Paper data
Title:
Using stochastic complexity for ECG signal analysis
Author(s):
Aldea Rafael, Institute of Signal Processing, Tampere University of Technology, Finland
Giurcaneanu Ciprian Doru, Institute of Signal Processing, Tampere University of Technology, Finland
Page numbers in the proceedings:
Volume III pp 391-394
Session:
Applications
Using stochastic complexity for ECG signal analysis
Author(s):
Aldea Rafael, Institute of Signal Processing, Tampere University of Technology, Finland
Giurcaneanu Ciprian Doru, Institute of Signal Processing, Tampere University of Technology, Finland
Page numbers in the proceedings:
Volume III pp 391-394
Session:
Applications
Paper abstract
Applying the MDL based digital signal segmentation method, a new QRS detection algorithm is designed and tested. It is experimentally shown that the algorithm performs better than other 11 algorithms, in terms of False Positive/False Negative estimations. The newly defined Weighted Diagnostic Distortion (WDD) measure is computed for annotated files from MIT-BIH database to evaluate the accuracy of the detection algorithm and, also, to verify how well the P,T-waves are conserved by the broken line approximation.
Paper
