Evidence map›Paper›PMID 26779641›Full record

ArticleJournal of medical systems2016

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

Mahsa Raeiatibanadkooki, Saeed Rahati Quchani, MohammadMahdi KhalilZade, Kambiz Bahaadinbeigy

Abstract read
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Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mahsa RaeiatibanadkookiDepartment of Biomedical Engineering, Islamic Azad University of Mashhad, Mashhad, Iran. mahsa.raeiati.b@gmail.com.
Saeed Rahati QuchaniDepartment of Electronic Engineering, Islamic Azad University of Mashhad, Mashhad, Iran.
MohammadMahdi KhalilZadeDepartment of Biomedical Engineering, Islamic Azad University of Mashhad, Mashhad, Iran.
Kambiz BahaadinbeigyKerman University of Medical Sciences, Kerman, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Wavelet AnalysisAlgorithmsData CompressionElectrocardiographyHeart RateHumansNonlinear DynamicsTelemedicineChaosHuffman codingMobile monitoringTCP/IP protocolWavelet

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.