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Figure 2. Signal processing
Term Fourier Transform of signal x(t) is defined
by as in (Nijsen, 2006):
where h(t) is wavelet base, * is the complex con-
jugation and the factor 1/√a is used for energy
normalization. Wavelet transform has been used
by various studies for detecting seizures. Abibul-
laev et al. (2010) propose a method for automatic
detection of epileptic seizures in EEGs by using
basis wavelet functions and by doubling the
threshold. Hence, this is well suited for localiza-
tion and detecting of significant epileptic events
from noisy recorded EEG signals from seizures.
Signal in different threshold is given in Figure 3.
Another innovative wavelet-based method has
been proposed (Zandi, 2010) for real-time epi-
leptic seizure detection by using moving window
analysis.
∫
j
ωτ
SFTF x t w
[
]( ,
)
=
x
( ) * (
τ
h
t
−
τ
)
e
d
τ
,
h
where h(t) is a window function, * is the com-
plex conjugation and ω is continuous frequency
(rad/s) and
t
is I time (s). The sample frequency
of accelerometer signal can be used as 100 Hz.
Continuous Wavelet Transform (CWT)
Wavelet Transform is a newly developed math-
ematical tool for numerous problems. CWT is
used little waves that start and stop instead of
long cosine waves. In CWT signal is same but in
half time and double the frequency, hence, is very
fast (Strang, 1994). This method is also useful to
improve signal compression and noise reduction.
This is time frequency version of the signal and
it has two core advantages; (i) it removes the
condition of the stationary signal (ii) it presents
an optimal resolution in time and frequency do-
mains (Wavelet, 1999). The Continuous Wavelet
Transform of a signal x(t) with scale a and position
t is defined as in (Nijsen, 2006):
The Requirements of a CRESH for
Remote Detection and Prediction of
Epileptic Seizures
Technical Requirements
In the same way as any healthcare system, there are
several key technical requirements for a CREHS
for remote detection and prediction of epileptic
seizures. These requirements involve good detec-
tion which means precise and real-time (or nearly
real-time) detection, reliability, and usability. As
a CREHS stores, processes, and retrieves a large
volume of health data records, it is important
that health data security is ensured in processing,
1
( ) *
(
t
−
τ
)
∫
CWT x t a
h
[
]( , )
=
x
τ
h
d
τ
,
a
a
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