High performance data compression method with pattern matching for biomedical ECG and arterial pulse waveforms

OBJECTIVEEvaluate correlations between variations in eletrocardiogram (ECG) recordings and acute myocardial infarction. METHODSUse of a low-cost software to digitalize printed and/or ".pdf" fi le format ECG recordings. Calculation of STsegment area and amplitudes of the J and Y points. RESULTSThe amplitude of the Y point holds maximum correlation with troponin concentration. ST-segment elevation is not a good statistical indicator of myocardial infarction severity. There is a strong negative correlation between the amplitude of the J point and the amount of magnesium ions, but no statistical correlation with sodium or calcium ions. Neither method for calculating the STsegment area (pixel counts and interpolation) indicated any signifi cant differences in the results. CONCLUSIONThe software used proved to be functional and costeffective. Y point amplitude is a sensitive marker of myocardial infarction, and is also a calculation method both simpler to use and less subject to error than the calculation of the ST-segment elevation area. KEY WORDSAcute myocardial infarction, telemedicine, eletrocardiogram.

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“…Therefore, the smallest unit of area determined on the paper corresponds to a 1 mm side square (fi g. 4) 18 .…”

Section: Calculation Of St Elevation J and Y Points -mentioning

confidence: 99%

Análise de registros eletrocardiográficos associados ao infarto agudo do miocárdio

Mansur¹,

Cury²,

Destro-Filho³

et al. 2006

Arq. Bras. Cardiol.

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“…With regard to clinically relevant region encoding, not much has been published. In 1994, (Chen et al, 1994) made use of regions of interest using subband analysis and synthesis orvolumetric datasets using wavelets [15]. They followed up this work with (Chen et al, 1995) by using structure preserving adaptive quantisation methods as a means of improving quality for compression rates in the regions of interest [16].…”

Section: Related Workmentioning

confidence: 99%

Multi-Resolution Analysis For Medical Image Compression

Alhanjouri¹

2011

IJCSIT

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The improvement in image compression filed is mainly related to the need of rapid and efficient techniques for the storage and transmission of data among individuals. To obtain the maximal capabilities of storage and transmission, different compression algorithms should be compared to find the optimal technique for medical image compression. This work examines the coding properties of the Wavelet, Curvelet, and wave-atom transforms as multiresolution analysis techniques. Also the comparative study is introduced to determine the best technique for medical image compression. MRI and CT are the images that used to achieve this work. Many parameters should be study for each technique to accomplish the best performance for each one. In this work, Wave-atom is stated as the best multi-resolution analysis technique for image compression applications.

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“…In 2004, Chen etc. [14] classifies the continuous blood pressure signal according to the similarity for this kind of physiological signals, and then proposes to use Huffman coding [15], runlength coding [16] and vector quantization [17][18] for further data compression. Although the compression ratio of their method lies between 14.17 and 34.40, which is apparently higher than traditional algorithms, like TP, AZTEC, CORTES etc., however it is still not a lossless compression algorithm for the continuous blood pressure data.…”

Section: Introductionmentioning

confidence: 99%

A Lossless Characteristic Compression Method for Continuous Arterial Pulse Waveforms

Lin

Huang

Lin

et al. 2012

2012 International Conference on Computing, Measurement, Control and Sensor Network

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Arterial blood pressure is one of the important biomedical waveforms that possess lots of important clinical and pathological information. This paper aims in designing a technique, which is called characteristic compression method, to perform almost lossless data compression for the continuous arterial blood pressure waveforms. This method uses the spline function to interpolate the original waveform at preselected sample points first. A fourth order spline function is considered with associated formulas in describing the coefficients of the function. A second stage compression is accompanied by using 12-bit digital data representation to store sample points and coefficients for each interval. Numerical simulation confirms that the proposed technique is feasible and does provide a very high compression rate and almost lossless reconstruction for the continuous arterial pulse wave.

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High performance data compression method with pattern matching for biomedical ECG and arterial pulse waveforms

Cited by 33 publications

References 17 publications

Análise de registros eletrocardiográficos associados ao infarto agudo do miocárdio

Análise de registros eletrocardiográficos associados ao infarto agudo do miocárdio

Multi-Resolution Analysis For Medical Image Compression

A Lossless Characteristic Compression Method for Continuous Arterial Pulse Waveforms

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