79
Chapter 6
Detection of Epileptic Seizure
Using STFT and Statistical
Analysis
Furkan Kalin, T. Cetin Akinci, Deniz Türkpence,
Serhat Seker and Ufuk Korkmaz
Abstract
In this study, EEG data from two volunteer individuals, a healthy individual and
a patient with epilepsy, were investigated with two different methods in order to
distinguish healthy and patient individuals from each other. The data were obtained
from a healthy individual and from a patient with epilepsy at the time of epileptic
seizure and of seizure-free interval. The data are those of which validity and
reliability were proven and were supplied from the data bank records of University
Hospital of Bonn in Germany. In the study, the statistical parameters of the collected data were calculated, then the same data were analysed using short-time
Fourier transform (STFT) method, and then they were compared. Both statistical
parameter results and spectrum analysis results are compatible with each other, and
they can successfully detect healthy individuals and epileptic patients at the time
of epileptic seizure and seizure-free interval. In this sense, the results were mathematically highly compatible, which offers significant information for the diagnosis
of the disease. In the analysis, the variance values were determined as 253.203 for
the healthy individual, 806.939 for the patient at seizure-free interval and 6985.755
for that patient at the time of seizure. Accordingly, standard deviation can be said
to be quite distinctive in the designation of values. The frequencies of all three cases
resulted in 0, 0–5 and 0–20 Hz, respectively, as a result of conducted STFT analysis,
which is quite consistent with the results of the statistical analysis parameters.
Keywords: electroencephalogram, statistical analysis, epilepsy, STFT, seizure
1. Introduction
Temporary clinical conditions, including loss of consciousness, sensory, autonomic and mental disorders, arising from excessive electrical discharges in the nerve
cells in the brain, with certain intervals are called as seizure. The condition which
becomes chronic with the repetition of these seizures is called as epilepsy. Epilepsy
is a chronic disorder that affects the brain and that can be encountered in people of
all age groups. It is a neurological disease, most commonly seen in childhood and
adolescence periods, and is the second most common disease in adults, followed by
brain vessel diseases [1–3]. According to the World Health Organization data, 50
million people around the world are patients with epilepsy [4, 5]. EEG is also used
as an auxiliary diagnostic method in the diagnosis of epilepsy, in addition to clinical
Chapter 6
Detection of Epileptic Seizure
Using STFT and Statistical
Analysis
Furkan Kalin, T. Cetin Akinci, Deniz Türkpence,
Serhat Seker and Ufuk Korkmaz
Abstract
In this study, EEG data from two volunteer individuals, a healthy individual and
a patient with epilepsy, were investigated with two different methods in order to
distinguish healthy and patient individuals from each other. The data were obtained
from a healthy individual and from a patient with epilepsy at the time of epileptic
seizure and of seizure-free interval. The data are those of which validity and
reliability were proven and were supplied from the data bank records of University
Hospital of Bonn in Germany. In the study, the statistical parameters of the collected data were calculated, then the same data were analysed using short-time
Fourier transform (STFT) method, and then they were compared. Both statistical
parameter results and spectrum analysis results are compatible with each other, and
they can successfully detect healthy individuals and epileptic patients at the time
of epileptic seizure and seizure-free interval. In this sense, the results were mathematically highly compatible, which offers significant information for the diagnosis
of the disease. In the analysis, the variance values were determined as 253.203 for
the healthy individual, 806.939 for the patient at seizure-free interval and 6985.755
for that patient at the time of seizure. Accordingly, standard deviation can be said
to be quite distinctive in the designation of values. The frequencies of all three cases
resulted in 0, 0–5 and 0–20 Hz, respectively, as a result of conducted STFT analysis,
which is quite consistent with the results of the statistical analysis parameters.
Keywords: electroencephalogram, statistical analysis, epilepsy, STFT, seizure
1. Introduction
Temporary clinical conditions, including loss of consciousness, sensory, autonomic and mental disorders, arising from excessive electrical discharges in the nerve
cells in the brain, with certain intervals are called as seizure. The condition which
becomes chronic with the repetition of these seizures is called as epilepsy. Epilepsy
is a chronic disorder that affects the brain and that can be encountered in people of
all age groups. It is a neurological disease, most commonly seen in childhood and
adolescence periods, and is the second most common disease in adults, followed by
brain vessel diseases [1–3]. According to the World Health Organization data, 50
million people around the world are patients with epilepsy [4, 5]. EEG is also used
as an auxiliary diagnostic method in the diagnosis of epilepsy, in addition to clinical