MEANS ECG Physicians’ Manual for Welch Allyn CP Series Electrocardiographs

MEANS ECG Physicians' Manual for Welch Allyn CP Series Electrocardiographs

Revision date: 2016-07

Welch Allyn 4341 State Street Road Skaneateles Falls, NY 13153 USA © 2016, DIR: 80011564, Ver: F www.welchallyn.com

Caution

Federal US law restricts sale of the device identified in this manual to, or on the order of, a licensed physician.

© 2016 Welch Allyn. All rights are reserved. To support the intended use of the product described in this publication, the purchaser of the product is permitted to copy this publication, for internal distribution only, from the media provided by Welch Allyn. No other use, reproduction, or distribution of this publication, or any part of it, is permitted without written permission from Welch Allyn. Welch Allyn assumes no responsibility for any injury to anyone, or for any illegal or improper use of the product, that may result from failure to use this product in accordance with the instructions, cautions, warnings, or statement of intended use published in this manual.

About this manual

This manual documents the logic behind the diagnostic criteria provided by the Welch Allyn CP series interpretive resting ECG system. It is provided as a supplement to the electrocardiographs user's manual for those interested in or requiring knowledge of specific details of the system's algorithms. Please refer to the electrocardiographs general user's manual for information about use, installation and configuration, as well as applicable precautions and warnings.

The algorithms employed in our system are collectively known as the Modular ECG Analysis System, MEANS. MEANS was developed by the Department of Medical Informatics at the Erasmus University of Rotterdam in the Netherlands. Portions of this manual are copyright  1999 by the Department of Medical Informatics, Faculty of Medicine and Health Sciences, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands.

The initial sections of this manual provide an overview of the general signal processing methodology involved, followed by detailed descriptions of the contour and rhythm analysis statement logic, and an index to all statements. The final section provides an analysis of the performance of MEANS.

Contents

Table Caption: This table outlines a manual for analyzing electrocardiograms (ECGs), divided into two main sections: Contour Analysis and Rhythm Analysis, with detailed sub-sections and page references for each topic.

1 Introduction

Computers and humans interpret ECG signals in fundamentally different ways. The principal 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 sampling must be dense enough to ensure sufficient fidelity in rendering the original analog signal. Current standards for ECG recording recommend a sampling rate of 500 Hz or higher.

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 AC 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.

The I-wave and K-wave isoelectric segments within the QRS are not included in the durations measurements of the respective adjacent waveform. Instead, the I and K durations are separate measurement values that are presented in the measurements report.

The electrocardiograph does not need to be configured with specific filter settings to pass the distortion test.

1.2 Pattern recognition

This part deals with the analysis of the various waveforms. First of all, the QRS complexes must be detected . No other waves or artifacts should be labeled as such. The intervals between QRS complexes are measured and stored. After all QRS complexes have been detected, they are typified , i.e., a comparison is performed that gives rise to classes of similar QRS complexes.

Often there is only one type of QRS complex. If there are more, the 'ordinary,' 'representative' or 'dominant' one is established; the others are 'extraordinary' or 'nondominant'. Mostly, the number of dominant complexes in a recording is larger than that of the non-dominant ones. In special cases this may not be true. In bigeminy their number may be equal to that of the non-dominant complexes, or be one less or one more, depending on when