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This paper aims to reduce the amount of physical space the electrocardiogram data occupies and needs to be transferred, designing an efficient algorithm ...
This work investigates a set of ECG data compression schemes in frequency domain to compare their performances in compressing ECG signals.
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In this paper, we investigated the performance on ECG arrhythmia classification on ECG signal decompressed after lossy compression with a high compression ...
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Apr 4, 2023 · In this paper, we propose an improved classification scheme for deep compressed sensing models. The framework is comprised of four modules: pre-processing; ...
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In addition the number of successive coded differences is flexible and defined with a window size. A new frame format was developed to transmit data. The ...
Sep 6, 2024 · This study proposes a deep learning-based ECG compression algorithm that guarantees a desired upper limit on the compression error.
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This paper presents a hybrid technique for the compression of ECG signals based on DWT and exploiting the correlation between signal samples.
ABSTRACT. Electrocardiogram (ECG) data compression reduced the storage requirements to develop a more efficient tele- cardiology system for cardiac analysis ...
Jul 14, 2022 · As an end-to-end method, deep learning based on an auto-encoder can directly compress the ECG signal without additional encoding algorithms.
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Jul 26, 2024 · This paper presents a real-time, low-complexity algorithm for compressing electrocardiogram (ECG) signals.
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