• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.193-195
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• 2009

In this paper, we propose an effective compression method for electrocardiogram(ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to Increase inter and intra-beat correlation. The proposed method added block division and mean-period normalization techniques on top of conventional 2-D data ECG compression methods. JPEG 2000 is chosen for compression of 2-D ECG data. Standard MIT-BIH arrhythmia database is used for evaluation and experiment. The results show that the proposed method outperforms compared to the most recent literature especially in case of high compression rate.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.11
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• pp.786-792
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• 2004

A wavelet based ECG data compression has become an attractive and efficient method in many mobile tele-cardiology applications. But large data size required for high compression performance leads a serious delay. In this paper, new wavelet compression method with minimum delay is proposed. It is based on deciding the type and compression ratio(CR) of block organically according to the standard deviation of input ECG data with minimum block size. Compression performances of the proposed algorithm for different MIT ECG Records were analyzed comparing other ECG compression algorithm. In addition to the processing delay measurement, compression efficiency and reconstruction sensitivity to error were also evaluated via random noise simulation models. The results show that the proposed algorithm has both lower PRD than other algorithm on same CR and minimum time in the data acquisition, processing and transmission.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.271-278
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• 1995

An ECG data compression algorithM using max-min slope update is proposed and a real time 3 channel ECG transmission system is implemented using the proposed algorithm. In order to effectively compress ECG data, we compare a threshold value with the max-min slope difference (MMSD) which is updated at each sample values. If this MMSD value is smaller than the threshold value, then the data is compressed. Conversely, when the MMSD value is larger than threshold value, the data is transmitted after storing the value and the length between the data which is beyond previous threshold level. As a result, it can accurately compress both the region of QRS, P, and T wave that has fast-changing and the region of the base line that slope is changing slow. Therefore, it Is possible to enhance the compression rate and the percent roms difference. In addition, because of the simplicity, this algorithm is more suitable for real-time implementation.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.221-224
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• 1996

This paper presents the ECG data compression using wavelet transform(WT) and adaptive fractal interpolation(AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data compression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arrhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 without any entroy coding.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.313-320
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• 2012

An ECG(Electrocardiogram) compression can increase the processing speed of system as well as reduce amount of signal transmission and data storage of long-term records. Whereas conventional performance evaluations of loss or lossless compression algorithms measure PRD(Percent RMS Difference) and CR(Compression Ratio) in the viewpoint of engineers, this paper focused on the performance evaluations of compression algorithms in the viewpoint of diagnostician who diagnosis ECG. Generally, for not effecting the diagnosis in the ECG compression, the position, length, amplitude and waveform of the restored signal of PQRST wave should not be damaged. AZTEC, a typical ECG compression algorithm, is validated its effectiveness in conventional performance evaluation. In this paper, we propose novel performance evaluation of AZTEC in the viewpoint of diagnostician.

• ETRI Journal
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• v.29 no.4
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• pp.530-532
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• 2007

This paper presents a simple method to implement a complete on-line portable wireless holter including an electrocardiogram (ECG) monitoring, processing, and communication protocol. The proposed algorithm significantly reduces the hardware resources of threshold estimation for ECG compression, using the standard deviation updated with each new input signal sample. The new method achieves superior performance in terms of hardware complexity, channel occupation and memory requirements, while keeping the ECG quality at a clinically acceptable level.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.12
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• pp.45-61
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• 1996

This paper presents the ECG data compression using wavelet transform (WT) and adaptive fractal interpolation (AFI). The WT has the subband coding scheme. The fractal compression method represents any range of ECG signal by fractal interpolation parameters. Specially, the AFI used the adaptive range sizes and got good performance for ECG data cmpression. In this algorithm, the AFI is applied into the low frequency part of WT. The MIT/BIH arhythmia data was used for evaluation. The compression rate using WT and AFI algorithm is better than the compression rate using AFI. The WT and AFI algorithm yields compression ratio as high as 21.0 wihtout any entropy coding.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.608-616
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• 2013

This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.23-27
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• 2009

In this paper, we propose an effective compression method for electrocardiogram (ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to increase inter and intra-beat correlation. The proposed method added block division and mean-period normalization techniques on top of conventional 2-D data ECG compression methods. JPEG 2000 is chosen for compression of 2-D ECG data. Standard MIT-BIH arrhythmia database is used for evaluation and experiment. The results show that the proposed method outperforms compared to the most recent literature especially in case of high compression rate.