# Effective high compression of ECG signals at low level distortion

## TL;DR

This paper presents a fast, efficient wavelet transform-based lossy compression method for ECG signals that achieves high compression ratios at low distortion levels, suitable for remote healthcare applications.

## Contribution

It introduces a novel ECG compression technique using wavelet transforms and efficient storage, outperforming recent benchmarks in compression ratio and speed.

## Key findings

- Average compression ratio of 23.17 at PRD 0.53
- Up to 62.5 compression ratio at PRD 1.71
- Compression of 30-minute record in 0.14 seconds

## Abstract

An effective method for compression of ECG signals, which falls within the transform lossy compression category, is proposed. The transformation is realized by a fast wavelet transform. The effectiveness of the approach, in relation to the simplicity and speed of its implementation, is a consequence of the efficient storage of the outputs of the algorithm which is realized in compressed Hierarchical Data Format. The compression performance is tested on the MIT-BIH Arrhythmia database producing compression results which largely improve upon recently reported benchmarks on the same database. For a distortion corresponding to a percentage root-mean-square difference PRD of 0.53, in mean value, the achieved average compression ratio is 23.17 with quality score of 43.93. For a mean value of PRD up to 1.71 the compression ratio increases up to 62.5. The compression of a 30 min record is realized in an average time of 0.14 s. The insignificant delay for the compression process, together with the high compression ratio achieved at low level distortion and the negligible time for the signal recovery, uphold the suitability of the technique for supporting distant clinical health care.