Continuous monitoring and detection of ST-T changes in ischemic patients

The authors developed a complete two channel ST episode detection system for long term ECG records. To improve the system sensitivity, a high performance QRS detector was implemented and some noise criteria were applied, to reject too noisy measure values (sens: 97.51% PPA: 99.96%). A three layer feedforward Artificial Neural Network (ANN), trained by backpropagation algorithm, was introduced. It processed the inputs (ST amplitude and ST slope, both in absolute value) in a nonlinear way so that the ST episodes became more easily recognizable from ANN output and the system sensitivity resulted improved (sens: 85% PPA; 88% with vs. sens: 78% PPA: 90% without ANN). The training set was built with 3 out of the 50 records of the European Society of Cardiology ST-T Database. The remaining records were used for system evaluation.<>