Document Type
Conference Proceeding
Language
eng
Format of Original
1 p.
Publication Date
9-19-2004
Publisher
Institute of Electrical and Electronics Engineers
Source Publication
Computers in Cardiology, 2004
Source ISSN
0-7803-8927-1
Original Item ID
doi: 10.1109/CIC.2004.1443028
Abstract
This paper presents a nonlinear signal classification approach to differentiating different atrial fibrillation terminalion stages; non-terminating (N), terminating in one minute (S), and terminating immediately (T) following the end of the recording. The nonlinear approach is based on Gaussian mixture models of reconstructed phase spaces of the last 2s of data in each recording. The removal of the ventricular component of the signal was removed by one of two methods: QRST averaging and subtraction and 4-9 Hz bandpass filtering of the recording. The accuracy of the approach is 63.3 and 66.7% for differentiating N vs. T and 60 and 70% accuracy for differentiating S us. Z for QRST subtracted and filtered data respectively. When the training data was augmented with 150 more training cases, the results improved to 66.7 and 80% for N vs. T and 70 and 70% for S us. T. An artifact was noted in the recordings that allowed a different set of criteria (the slope and percent of data remaining after last Q point at the end of each of the recordings) to accurately classify N us. T at 80% and S vs. Tat 85%.
Recommended Citation
Roberts, Felice M. and Povinelli, Richard J., "A Statistical Feature Based Approach to Predicting Termination of Atrial Fibrillation" (2004). Electrical and Computer Engineering Faculty Research and Publications. 116.
https://epublications.marquette.edu/electric_fac/116
Comments
Accepted version. Published as part of the proceedings of the conference, Computers in Cardiology, 2004: 673-676. DOI. © 2004 The Institute of Electrical and Electronics Engineers. Used with permission.