Welch Allyn Cardioperfect Workstation, PEDMEANS ECG Interpretation Module - Physicians - User Manual - Manual (Page 5)

CardioPerfect Workstation
PEDMEANS ECG Interpretation Module Physicians Manual
DIR 80015051 Rev. C 5 / 55
1 Introduction
The PEDMEANS algorithm covers ages from 1 day through 17 years.
The way that a computer follows in the interpretation of a signal such as the electrocardiogram
(ECG) differs fundamentally from those by which a human observer arrives at its understanding.
The princi
pal difference is in the manner in which a computer “looks” at the signal. To be
interpretable, a continuous (analog) signal must be converted into numbers, i.e., digitized. The
signals are measured at short intervals, and the measured values (the samples) are stored as
digital numbers. On this set of numbers the analysis must take place. The diagnostic criteria in this
manual assume the pediatric ECGs to be recorded with lead V3R instead of V3 and lead V7 instead
of V5, following common practice in The Netherlands. The Welch Allyn CardioPerfect PC-based
interpretive resting ECG system also allows for pediatric ECGs to be performed using the standard
lead set. The PEDMEANS algorithm can analyze this data and provide both measurements and
interpretive statements.
After collection of the data, the processing follows a number of successive stages:

Signal conditioning

Pattern recognition

Parameter extraction

Diagnostic classification
Each of these steps must be performed correctly to ensure a satisfactory final result. If, for
instance, the signals are not correctly cured of disturbances this may result in a faulty waveform
recognition. The diagnostic classification is then likely to come out wrong. The successive steps will
now be discussed more extensively.
1.1 Signal conditioning
The ECG signal can be disturbed in several ways:

Continuous noise of a single frequency, sometimes with higher harmonics, due to 50 or 60 Hz
mains interference.

Drift: more or less gradual baseline shifts, e.g., caused by respiration.

Bursts of noise of mixed frequencies and various amplitudes due to electrical signals from
active muscles.

Sudden baseline jumps due to changes in electrode-skin impedance.

Spikes: isolated, large amplitude variations of short duration.

Amplitude saturation of the signal.
To correct these disturbances several techniques have been used. Mains interference is
suppressed by an adaptive filter that estimates the coming noise estimates and subtracts the
estimates from the encountered signal. Baseline shift is corrected by simply connecting the onsets
of successive QRS complexes by straight lines and determining the signal amplitudes with respect
to these line segments. Beat selection and averaging (see below) help to reduce disturbances of
muscle noise. If a disturbance is detected that may affect the diagnostic classification, the program
issues a warning.