The use of the Discrete Hilbert Transform (DHT) in the area of Electrocardiogram (EGG) analysis is investigated. It is shown that by using DHT processing, time alignment of individual heart-beats is not necessary, thus allowing the use of a pattern recognition method previously untried in EGG processing. It is possible to perform morphological recognition by mapping the Hilbert Transformed EGG into a two dimensional recognition matrix and achieve abnormality discrimination by applying a generalised form of the method of modified potential functions in association with a Bhattacharyya distance measure. Other topics examined include the mathematics and implementation of a Hilbert Transformer, display of ECGs, especially P- and T-wave enhancements, QRS detection and waveform delineation, and abnormality recognition (both morphology end rhythms). A suggested clinical system that consists of a 16-bit microprocessor host system capable of basic EGG processing, data storage, and report generation is outlined. The EGG processing subsystem is comprised of a hardware module using bit-slice components to accomplish the DHT and auxiliary filtering, and a custom VLSI I.C. to perform the morphological recognition. Experimental results are included in addition to a brief history of EGG computer systems, techniques , and traditional pattern recognition approaches.