ECG signal compression using data extraction and truncated singular value decomposition

In this paper a novel algorithm is used for compressing ECG data. The algorithm uses two techniques simultaneously to get a better compression of ECG data. Firstly Data extraction: a sampling technique based on a user defined threshold value is applied on ECG followed by Truncated Singular Value Decomposition. Changing the number of Singular Values higher compression can be achieved. The proposed method provides two variables: Threshold & Number of Singular Value, which can be changed to achieve optimum compression while keeping the error low. Compression performance & quality of reconstructed ECG in the proposed method is evaluated using Compression Ratio (CR) & Percent Root Mean Square Difference (PRD).