Journal of Computer Science & Systems Biology

Fractal-Dimension-Based Method for Quantification of T-Wave Alternans Using Short Time Series

Abstract

Motoki Sakai and Daming Wei

The presence of T-Wave Alternans (TWA) in an electrocardiogram (ECG) has been certified as an important predictor for the risk of sudden cardiac death (SCD). TWA is a beat-to-beat change in the amplitude of a T-wave, but is rarely visible to the naked eye. Thus, automatic detection and quantification of TWA are desirable. While several automatic algorithms, such as the periodogram method or the modified moving average method (MMA), have been developed to detect or quantify TWA, most conventional methods do not effectively measure short-duration TWA (SDTWA) (<16 beats). In this paper, we proposed a fractal dimension based SDTWA quantification method, and evaluated it with simulated ECG signals with SDTWA episodes (<16 beats) based on the European ST-T database. In the evaluation, the proposed method was applied to ECG signals with TWA amplitude of 5, 15, 30, 45, 60 and 75 μV. Sensitivity and positive predictivity of over or closed to 90% were obtained except for the 5 μV SDTWA episodes. Even for 5 μV SDTWA episodes, the sensitivity reached 75%. We believe that proposed s fractal dimension based method is a promising method for SDTWA analysis.