Physionet Challenge 2011: Improving the quality of electrocardiography data collected using real time QRS-complex and T-Wave detection

The Physionet Challenge [1] focused on discerning between usable and unusable electrocardiography (ECG) data tele-medically from mobile embedded devices. Based on our publications [2,3,4], we have designed a method to determine the quality of ECG data and its usability using an adaptation of the Tompkins et al [5] real time QRS detection algorithm. With our modifications to the algorithm to cater to a very short length of data, out method is able to differentiate with accuracy the usability of ECG data in training set A as well as test set B.

[1]  P. A. Lynn.  Online digital filters for biological signals: some fast designs for a small computer , 1977, Medical and Biological Engineering and Computing.

[2]  Thomas Chee Tat Ho,et al.  An augmentative and portable QTc-Observer(QTO-Q2) to facilitate more purposeful outpatient monitoring , 2010, 2010 Computing in Cardiology.

[3]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[4]  E.T. Lim,et al.  Cellular phone based online ECG processing for ambulatory and continuous detection , 2007, 2007 Computers in Cardiology.

[5]  X. Chen,et al.  Smart phone-based automatic QT interval measurement , 2007, 2007 Computers in Cardiology.