QOE ‒ Lossless Real-Time Multichannel Signal Encoding Algorithm

This study presents the Quite OK Encoding (QOE), a novel encoding algorithm designed for the efficient compression of multi-channel signals with a focus on losslessness, speed, and memory utilization.The evaluation of this algorithm was conducted using an electrocardiogram (ECG), a seismograph, and water parameter signals.The results indicate that it can effectively compress ECG signals, without relying on complex predictors, dictionaries, detectors, or additional encoding methods.The experiments targeted both twochannel and twelve-channel ECG signals from the MIT-BIH arrhythmia database as well as the PTB Diagnostic ECG Database.The properties of the proposed algorithm were assessed concerning cross-correlation between channels.The compression properties of the proposed algorithm were evaluated as well with seismic and water analysis signals.The computing efficiency of the proposed algorithm was assessed on the ATMega328p and STM32F446RE microcontroller systems.The findings indicate that the STM32F446RE demonstrated superior results with fewer computing instructions required.

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Publication Details

Journal
Acta Polytechnica Hungarica
Published
2025-01-01
DOI
https://doi.org/10.12700/aph.22.9.2025.9.8
Primary Topic
Blind Source Separation Techniques
Type
article
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article

QOE ‒ Lossless Real-Time Multichannel Signal Encoding Algorithm

Ján Šaliga, Jozef Kromka, Ondrej Kováč
Acta Polytechnica Hungarica
Blind Source Separation Techniques
article

QOE ‒ Lossless Real-Time Multichannel Signal Encoding Algorithm

Ján Šaliga, Jozef Kromka, Ondrej Kováč
article en

Abstract

This study presents the Quite OK Encoding (QOE), a novel encoding algorithm designed for the efficient compression of multi-channel signals with a focus on losslessness, speed, and memory utilization.The evaluation of this algorithm was conducted using an electrocardiogram (ECG), a seismograph, and water parameter signals.The results indicate that it can effectively compress ECG signals, without relying on complex predictors, dictionaries, detectors, or additional encoding methods.The experiments targeted both twochannel and twelve-channel ECG signals from the MIT-BIH arrhythmia database as well as the PTB Diagnostic ECG Database.The properties of the proposed algorithm were assessed concerning cross-correlation between channels.The compression properties of the proposed algorithm were evaluated as well with seismic and water analysis signals.The computing efficiency of the proposed algorithm was assessed on the ATMega328p and STM32F446RE microcontroller systems.The findings indicate that the STM32F446RE demonstrated superior results with fewer computing instructions required.

Acta Polytechnica HungaricaVol. 22(9)
Technical University of Košice (SK)
Openalex Percentile: Top 69%
Blind Source Separation Techniques
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