Literature DB >> 26779641

Compression and Encryption of ECG Signal Using Wavelet and Chaotically Huffman Code in Telemedicine Application.

Mahsa Raeiatibanadkooki1, Saeed Rahati Quchani2, MohammadMahdi KhalilZade3, Kambiz Bahaadinbeigy4.   

Abstract

In mobile health care monitoring, compression is an essential tool for solving storage and transmission problems. The important issue is able to recover the original signal from the compressed signal. The main purpose of this paper is compressing the ECG signal with no loss of essential data and also encrypting the signal to keep it confidential from everyone, except for physicians. In this paper, mobile processors are used and there is no need for any computers to serve this purpose. After initial preprocessing such as removal of the baseline noise, Gaussian noise, peak detection and determination of heart rate, the ECG signal is compressed. In compression stage, after 3 steps of wavelet transform (db04), thresholding techniques are used. Then, Huffman coding with chaos for compression and encryption of the ECG signal are used. The compression rates of proposed algorithm is 97.72 %. Then, the ECG signals are sent to a telemedicine center to acquire specialist diagnosis by TCP/IP protocol.

Entities:  

Keywords:  Chaos; Huffman coding; Mobile monitoring; TCP/IP protocol; Wavelet

Mesh:

Year:  2016        PMID: 26779641     DOI: 10.1007/s10916-016-0433-5

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  16 in total

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Journal:  IEEE Trans Inf Technol Biomed       Date:  2009-09-22

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Authors:  Luca Citi; Emery N Brown; Riccardo Barbieri
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6.  Variable threshold method for ECG R-peak detection.

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Journal:  J Med Syst       Date:  2011-06-22       Impact factor: 4.460

7.  Compressed sensing for real-time energy-efficient ECG compression on wireless body sensor nodes.

Authors:  Hossein Mamaghanian; Nadia Khaled; David Atienza; Pierre Vandergheynst
Journal:  IEEE Trans Biomed Eng       Date:  2011-05-19       Impact factor: 4.538

8.  Discrete wavelet transform and singular value decomposition based ECG steganography for secured patient information transmission.

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Journal:  J Med Syst       Date:  2014-09-04       Impact factor: 4.460

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Authors:  J L Salinet; J P V Madeiro; P C Cortez; P J Stafford; G André Ng; G André Ng; F S Schlindwein
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10.  Wavelet-based watermarking and compression for ECG signals with verification evaluation.

Authors:  Kuo-Kun Tseng; Xialong He; Woon-Man Kung; Shuo-Tsung Chen; Minghong Liao; Huang-Nan Huang
Journal:  Sensors (Basel)       Date:  2014-02-21       Impact factor: 3.576

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  6 in total

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Authors:  M A Murillo-Escobar; L Cardoza-Avendaño; R M López-Gutiérrez; C Cruz-Hernández
Journal:  J Med Syst       Date:  2017-02-28       Impact factor: 4.460

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Journal:  J Med Syst       Date:  2016-03-19       Impact factor: 4.460

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4.  Tree parity machine guided patients' privileged based secure sharing of electronic medical record: cybersecurity for telehealth during COVID-19.

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Journal:  Multimed Tools Appl       Date:  2021-03-21       Impact factor: 2.757

5.  Neural Synchronization-Guided Concatenation of Header and Secret Shares for Secure Transmission of Patients' Electronic Medical Record: Enhancing Telehealth Security for COVID-19.

Authors:  Arindam Sarkar; Moirangthem Marjit Singh; Jyotsna Kumar Mandal
Journal:  Arab J Sci Eng       Date:  2021-01-02       Impact factor: 2.334

6.  Complex study on compression of ECG signals using novel single-cycle fractal-based algorithm and SPIHT.

Authors:  Andrea Nemcova; Martin Vitek; Marie Novakova
Journal:  Sci Rep       Date:  2020-09-25       Impact factor: 4.379

  6 in total

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