Digitizing paper electrocardiograms: Status and challenges

Waits, George S.; Soliman, Elsayed Z.

doi:10.1016/j.jelectrocard.2016.09.007

Cited by 24 publications

(20 citation statements)

References 21 publications

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“…Nevertheless, the number of subjects with a N 20 ms inter-method QT interval difference was only 23.6%. Similar paper-to-digital ECG conversion methods have been reviewed recently [8]. The reviewed methods differed in sample sizes, algorithms, and functions.…”

Section: Discussionmentioning

confidence: 99%

“…In the process of paper-to-digital conversion, paper ECGs are first scanned into digital images, which are then converted into digital signals, which in turn can be subsequently measured digitally. There have been propositions and requirements for ECG digitization and digital measuring [4,6,7]; however, no single method is currently in universal use, and all previously proposed methods have their own advantages and disadvantages [8,9]. An accurate and reliable paper ECG digitizing and digital measuring method would enable efficient studying of archived paper ECGs of patient cohorts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experiences in digitizing and digitally measuring a paper-based ECG archive

Holkeri

Eranti

Kenttä

et al. 2018

Journal of Electrocardiology

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experiences in digitizing and digitally measuring a paper-based ECG archive

Holkeri

Eranti

Kenttä

et al. 2018

Journal of Electrocardiology

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“…Perceptual spectral centroid method for harmonic centroid of string instruments proposed by Hermes et al was apply for ECG signals, as it relates closely. [17] Different conversion in text, conversion algorithm, faulty algorithm, applications and standardization efforts were received by Waits et al recently.…”

Section: Related Workmentioning

confidence: 99%

Digitization of Documented Ecg Signals using Image Processing

Karhe,

Kale

2019

IJEAT

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In order to implement the heart disease prediction algorithms, the scanned ECG images need to be digitized. The ECG image digitization from ECG images deals with converting the ECG images in to digital format which can be processed by heart disease prediction algorithms. To present the Heart disease prediction algorithms, the digital signals can be directly applied. In this paper we have presented an effective ECG digitization technique using Dijikstraw’s shortest path algorithm. The scanned ECG images are oversampled 8 times. Then ECG curve is traced using Dijikstraw’s shortest path algorithm. The shortest path computed represents the scanned ECG signal in digitized form which can be directly used for heart disease prediction. The proposed method gives the accurate digitization by reducing the complications of the digitization process

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“…Recently, Waits et al [17] reviewed various digitization and conversion algorithms and criticised said algorithms, applications, and standardization efforts. A comprehensive list of each paper-to-digital conversion algorithm was discussed in tabular form along with limitations and corresponding solutions.…”

Section: Related Workmentioning

confidence: 99%

Robust Algorithm for Digitization of Degraded Electrocardiogram Paper Records

Patil¹,

Karandikar²

2017

IJCT

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Electrocardiogram (ECG) paper records are used commonly for diagnosing heart abnormalities. The stored ECG paper records are recorded on thermal paper and may face ink evaporation problem over the time. Generally, to overcome this problem ECG paper record is scanned and stored as an image. However, the addition of noise during scanning such as low resolution scan, blurring, folding of paper, nonuniform lighting, orientation etc. can create difficulty in information retrieval. Current work robustly handles various degradation problems encountered in ECG paper scanning using modified k-fill algorithm. The proposed algorithm is tested with 836 ECG paper recordings with different types of degradations like aging effect, folding effect, ink evaporation effect, blurring effect and low resolution effect. We extracted clinically important parameters such as heart rate etc. with accuracy of 97.33% and abnormalities such as bradycardia, tachycardia, and atrial flutter from the ECG paper records using perceptual spectral centroid method. Overall accuracy of our prediction algorithm was found out to be 98.6%. We assume our work would be low cost, preliminary expert mechanism at rural places in the absence of expert cardiologist.

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Digitizing paper electrocardiograms: Status and challenges

Cited by 24 publications

References 21 publications

Experiences in digitizing and digitally measuring a paper-based ECG archive

Experiences in digitizing and digitally measuring a paper-based ECG archive

Digitization of Documented Ecg Signals using Image Processing

Robust Algorithm for Digitization of Degraded Electrocardiogram Paper Records

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