New method for digitization and computerized analysis of paper recordings of standard 12-lead electrocardiograms

Lawson, William T.; Wagner, Galen S.; Startt-Selvester, R.S.; Ybarra, Gary

doi:10.1109/cic.1995.482566

Cited by 14 publications

(9 citation statements)

References 3 publications

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“…After the MIT-BIH arrhythmia database was created, a lot of research work in digitization of ECG paper recordings has been done [8]. Preserving the smoothness of the digitized ECG and the peaks of the PQRS and T waves remains a difficult task.…”

Section: Literature Surveymentioning

confidence: 99%

Digitization of Electrocardiogram Using Bilateral Filtering

Sadasivan¹

2020

Preprint

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Electrocardiogram (ECG) is one of the most basic tools available for the detection of cardiovascular disease (CVD) which has evolved as one of the major causes of death in recent times, spanning countries. Conventionally, ECGs are printed on graph sheets which keep fading away with time. Hence, the preservation of ECG graph sheets is difficult. Digitization of printed ECG graph sheets is a solution to this problem. Digitization also helps in faster analysis and interpretation of ECG signals. Although the previous works have succeeded in smoothing ECG after extracting the signal from graph sheet, the cost amounts to loss of peak amplitude characteristics leading to wrong diagnosis. In this work, we propose a digitization technique to extract ECG signals from graph sheets. The proposed bilateral filter based method achieves a high degree of smoothness with all the peak characteristics intact when compared to other implementations using Butterworth filters. With this technique, it is now possible to create extensive databases similar to MIT-BIH from printed ECG graph sheets. A high level of automation is achieved, and results verified with over 60 ECGs and compared.

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Section: Literature Surveymentioning

confidence: 99%

Digitization of Electrocardiogram Using Bilateral Filtering

Sadasivan¹

2020

Preprint

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“…This is a tedious process. A scanning resolution of 200 dpi [4] is used for scanning signal printouts and used gray scale thresholds to separate the ECG trace from the background grid lines.…”

Section: Literature Surveymentioning

confidence: 99%

Digitization of documented signals using vertical scanning

Patil¹,

Karandikar

2015

2015 International Conference on Microwave, Optical and Communication Engineering (ICMOCE)

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The document digitization is one of the emerging trends of digitization. The digitization of documents allows retrieving of information from paper document. This information can be ECG, EEG, humidity etc. The document digitization process involves conversion of paper document into image and processing of obtained image to extract information. The digitized signals can be directly applied to present prediction algorithms. As the digitization literature is surveyed, the process of extraction of digital signal from scanned paper document plays very important role in document digitization process. Generally this is done using horizontal scanning. This paper emphasize on use of vertical scanning for extraction of signal trace from paper documents in contrast to horizontal scanning. The vertical scanning method reduces complexity of the digitization process as well as gives accurate digitization.

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“…Ravichandran et al extracted ECG signal [14] and interfaced with patient's record using optical character recognition (OCR). Lawson et al used scanning resolution of 200 dpi and grayscale thresholds were used to separate the ECG trace from the background grid lines [15]. Their low resolution method results in loss of data accuracy and grayscale thresholds results in missing pixels.…”

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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New method for digitization and computerized analysis of paper recordings of standard 12-lead electrocardiograms

Cited by 14 publications

References 3 publications

Digitization of Electrocardiogram Using Bilateral Filtering

Digitization of Electrocardiogram Using Bilateral Filtering

Digitization of documented signals using vertical scanning

Robust Algorithm for Digitization of Degraded Electrocardiogram Paper Records

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