Key result
Discrete Cosine Transform (DCT) and SAPA/FAN techniques demonstrated the best compression performance for ECG signals compared to other time-frequency methods evaluated.
Why the study?
Telecardiology generates very large amounts of ECG data, creating a need for efficient, lossless compression techniques to reduce storage requirements.
Among various ECG compression techniques, DCT and SAPA/FAN demonstrate the best compression performance for telecardiology applications.
May guide ECG compression selection for telecardiology; leaves open prospective clinical validation.
Technological advances introduce different methods for telecardiology. Telecardiology includes many applications and is one of the long-standing medical fields that have grown very well. In telecardiology, a very high amount of ECG data is recorded. Therefore, to compress electrocardiogram data (ECG), there is a need for an efficient technique and lossless compression. The compression of ECG data reduces the storage needs for a more efficient cardiological system and for analyzing and diagnosing the condition of the heart. In this paper, ECG signal data compression techniques are analyzed using the MIT-BIH database and then compared with the Apnea-ECG and Challenge 2017 Training bases. During the study, some of the various techniques of frequency analysis, range and time are widely used, such as run-time coding, AZTEC, Spin-Coding, FFT, DCT, DST, SAPA/FAN and DCT-II, where DCT and SAPA/FAN have the best compression performance compared to other methods.
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Hakkak et al. (2019) studied ECG signal compression (n=35). Time-frequency-based ECG compression techniques (e.g., SAPA/FAN, DCT, FFT) vs. Other compression methods (e.g., AZTEC, Spin-Coding) was evaluated on Compression performance (Compression Ratio, Percent Root-Mean-Square Difference, Quality Score). Discrete Cosine Transform (DCT) and SAPA/FAN techniques demonstrated the best compression performance for ECG signals compared to other time-frequency methods evaluated.
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