purpose of model selection we simulate sinusoidal signal data which have the same trend as the empirical<br> ABR signal data, and then apply the selected model to ABR data from 17 healthy, normal hearing individual<br> ears as recorded using SD-BERA, SensoDetect-Brainstem Evoked Response Audiometry. The root mean<br> square error (RMSE) is the main tool used to compare the proposed spectral estimation methods. The<br> Spectrogram is found to be an appropriate method of spectral estimation for signals with relatively low<br> disturbance. In particular, for signals with a white disturbance with standard deviation, , value in the<br> interval 0,15.0, it is found to be best of the three methods. For 15.0 ≤ ≤ 30.0, the PM MW method<br> performs as good as the spectrogram, if not better. Finally, for ≥ 30.0 the PM MW continues to be the<br> best of the three methods where as the Spectrogram turns out to be worst of them.