ITERATIVE ECG SIGNAL FILTERING FOR BETTER MALFUNCTION RECOGNITION AND DIAGNOSIS

摘要

This paper presents an adaptive, iteratively functioning ECG signal filtering method. After a conventional pre-filtering, the waves from the signal are localized and the model's parameters are determined. The gained information allows an iterative-type filtering in permanent concordance with the aimed processing manner. The structure of the algorithm allows real-time adaptation to the heart's state. Using these methods for one channel of the MIT-BIH database, the detection rate of QRS complexes is above 99.8%. The negative influence of various noise types, like 50/60 Hz power line, abrupt baseline shift or drift, and low sampling rate was almost completely eliminated.