Functional heart diagnosis by the visualization of time-dependent potential deviation and topologic map-based shape analysis from high-resolution ECG

摘要

Our work focuses on functional heart analysis during acute myocardial infarction based on time-sequence data derived with a high-resolution ECG technique. This data stream can be interpreted as a sequence of potential deviation images. The analysis is performed by both visualizing the potential deviation onto the thorax as well as by shape analysis of the underlying ECG signals using a topologic map. The algorithm deals with the measurement of similarity between different pathological signal types. In contrast to other techniques, the whole ECG signal, coded as a feature vector, is used as input for the self-organizing map. The results show that this approach is suitable for handling unsharp class transitions common to the medical domain.