Application to biomedical signals - Practical Biomedical Signal Analysis Using MATLAB - page 176

ecgpuwave/ ) as a routine ecgpuwave .
A classification system for the electrocardiogram features called the Minnesota
Code [Pineas et al., 1982] utilizes a defined set of measurement rules to assign spe-
cific numerical codes describing ECG morphology. It provides the ranges of normal
values of ECG morphological features in the standard 12 leads. The system was
developed in the late 1950s in response to the need for reporting ECG findings in
uniform and objective terms and has been updated and improved since then. Min-
nesota Code incorporates ECG classification criteria that have been validated and
accepted by clinicians [Kors et al., 1996].
ECG ST segment analysis is of special interest for detection of ischemia, heart
rate changes, and other heart disturbances. The review of the ST segment analysis
approaches, comparison of performance of ST analyzers, and algorithm for detection
of transient ischemic heart rate related ST episodes may be found in [Jager, 2006].
Another feature of ECG important for clinical diagnosis is T-wave alternans
(TWA). T wave is connected with the processes of repolarization of the heart mus-
cle and its character changes from beat to beat and in particular its amplitude has
alternating higher and lower values in consecutive cycles. TWA is a valuable ECG
index that indicates increased susceptibility for ventricular arrhythmia and the risk
of cardiac arrest, one of the most frequent causes of sudden death. The parameter
commonly used in diagnostics is T wave amplitude, although its phase and shape are
also considered. To find subtle TWA fluctuations spectral analysis is usually applied
to the series constructed from T wave amplitude values, found in consecutive cycles.
The alternation of amplitude from beat to beat is reflected in the power spectrum of
these signals as a peak at 0.5 Hz. The peak amplitude normalized in respect to noise
gives the information about the T wave variability; its higher value reflects greater
repolarization dispersion and indicates risk of sudden cardiac arrest [Narayan, 2006].
An important TWA index is its phase, which may be detected by methods quantify-
ing sign-change between successive pairs of beats, or by means of Fourier transform.
TWA phase reversal is helpful in sudden cardiac arrest risk stratification.
4.2.1.3.3 Spatial representation of ECG activity; body surface potential map-
ping and vectorcardiography New diagnostic possibilities were opened by the
methods involving mapping of the spatial distribution of TWA on a thorax [Klin-
genheben et al., 2005, Fereniec and Karpinski, 2004]. It is known that sometimes
there can be no changes in the standard ECG despite the evidence of coronary artery
disease or myocardial infarction. Analysis of high-resolution ECG recorded from
multiple electrodes placed on the torso enables detection of electric activity of indi-
vidual fragments of the cardiac muscle which opens up a possibility of developing
a qualitatively new diagnostic method and a means to control the efficiency of treat-
ment.
Figure 4.30 shows body surface maps of the QRST integral for a healthy volunteer
and a patient after myocardial infarction (MI) with a documented episode of ventric-
ular tachycardia (VT). The drastic change in the shape of isopotential boundaries
may be easily observed.