Automated methods for ischemia detection in long-duration ECGs

Myocardial ischemia diagnosis using long-duration electrocardiographic recordings is a simple and noninvasive method that needs further development before being used in everyday medical practice. Several techniques that automate ischemia detection have been proposed during the last decade and are under evaluation. They are based on different methodologic approaches, which include digital signal analysis, rule-based techniques, fuzzy logic methods, and artificial neural networks, with each approach exhibiting its own advantages and disadvantages. Most recent systems employ artificial neural networks to perform diagnoses since they have demonstrated great consistency in producing accurate results. The performance of the developed detection systems is very promising but they need further evaluation.