A Real-Time ECG Data Compression and Transmission Algorithm for an e-Health Device

Abstract

This paper introduces a real-time data compression and transmission algorithm between e-health terminals for a periodic ECGsignal. The proposed algorithm consists of five compression procedures and four reconstruction procedures. In order to evaluate the performance of the proposed algorithm, the algorithm was applied to all 48 recordings of MIT-BIH arrhythmia database, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), rms, SNR, and quality score (QS) values were obtained. The result showed that the CR was 27.9:1 and the PRD was 2.93 on average for all 48 data instances with a 15% window size. In addition, the performance of the algorithm was compared to those of similar algorithms introduced recently by others. It was found that the proposed algorithm showed clearly superior performance in all 48 data instances at a compression ratio lower than 15:1, whereas it showed similar or slightly inferior PRD performance for a data compression ratio higher than 20:1. In light of the fact that the similarity with the original data becomes meaningless when the PRD is higher than 2, the proposed algorithm shows significantly better performance compared to the performance levels of other algorithms. Moreover, because the algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.

A Comparative Analysis of Methods for Evaluation of ECG Signal Quality after Compression

“…Equation ( 20 ) is for one window of length w . Signal to Noise Ratio (SNR) [ 2 , 3 , 19 , 20 , 28 , 35 , 41 ] corresponds to ( 21 ). Noise is here understood as a difference between original and reconstructed signal (error in ( 9 )).…”

“…The method angle between two vectors ( α ) [ 48 ], shown in ( 32 ), is based on the fact that the dot product of orthogonal signals is zero. Quality score (QS) [ 5 , 19 , 20 , 41 ] is a combination of two methods: CF as an efficiency measure and PRD as a measure of quality (see ( 33 )). QS is suitable for comparison of signals with various CF and PRD.…”

A Remote Health Monitoring System for the Elderly Based on Smart Home Gateway

“…The CR, PRD, QS, and the time consumption of each record is shown in Table 2 . Compared with the run length encoding method [ 11 ], the DCT-based [ 12 , 15 ] method and the empirical mode decomposition- (EMD-) based method [ 14 , 16 ] are shown in Table 3 . Figure 3() shows the comparison between the original ECG signal and the reconstructed signal of the number 100 record.…”

“…The CR of the proposed method is higher than those of the EMD-based [ 16 ] method and the DCT-based [ 12 ] method without filtering. The CRs of EMD-wavelet-based [ 14 ] method and DCT-based (with 20% filtering window) method [ 15 ] are higher than that of the proposed method in this paper, but the PRDs of such two methods are over 2%, which is unsuitable for diagnosing [ 15 ]. Also, the run length encoding [ 11 ] method has lower CR and higher PRD.…”

Wavelet-based ECG data compression optimization with genetic algorithm

“…Signal adaptation methods based on a pre-process are unsuitable for real-time applications and time-domain methods are usually sensitive to the interference of high frequency components. With high compression performance and real-time processing capability, transform-domain methods have attracted much attention of researchers recently, especially for discrete cosine transform (DCT) [7] and discrete wavelet transform (DWT) [8] due to their excellent compression performance.…”