Time series prediction for event triggering

摘要

Delays in event detection in time-varying data can be reduced by predicting the time-varying data and then detecting the event in the predicted data. This finds application in the triggering of medical imaging devices, where physiological events can be detected in the time-varying data. An artificial neural network can be trained to predict data such as ECG signals from which a detection algorithm can accurately predict the occurrence of an event that will serve as a reference point for triggering.