Gaussian-based analysis for accurate compressed ECG trace streaming |
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| Alessandra Galli, Giada Giorgi, Claudio Narduzzi |
- Abstract:
- Wearable cardiac monitors can usefully contribute to early detection of potential cardiovascular pathologies, however ECG trace data streaming over wireless links creates some significant challenges. We propose a signal analysis approach based on a Gaussian dictionary to model and compress ECG traces. The algorithm operates on fixed-length segments, and achieves effective compression for wireless data transmission, associating just 10 bytes to each Gaussian feature. At the same time it enables accurate reconstruction of ECG traces from the reduced data set. We tested our method on a set of 46 ECG recordings taken from the Physionet MIT-BIH Arrythmia Database, obtaining 90% data compression rates, while percent relative deviation of reconstructed traces is always below 5%.
- Download:
- IMEKO-TC4-2022-39.pdf
- DOI:
- 10.21014/tc4-2022.39
- Event details
- IMEKO TC:
- TC4
- Event name:
- TC4 Symposium 2022
- Title:
25th IMEKO TC4 Symposium and 23nd International Workshop on ADC and DAC Modelling and Testing (IWADC)
- Place:
- Brescia, ITALY
- Time:
- 12 September 2022 - 14 September 2022