Lossless Compression Technique for Real-Time Photoplethysmographic Measurements

Abstract

Photoplethysmogram (PPG) signal can provide vital diagnostic information on cardiovascular functions of the human body. In this paper, a lossless, real-time compression technique based on combination of second-order delta and the Huffman encoding is proposed for the PPG signal. The algorithm was validated with 10-bit quantized PPG data collected from multiparameter intelligent monitoring in intensive care-II database under Physionet and healthy volunteers using Biopac Systems at 125-Hz sampling frequency. Using a block size of 48 samples, the average compression ratio, percentage root-mean-squared difference (PRD), and PRD normalized achieved was 2.223, 0.127, and 0.187 respectively with 30 sets of volunteers' data. Three prime clinical features, systolic amplitude, systolic upstroke time, and pulse width from the decompressed PPG waveform were evaluated with less than 1% distortion on the diagnostic measures. A study was also done to estimate the compression efficiency for different sample block size, wave morphology, and sampling frequency of raw data. The low time complexity of the proposed algorithm encourages its implementation for development low-cost real-time PPG measurement application in patient monitoring.