Electrocardiogram Data Compression Using Wavelet Transform and Variable-Length Run-Length Encoding

Data compression algorithm is an effective tool to reduce the storage requirements and improve the transmission efficiency in wearable ECG monitoring system. Therefore, an efficient ECG data compression scheme which based on discrete wavelet transform (DWT) and variable-length run-length encoding was presented in this paper. DWT is utilized to compute the transform coefficients of the original data. Then using the dead-zone quantization method to quantize wavelet coefficients, and the threshold is determined according to the energy packing efficiency (EPE). Coefficients below the threshold are removed directly, while other wavelet coefficients are kept at the preset quantization level. Further, using the variable-length run-length encoding algorithm to encode the quantized coefficients. The performance of the compression method was evaluated by compressing the ECG records from the MIT-BIH arrhythmia database. The average values of compression ratio (CR), quality score (QS), quality score 1 (QS1), quality score normalized (QSN), percent root mean square difference (PRD), percent root mean square difference 1 (PRD1), percent root mean square difference normalized (PRDN) and signal to noise ratio (SNR) of the proposed method are 20.48, 47.13, 4.85, 3.12, 0.47, 4.16, 6.86 and 24.12 dB respectively. Compared with other ECG compression schemes, the results show that this scheme has better performance.