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Copyright (c) 2023 Proceedings on Automation in Medical Engineering
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Tensors are multi-dimensional arrays which can be used to represent multi-dimensional data. Here we show how to approximate and compress multiple QRS-aligned multichannel ECG sections, each comprising P-wave, QRS-complex, and T-wave, by higher order singular value decomposition (HOSVD). We also introduce a method for the selection of components obtained by HOSVD for data approximation and a measure to quantify the quality of this tensor-based approximation of multi-dimensional data. The compression performance of this lossy data compression approach is assessed by the compression ratio.