ECG signal:
ECG signal, also known as EKG
signal, is a diagnostic tool which makes the electrical and muscular function
of the heart accessible for analysis. The continuous pumping of blood by heart
from lungs to various parts of body is responsible for generation of ECG
signal. The heart is a two stage electrical pump
and its electrical activity can be measured by placing the electrodes on the
chest or by using some special bands. The
electrocardiogram is used to measure the rate and rhythm of the heartbeat, as
well as it provides an evidence of blood flow to the heart muscles.
Fig1 ECG signal
Introduction:
For ECG signal analysis we perform
Signal Processing on it. With the help of the signal processing we can extract
that information from the ECG signal that we cannot extract by simply
visualizing it. Many noises may add into our ECG signal and elimination of
these noises is also the important objective of the Signal processing. And
another main objective of the signal processing is to do the compression of the
data. The following diagram shows the algorithm for basic ECG signal processing:
Fig2 Algorithm for basic ECG signal processing
After getting the information by the
signal processing, we can use this information in many applications.
ECG Pre-Processing:
Filtering is done in Pre-Processing
part of the ECG signal and after filtering, various analyses are performed on
the ECG signal. Filters are mainly designed for the removal of the following:
- 1 Baseline wander
- 2 Power line interference
Baseline wander:
The main factor require for designing
the linear, time-invariant, high pass filters for removal of baseline wander is
cutoff frequency and phase response characteristics In definite situations,
baseline wander becomes commonly well-defined at higher heart rates such as
during the final stages of a stress test when the workload increases. Then, it
may be advantageous to couple the cut-off frequency to the general heart rate,
rather than to the lowest possible heart rate, to further improve baseline
removal.
Figure 3(a) shows Electrocardiographic baseline wander because
of sudden body movements. The amplitude of the baseline wander is considerably
larger than that of the QRS complexes .Figure3(b) a close-up in time (10 x) of the ECG signal
framed in (a)
Power line Interference:
Electromagnetic fields generated by a power line signify a common
noise source in the ECG that is characterize by 50 or 60 Hz sinusoidal
interference, probably accompany by a number of harmonics. Such narrow band
noise makes the analysis and interpretation of the ECG more difficult, as the
description of low-amplitude waveforms becomes unpredictable and fake waveforms
may be introduced.
4 QRS Detection:
The information content present in any ECG signal is its
existence and its time of occurrence. The QRS complex present in ECG signal
indicates the existence of beat in the signal. Also many other analyses of
human body like pulse rate, blood pressure measurement, physical and mental
status etc can be performed after detection of QRS peak. Thus, proper detection
is of utmost requirement which ensures that refined and distortion less signal will
be further used by system for human body analysis. The poor detection can lead
to limitation in performance of whole system.
The two problems frequently faced in QRS detection are that the
signal either remains undetected or signal is detected falsely. The problem of
more concern is no detection, because the information content from that part is
lost and cannot be recovered in later stages of the system. For false detection
of signal, there are various methods to resolve it like performing classification
of QRS morphologies. The detector must be capable of detecting different
morphologies to allow sudden changes in the output i.e. it should not lock onto
certain types of rhythm, but treat each event as if it could occur at almost
any time. The noises also accompany the detected signal. These noises may be transient
in behavior or persistent.
Fig Block diagram of QRS Detector
The above figure shows the block diagram of a commonly used QRS
detector. The input to system is the ECG signal, and the output is a series of
occurrence times of the QRS complex signal. It is a must requirement to improve
the resolution using an algorithm which is responsible for time alignment of
the detected signal. Time alignment helps in elimination of smearing which
occurs during computation of the ensemble average of several detected beats.
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