A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications

Ma, Jiali; Zhang, Tantan; Dong, Min

doi:10.1109/jbhi.2014.2357841

Cited by 96 publications

(63 citation statements)

References 26 publications

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“…The literature concerning both lossless [4][5][6][7][8] and lossy compression [9][10][11][12][13][14][15] of ECG records is vast. It includes emerging methodologies based on compressed sensing [16][17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

“…Even if the approach falls within the standard transform compression category, it achieves stunning results. Fresh benchmarks on the MIT-BIH Arrhythmia database are produced for values of PRD as in recent publications 11,12,14,15 .…”

Section: Introductionmentioning

confidence: 99%

“…Comparison between the average performance of the proposed method and the method in12 for the same mean value of PRD.…”

mentioning

confidence: 99%

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Effective high compression of ECG signals at low level distortion

Rebollo-Neira

2019

Sci Rep

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An effective method for compression of ECG signals, which falls within the transform lossy compression category, is proposed. The transformation is realized by a fast wavelet transform. The effectiveness of the approach, in relation to the simplicity and speed of its implementation, is a consequence of the efficient storage of the outputs of the algorithm which is realized in compressed Hierarchical Data Format. The compression performance is tested on the MIT-BIH Arrhythmia database producing compression results which largely improve upon recently reported benchmarks on the same database. For a distortion corresponding to a percentage root-mean-square difference (PRD) of 0.53, in mean value, the achieved average compression ratio is 23.17 with quality score of 43.93. For a mean value of PRD up to 1.71 the compression ratio increases up to 62.5. The compression of a 30 min record is realized in an average time of 0.14 s. The insignificant delay for the compression process, together with the high compression ratio achieved at low level distortion and the negligible time for the signal recovery, uphold the suitability of the technique for supporting distant clinical health care.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effective high compression of ECG signals at low level distortion

Rebollo-Neira

2019

Sci Rep

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“…In addition, even the basic procedure is very close to the competing methods. Particularly, the QS is very high for [55], [56], which are also utilizing rational functions. However, in those works, the complexity of the model, i.e., the number of inverse poles n, and the subspace dimension N were fixed a priori, while these parameters are found automatically in our algorithm.…”

Section: Methodsmentioning

confidence: 99%

Generalized Rational Variable Projection With Application in ECG Compression

Kovács

Fridli

Schipp

2020

IEEE Trans. Signal Process.

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In this paper we develop an adaptive transformdomain technique based on rational function systems. It is of general importance in several areas of signal theory, including filter design, transfer function approximation, system identification, control theory etc. The construction of the proposed method is discussed in the framework of a general mathematical model called variable projection. First we generalize this method by adding dimension type free parameters. Then we deal with the optimization problem of the free parameters. To this order, based on the well-known particle swarm optimization (PSO) algorithm, we develop the multi-dimensional hyperbolic PSO algorithm. It is designed especially for the rational transforms in question. As a result, the system along with its dimension is dynamically optimized during the process. The main motivation was to increase the adaptivity while keeping the computational complexity manageable. We note that the proposed method is of general nature. As a case study the problem of electrocardiogram (ECG) signal compression is discussed. By means of comparison tests performed on the PhysioNet MIT-BIH Arrhythmia database we demonstrate that our method outperforms other transformation techniques.

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“…The storage, transmission, and retrieval of massive bio-information should meet several compulsory requirements [7]: (1) high efficiency for rapid transmission and prompt retrieval; (2) strict information security to guarantee users’ privacy; and (3) high data fidelity to preserve the pathological information. It requires decreasing the quantity of data to be transmitted (compression) and protecting such data against unauthorized access (encryption).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous encryption and compression of medical images based on optimized tensor compressed sensing with 3D Lorenz

et al. 2016

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BackgroundThe existing techniques for simultaneous encryption and compression of images refer lossy compression. Their reconstruction performances did not meet the accuracy of medical images because most of them have not been applicable to three-dimensional (3D) medical image volumes intrinsically represented by tensors.MethodsWe propose a tensor-based algorithm using tensor compressive sensing (TCS) to address these issues. Alternating least squares is further used to optimize the TCS with measurement matrices encrypted by discrete 3D Lorenz.ResultsThe proposed method preserves the intrinsic structure of tensor-based 3D images and achieves a better balance of compression ratio, decryption accuracy, and security. Furthermore, the characteristic of the tensor product can be used as additional keys to make unauthorized decryption harder.ConclusionsNumerical simulation results verify the validity and the reliability of this scheme.

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A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications

Cited by 96 publications

References 26 publications

Effective high compression of ECG signals at low level distortion

Effective high compression of ECG signals at low level distortion

Generalized Rational Variable Projection With Application in ECG Compression

Simultaneous encryption and compression of medical images based on optimized tensor compressed sensing with 3D Lorenz

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