Abstract
The 2008 Computers in Cardiology Challenge is to automatically identify and measure T-wave alternans. The study presented here applies an electrophysiological cardiac model to the problem of characterizing the T-wave variability. Thus, the hypothesis is that the existence and magnitude of T-wave alternans can be identified and measured using a cardiac inverse problem approach, where the magnitude of the alternans are measured in the model space. The dataset used in this study is a collection of records from selected databases in the Physionet databank. Additionally, a simulated ECG dataset is used to study the sensitivity and specificity of the proposed approach under various noise conditions. Results on the simulated ECG data set show that the approach is able to differentiate between 5, 10, 20, and 100 microvolt T-wave alternans in the presence of various noises between -25 and 5dB SNR. The score from the challenge, which is the Kendall rank correlation coefficient, is 0.331.
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