Automated ECG interpretation

Automated ECG interpretation is the use of artificial intelligence and pattern recognition software and knowledge bases to carry out automatically the interpretation, test reporting, and computer-aided diagnosis of electrocardiogram tracings obtained usually from a patient.

The first automated ECG programs were developed in the 1970s, when digital ECG machines became possible by third generation digital signal processing boards. Commercial models, such as those developed by Hewlett-Packard, incorporated these programs into clinically used devices.

During the 1980s and 1990s, extensive research was carried out by companies and by university labs in order to improve the accuracy rate, which was not very high in the first models. For this purpose, several signal databases with normal and abnormal ECGs were built by institutions such as MIT and used to test the algorithms and their accuracy.

The manufacturing industries of ECG machines is now entirely digital, and many models incorporate embedded software for analysis and interpretation of ECG recordings with 3 or more leads. Consumer products, such as home ECG recorders for simple, 1-channel heart arrhythmia detection, also use basic ECG analysis, essentially to detect abnormalities. Some application areas are:

The automated ECG interpretation is a useful tool when access to a specialist is not possible. Although considerable effort has been made to improve automated ECG algorithms, the sensitivity of the automated ECG interpretation is of limited value in the case of STEMI equivalent as for example with "hyperacute T waves", de Winter ST-T complex, Wellens phenomenon, Left ventricular hypertrophy, left bundle branch block or in presence of a pacemaker. Automated monitoring of ST-segment during patient transport is increasingly used and improves STEMI detection sensitivity, as ST elevation is a dynamical phenomenon.

Translated and reproduced by permission of the author.

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