Transcript Multimédia és egészségügy

5th practice
Medical Informatics
Biomedical Signal Processing
TAMUS, Zoltán Ádám
[email protected]
 The
electrical manifestation of the
contractile activity of the heart
 The ECG can be easily recorded with
surface electrodes on the limbs or chest
(Einthoven’s triangle)
 The waveshape is altered by
cardiovascular diseases
 Einthoven’s
triangle
 The
ECG is an electrical signal (function of
time)
 The
SA node fires
 Slow-moving
depolarization
(contraction) of
the atria
 The P wave in
ECG
• 0.1-0.2 mV
• 60-80 ms
 Propagation
delay at atriovenricular (AV)
node
 Normally isoelectric segment
 PQ segment
• 60-80 ms
 His
bundle, the
bundle
branches, and
the Purkinje
system of
specialized
conduction
fibers
propagate the
stimulus to the
ventricles at
high rate
 The
wave of
stimulus spreads
rapidly from the
apex of the heart
upwards
 Rapid
depolarization
(contraction) of
ventricles
 QRS wave
• 1 mV
• 80 ms
 The
ventricular
muscle cells
possess a
relatively long
action potential
300-350 ms
 Result: isoelectric segment
 ST segment
• 100-120 ms
 Repolarization
(relaxation) of
ventricles causes
slow T wave
• 0.1-0.3 mV
• 120-160 ms
 Physiological
interference
• Respiration, squirms, coughs etc.
• Mother’s ECG appearing with the ECG of the
fetus
 Electromagnetic
interference
• TV and radiostations, CRTs, computers,
fluorescent lamps
 Result: noise
in the ECG signal
 Signal
• Deterministic signal:
 the value at a given instance of time may be computed
using a closed-form mathematical function of time or
 Predicted from a knowledge of a few past values of the
signal
• Nondeterministic signal (random signal):
 That does not meet the conditions of the deterministic
signal
 The noise may be random, structured
(deterministic) and physiological
 Random
noise
• ensemble average: 0
1 M
 x (t1 )  lim
xk (t1 )

M  M
k 1
 Reduction: Moving Average (MA) filter
• general form:
N
y ( n)   bk x (n  k )
k 0
• bk:filter coefficients
 Examples
of MA filters
• von Hann or Hanning filter:
1
y ( n)  x( n)  2 x( n  1)  x( n  2)
4
• 8-point average:
1 7
y ( n)   x ( n  k )
8 k 0
 Rangaraj
M. Rangayyan: Biomedical
Signal Analysis, IEEE Press/Wiley, New
York, NY, 2002.
 1. Observation
of noisy ECG signal
 2. Filtering the noisy ECG signal by MA
filter
• von Hann or Hanning filter
• 8-point MA filter
sample files: http://zoltanadam.fw.hu
software: MS Excel