One-lead ischemia detection using a new backpropagation algorithm and the European ST-T database

A supervised neural network (NN) based algorithm was used to detect ischemic episodes from electrocardiograms (ECGs). The algorithm is tested on the European ST-T database. The algorithm is very fast in its recall state due to the NN, and uses the minimum amount of information, since it is applied on a one-lead ECG. The adaptive training backpropagation algorithm reduces dramatically the training time, and makes possible adjustment training. Even though the algorithm has some problems with detecting the exact onset and end of an ischemic episode, its performance was encouraging since it had a gross sensitivity of 84.4% for ischemia episode detection in the 60 out of 90 records on which it was initially tested. Thus, it seems to be suitable for use in critical care units due to its speed and training capabilities