Influence of paper electrocardiogram digitizing on T wave and QRS complex morphology parameters

Image digitization of discontinuous and degraded electrocardiogram paper records using an entropy-based bit plane slicing algorithm

BACKGROUND

Electrocardiograms (ECGs) are routinely recorded and stored in a variety of paper or scanned image format. Current ECG recording machines record ECG on graph paper, also it provides digitized ECG signal along with automated cardiovascular diagnosis (CVD). However, such recording machines cannot analyse preserved paper ECG records as it requires input in terms of digitized signal. Therefore, it is important to extract ECG signal from these preserved paper ECG records using digitization method. There are different paper degradations that adversely affect digitization process. The purpose of this work is to perform an image enhancement and digitization of the degraded ECG images to extract continuous ECG signal.

METHODS

In this paper, we propose entropy-based bit plane slicing (EBPS) algorithm in which pre-processing is done using dominant color detection and local bit plane slicing. Maximum entropy based adaptive bit plane selection is applied to the pre-processed image. Discontinuous ECG correction (DECGC) is then done to produce continuous ECG signal.

RESULTS

The algorithm is tested on 836 different degraded paper ECG records obtained from various diagnostic centers. After analysis with 101 known ground truth ECG signals the accuracy, sensitivity, specificity and overall F-measure of ECG is 99.42%, 99.69%, 99.81% and 99.26% respectively. The RMS error and correlation between the extracted digitized signal and ground truth for 101 cases is 0.040 and 99.89% respectively.

CONCLUSIONS

The EBPS method is able to remove all types of degradation in paper ECG records to generate a uniform digitized signal. Instead of manual measurement and prediction from archived paper ECG records, automated prediction (using already existing cardiovascular diagnosis software) is possible with the help of extracted digitized signal obtained using proposed digitization method, which will also help retrospective cardiovascular analysis.

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

BACKGROUND

No established method for digitizing and digital measuring of paper electrocardiograms (ECG) exists. We describe a paper ECG digitizing and digital measuring process, and report comparability to manual measurements.

METHODS

A paper ECG was recorded from 7203 health survey participants in 1978-1980. With specific software, the ECGs were digitized (ECG Trace Tool), and measured digitally (EASE). A sub-sample of 100 ECGs was selected for manual measurements.

RESULTS

The measurement methods showed good agreement. The mean global (EASE)-(manual) differences were 1.4ms (95% CI 0.5-2.2) for PR interval, -1.0ms (95% CI -1.5-[-0.5]) for QRS duration, and 11.6ms (95% CI 10.5-12.7) for QT interval. The mean inter-method amplitude differences of RampV5, RampV6, SampV1, TampII and TampV5 ranged from -0.03mV to 0.01mV.

CONCLUSIONS

The presented paper-to-digital conversion and digital measurement process is an accurate and reliable method, enabling efficient storing and analysis of paper ECGs.

Digitizing paper electrocardiograms: Status and challenges

The paper electrocardiogram (ECG) has been widely used for cardiac assessment for well over a century. ECGs can be obtained quickly and cheaply. For this reason, an ever-growing amount of paper ECG records continue to accumulate, some of which are stored into a paper-only format. Converting paper ECGs into digital form has been proposed as the most efficient means to store and analyze an otherwise cumbersome paper archive. In this article, a literature review was conducted for conversion algorithms, criticisms of said algorithms, applications, and standardization efforts. The algorithms were compared in tabulated form. Key functions that have advanced the conversion algorithms as well as remaining challenges are discussed.