الفهرس 
Electrocardiogram SignalOnly 14 pages are availabe for public view
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Abstract
Biomedical signals, in general, are the electrical signals that represent different actions in the body. Specifically, the electrocardiogram signal (ECG) describes the human heart activities. The compression of this signal is highly beneficial for either wireless transmission or storage. In this work, a new technique for ECG compression is developed and introduced. The technique is based on the observation that the ECG signal in the normal conditions is very stable with highly correlated successive pulses. Thus, the technique performs differential encoding between each new pulse and a stored reference pulse. This idea is inspired by the techniques of video compression where the inter-frame changes are very limited. Therefore, a high signal compression ratio can be obtained. Simulations on selected records from the MIT-BIH database are performed to assess the introduced technique performance and compare it to the modern techniques. The algorithm also addresses common problems and inefficiencies that commonly affect the ECG signal and shows that it can overcome them without a major loss. The performance is characterized by the compression ratio (CR) which measures how much the algorithm is capable of compressing the signal and the percentage of root mean square differences (PRD) that measures the dissimilarity between the reconstructed and the original signals. The proposed algorithm achieves a CR of 105 with PRD below 1.25% for stable ECG signals. Moreover, a comparison with the existing ECG compression methods demonstrated the superiority of the new proposed technique.