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

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 als...

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Publicado en:Journal of Medical Systems Vol. 40; no. 3; pp. 1 - 9
Autores principales: Raeiatibanadkooki, Mahsa, Quchani, Saeed, KhalilZade, MohammadMahdi, Bahaadinbeigy, Kambiz
Formato: equations & formulas pictorial research tables/charts tracings Journal Article
Publicado: Springer Nature Mar2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2016
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-016-0433-5
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        atl: Compression and Encryption of ECG Signal Using Wavelet and Chaotically Huffman Code in Telemedicine Application.
      aug:
        au:
          Raeiatibanadkooki, Mahsa
          Quchani, Saeed
          KhalilZade, MohammadMahdi
          Bahaadinbeigy, Kambiz
        affil: Department of Biomedical Engineering, Islamic Azad University of Mashhad, Mashhad Iran
      sug:
        subj:
          Telemedicine
          Monitoring, Physiologic Methods
          Wearable Sensors Utilization
          Electrocardiography
          Encryption Methods
          Data Security Methods
          Image Processing, Computer Assisted
          Cellular Phone Utilization
          Mobile Applications
          Algorithms
          Artifacts
          Communication Protocols
          Noise
          Descriptive Statistics
      ab: 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.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        tracings
        Journal Article
      ougenre: Article
    language: English
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