A novel entropy measure for analysis of the electrocardiogram


There has been much recent research into extracting useful diagnostic features from the electrocardiogram with numerous studies claiming impressive results. However, the robustness and consistency of the methods employed in these studies is rarely, if ever, mentioned. Hence, we propose two new methods; a biologically motivated time series derived from consecutive P-wave durations, and a mathematically motivated regularity measure. We investigate the robustness of these two methods when compared with current corresponding methods. We find that the new time series performs admirably as a compliment to the current method and the new regularity measure consistently outperforms the current measure in numerous tests on real and synthetic data.

Additional Information: Department: Computer Science. If you have discovered material in AURA which is unlawful e.g. breaches copyright, (either theirs or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.
Institution: Aston University
Uncontrolled Keywords: P-wave,kernel entropy,chaos,time series,regularity,complexity,nonlinear dynamics
Last Modified: 08 Dec 2023 08:37
Date Deposited: 09 Dec 2010 10:45
Completed Date: 2007-02
Authors: Woodcock, Dan


Export / Share Citation


Additional statistics for this record