Document Type
Thesis
Date of Award
9-30-1988
Degree Name
Master of Science in Electrical Engineering - (M.S.)
Department
Electrical Engineering
First Advisor
Stanley S. Reisman
Second Advisor
Burhan Tarik Oranc
Abstract
The objective of this thesis is to detect the Brainstem Auditory Evoked Response (BAER) using lower numbers of averages than at present, by using an optimal smoothing method which is based on the Kalman Filter.
By using this method, the wave V latency of the BAER which is useful in testing for hearing loss can be detected with as low as 500 averages, while the traditional signal averaging method requires at least 2000 averages. Thus the time required for a hearing loss test can be reduced from one hour to approximately 20 minutes.
Also several other methods for detecting BAER are discussed in this thesis. They are: Signal Averaging, a posteriori "Wiener" Filtering and Time-Varyzng Filtering. Compared to these methods, the Optimal Smoothing method is simple and effective. The results show that the Optimal Smoothing method can detect the peak position shift using a signal model. For the low noise case (SNR > 1: 2), it can detect the peak position even without a signal model. The results also show that the amplitude of the peak and the shape of the waveform after processing are not matched with the input signal in the large noise case. Therefore this method can only be used as a latency detector.
Recommended Citation
Qian, Chong An, "Kalman filtering applied to the analysis of brainstem auditory evoked potentials" (1988). Theses. 3177.
https://digitalcommons.njit.edu/theses/3177
