TimeFrequency Analysis of the Auditory Brainstem Response
(2013) FMS820 20132Mathematical Statistics
 Abstract (Swedish)
 This thesis is about timefrequency analysis of the brainstem auditory evoked
potential (BAEP). The work can be divided into two parts. One part where
a model is built up from a very simple example to a more complex model
resulting in a model consisting of a sum of sinusoids with stochastic starting
points and amplitudes. Dierent timefrequency methods have been evaluated
for these models and the multi window spectrogram with Hermitian
base functions performs the best in a real life situation with more than one
component and a high level of noise.
The second part consists of investigating real BAEP data. BAEP data from
ve patients were available. Each patient has two data sets which have
been studied. One while the patient is... (More)  This thesis is about timefrequency analysis of the brainstem auditory evoked
potential (BAEP). The work can be divided into two parts. One part where
a model is built up from a very simple example to a more complex model
resulting in a model consisting of a sum of sinusoids with stochastic starting
points and amplitudes. Dierent timefrequency methods have been evaluated
for these models and the multi window spectrogram with Hermitian
base functions performs the best in a real life situation with more than one
component and a high level of noise.
The second part consists of investigating real BAEP data. BAEP data from
ve patients were available. Each patient has two data sets which have
been studied. One while the patient is awake and one while it is asleep.
A hypothesis is that there exists some sort of dierence between these two
datasets. It turns out that it does. The earlier peaks dier slightly in latency
and the later peaks for the sleeping data seem to disappear. This result is
concluded from dierent time frequency methods, where the spectrogram and
the multiwindow spectrogram are the most successful methods. An attempt
to make a bootstrap simulation in order to estimate the mean and condence
bounds of each peak is also made for one dataset. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/4113810
 author
 Johansson, Henrik
 supervisor

 Maria Sandsten ^{LU}
 organization
 course
 FMS820 20132
 year
 2013
 type
 H2  Master's Degree (Two Years)
 subject
 language
 English
 id
 4113810
 date added to LUP
 20131021 14:53:46
 date last changed
 20131021 14:53:46
@misc{4113810, abstract = {This thesis is about timefrequency analysis of the brainstem auditory evoked potential (BAEP). The work can be divided into two parts. One part where a model is built up from a very simple example to a more complex model resulting in a model consisting of a sum of sinusoids with stochastic starting points and amplitudes. Dierent timefrequency methods have been evaluated for these models and the multi window spectrogram with Hermitian base functions performs the best in a real life situation with more than one component and a high level of noise. The second part consists of investigating real BAEP data. BAEP data from ve patients were available. Each patient has two data sets which have been studied. One while the patient is awake and one while it is asleep. A hypothesis is that there exists some sort of dierence between these two datasets. It turns out that it does. The earlier peaks dier slightly in latency and the later peaks for the sleeping data seem to disappear. This result is concluded from dierent time frequency methods, where the spectrogram and the multiwindow spectrogram are the most successful methods. An attempt to make a bootstrap simulation in order to estimate the mean and condence bounds of each peak is also made for one dataset.}, author = {Johansson, Henrik}, language = {eng}, note = {Student Paper}, title = {TimeFrequency Analysis of the Auditory Brainstem Response}, year = {2013}, }