Key result
A curvature-based ECG signal compression method preserved all feature points of the ECG signals and was more efficient than the amplitude zone time epoch coding method.
A curvature-based ECG signal compression method effectively preserves critical diagnostic features (P, Q, R, S, T waves) and improves efficiency for wireless transmission.
May aid wireless ECG transmission efficiency; leaves open clinical validation and workflow integration.
As electrocardiogram (ECG) signals are generally sampled with a frequency of over 200 Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently on a wireless personal area network (WPAN). In this paper, an ECG signal compression method for communications on WPAN, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, and T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes were extracted with the proposed method, which uses local extrema of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes were added according to the iterative vertex selection method. Through the experimental results on the ECG signals from Massachusetts Institute of Technology-Beth Israel hospital arrhythmia database, it was concluded that the vertexes selected by the proposed method preserved all feature points of the ECG signals. In addition, it was more efficient than the amplitude zone time epoch coding method.
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Kim et al. (2012) studied Arrhythmia (ECG signals). Curvature based ECG signal compression method vs. Amplitude zone time epoch coding method was evaluated on Preservation of feature points and efficiency. A curvature-based ECG signal compression method preserved all feature points of the ECG signals and was more efficient than the amplitude zone time epoch coding method.