Study and analysis of ECG compression algorithms
| Autor: | H M Chandrashekar, M Pallavi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
020208 electrical & electronic engineering 0206 medical engineering 02 engineering and technology 020601 biomedical engineering Hilbert–Huang transform Root mean square Amplitude Encoding (memory) Compression (functional analysis) Compression ratio 0202 electrical engineering electronic engineering information engineering Discrete cosine transform Algorithm Data compression |
| Zdroj: | 2016 International Conference on Communication and Signal Processing (ICCSP). |
| DOI: | 10.1109/iccsp.2016.7754531 |
| Popis: | Electrocardiogram (ECG) is one testing method for measuring electrical activity of heart. ECG is the graphical representation of the electrical signal generated from heart. Heart is an organ of human which pump blood for the entire body. It require huge amount of data to store and transmit these ECG signals. So it is necessary for compression of the ECG signals. In few last years, many algorithms have evolved to compress the ECG signals, in that four algorithms such as Amplitude Zone Time Epoch Coding algorithm (AZTEC), Turning Point (TP), compression by using Discrete Cosine Transform (DCT) and Backward difference and compression by using Empirical Mode Decomposition (EMD) are implemented and explained detail. The performance of all the algorithms are analyzed by using two parameters namely, Percent Root means square Difference (PRD) and Compression Ratio (CR). The CR and PRD are calculated for all 48 ECG records from the database of MIT-BIH arrhythmia. Finally the CR and PRD values are compared with all the four algorithms. The experimental result indicates that the compression by EMD gives better CR and PRD compare to all other methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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