Detecting ST level in electrocardiogram with low computational complexity

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Supervisor:
Dr. Jobbágy Ákos Andor
Department of Measurement and Information Systems

In my thesis I would like a show a new method for ECG signal analysis, which we can use in patient guardian device for ST level to measure the difference. The specialty of this method is that, it doesn’t use the ordinary algorythm for the measurement. It use low-level operations, low energy and low complexity. This is very necessery, because nowadays is more important to develope new programs with low enegery and computational requirements, which able to be correct concluded. The base of method is a timewindow, which we move the incoming ECG signal and a certain event come back with the ST level difference.

It is very important to note with the algorythm, when we use it, we need the user’s intervention, because the user give points on the ECG mean curve and from these calculate the program the difference. The inquiry of this method happened from online database, where there is a lot of annotations from doctors, who evaluated these signals. I use the so-called ST trend, which represents every EKG periods of ST level difference.

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