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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Nabilah Ibrahim
Universiti Tun Hussein Onn Malaysia

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Validation test on 3d heart phantom for mitral valve leaflet tracking Lina Farhana Mahadi; Nabilah Ibrahim; Shahnoor Shanta; Hideyuki Hasegawa
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp717-725

Abstract

Mitral valve movement is essential to be identified in order to monitor the abnormality of blood flow in right side of heart. The estimation and tracking of mitral valve has seldom been investigated since it required high temporal rate to scan the echocardiography images and it depends on the operator to capture the low-speckle and-noise images. This study presents the validation experiment performed on heart phantom made of thermoplastic polyurethane (TPU) filament which the objective is to validate the previous features tracking technique implemented in mitral valve locating in video frames using Kanade-Lucas-Tomasi (KLT) algorithm. The outcome was able to automatically detect the edge of mitral valve and thus in future, it manages to predict the flowing of blood pattern. An in-vitro experiment was conducted which involved a valve phantom scanning in water tank that connected to water pump. It was found in this study that the technique capable to detect and visualize the mitral valve up to 59 frames in 2.36 secondsby tracking the features of minimum eigenvalue within the selected region. It was also produced a good agreement of valve distance between the true value and the measured one, which achieved the minimum of 88% similarity. This yielded the validation of the proposed technique to track and visualize the mitral valves.
Detection of cardiac sounds components: a pilot study Norezmi Jamal; Nabilah Ibrahim; MNAH Sha’abani; Zulkifli Taat
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1330-1337

Abstract

This paper presents a preliminary study related to the detection and identification of cardiac sounds components including first sound (S1), second sound (S2) and murmurs. Detection and identification of cardiac sounds are an important process in automated cardiac sound analysis system in order to automatically diagnose people who are having cardiovascular disorder and determine the existence of murmurs. Sixteen of recorded cardiac sounds (eight normal cardiac sounds, four abnormal cardiac sounds with systole murmur, and four abnormal cardiac sounds with diastole murmur) from PASCAL Classifying Heart Sounds Challenge database were examined for analysis. This work is significant in studying the time and time-frequency based detection of cardiac sounds components characteristics. In time-based analysis, envelope of signal energy was used to do the peak detection of S1, S2 and murmur and also analysis of cardiac cycle, systole and diastole duration. While time-frequency based analysis was used to determine the S1, S2 and murmur frequency range. The findings yield the overall accuracy of envelope-based detection for normal cardiac sound signal at 60.85% while for abnormal cardiac sound signal at 57.24%.
Velocity hemodynamic patterns in aortic valve stenosis: a study of inlet velocity during systole phase Nur’Afifah Yousri; Nabilah Ibrahim; Ishkrizat Taib
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i3.pp884-891

Abstract

This work highlighted a close-up version of the aortic valve that provide detail parameter and clearer graphics compared to the 3D version. Therefore, four simplified models are designed and simulated by using computational fluid dynamics (CFD) which are one healthy valve model (100%) and three stenotic models with varying valve opening (70%, 50%, and 30%). The model dimensions and setup parameters are determined by comparing the healthy aortic valve with the previous data. The analysis focused on two different views, which are the view on a targeting line velocity along the x-axis, and the view at the y-axis around the aortic valve. Results on the evaluation graph at the x-axis and y-axis show significant differences in flow patterns between healthy and aortic valve stenosis. The healthy model of 100% valve opening depicted a lower velocity (m/s) at 1.5m/s compared to the stenotic model of 70%, 50%, and 30% valve opening that showed higher velocities of 3.24 m/s, 6.09 m/s, and 14.57 m/s, respectively, due to the narrowing of the valve opening. Thus, the smallest orifice of the valve produced a higher velocity. This finding highlights the importance of hemodynamic assessment in aortic valve stenosis by providing valuable insight for clinicians in pre-surgical evaluation.
Co-Authors Hideyuki Hasegawa Ishkrizat Taib Lina Farhana Mahadi MNAH Sha’abani Norezmi Jamal Nur’Afifah Yousri Shahnoor Shanta Zulkifli Taat