New Approach for Diagnosing Left Ventricular Hypertrophy Cardiac Disease Using Fuzzy Inference System

Salih, Sameer K.; Aljunid, S. A.; Aljunid, Syed M.; Maskon, Oteh

doi:10.1166/jmihi.2014.1331

J Med Imaging Hlth Inform

2014

DOI: 10.1166/jmihi.2014.1331

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New Approach for Diagnosing Left Ventricular Hypertrophy Cardiac Disease Using Fuzzy Inference System

Sameer K. Salih¹,

S. A. Aljunid²,

Syed M. Aljunid³

et al.

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New Approach for Digital Recovery for 12 Lead Ecg Raw Data From Color Scanned Image of Printed Record

SHALLAL,

ILYAS,

SALIH

2023

J. Mech. Med. Biol.

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Many medical reports and documents in printed form are available in huge sizes in archive units inside medical centers and hospitals around the world. The printed electrocardiogram paper is one type of archive data and is more powerful for expert cardiologists to study various cardiac diseases. On the other hand, the widespread development in the ability of intelligent computer systems to process digital signals increases the benefit of these data if converted to digital form. In this paper, a new approach for digital recovery of 12-lead electrocardiogram raw data from the printed colored scanned image has been proposed. This approach implements an algorithm with four steps including delineating effective regions, color filtering, contacting detected points, and sampling the resulted digital signals to reconstruct the digital electrocardiogram signal from the printed drawing of the same signal after digital scanning with significant resolution. Also, this algorithm is designed to process various kinds of printed electrocardiogram papers. The performance of the proposed approach is evaluated qualitatively by visual inspection of the recovered and original signals in the same graph. Also, the similarity of these signals is evaluated quantitatively using some standard evaluation metrics. The simulation results show the consistency and robustness of the proposed digital recovery approach to generate electrocardiogram digital data with a high percentage accuracy exceeding 98%. Also, plotting the recovered signal with the original printed signal on the same graph shows a significant percentage of congruence in time and amplitude. Finally, the proposed idea in this study opens the way for an unlimited bank of digital electrocardiogram data with different morphologies.

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New Approach for Digital Recovery for 12 Lead Ecg Raw Data From Color Scanned Image of Printed Record

SHALLAL,

ILYAS,

SALIH

2023

J. Mech. Med. Biol.

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show abstract

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New Approach for Diagnosing Left Ventricular Hypertrophy Cardiac Disease Using Fuzzy Inference System

Cited by 1 publication

References 0 publications

New Approach for Digital Recovery for 12 Lead Ecg Raw Data From Color Scanned Image of Printed Record

New Approach for Digital Recovery for 12 Lead Ecg Raw Data From Color Scanned Image of Printed Record

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