Neuro-fuzzy Classification of Transcranial Doppler Signals with Chaotic Meaures and Spectral Parameters
Ozturk, Ali and Arslan, Ahmet
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Abstract
Transcranial Doppler (TCD) is a non-invasive diagnosis method which is
used in diagnosis of various brain diseases by measuring the blood flow
velocities in brain arteries. In this study, chaos analysis of the TCD
signals recorded from the middle arteries of the temporal region of
brain of the 82 patients and 23 healthy people was investigated. Among
82 patients, 20 of them had cerebral aneurism, 10 had brain hemorrhage,
22 had cerebral oedema and the remaining 30 had brain tumor. Maximum
Lyapunnov exponent which is the strongest quantitative indicator of chaos
was found to be positive for all TCD signals. The correlation dimension
was found as greater than 2 and as fractional value for all TCD signals.
These two features were used for training a NEFCLASS model. The NEFCLASS
model had two input nodes for D2 and maximum Lyapunov exponent values
and five output nodes representing the subject group to which the inputs
belonged. In order to make k-fold cross-validation, the data set was
randomly divided into 5 subsets of equal size. In an iterated manner, 4
of these subsets were used for training and the remaining 1 subset was
used for testing. This operation was repeated for 3 times. The average
accuracy for train and test set was found as \%81 and \%79,
respectively. The performance of the NEFCLASS model was also assessed in
the same manner with spectral parameters (i.e. resistivity index and
pulsatility index) which were obtained from Doppler sonograms. The
average accuracy was found as \%67 and \%63 for train and test set,
respectively.... Show more Show less