Garuda - Garba Rujukan Digital

A Portable Insole Pressure Mapping System Kian Sek Tee; Yogindra Syam Hari Javahar; Hashim Saim; Wan Nurshazwani Wan Zakaria; Safinaz Binti Mohd Khialdin; Hazlita Isa; M. I. Awad; Chin Fhong Soon
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.7227

The human locomotion is studied through gait analysis and is best observed instrumentally rather than observing visually. Thus, a portable insole pressure mapping system is built to assist in studying the human gait cycle. The pressure distribution is determined by instrumentally mapping the insole using force sensitive resistive sensors that are connected to Arduino UNO via cables. The values are saved into a secure digital card that could be post processed. Hardware and software design phase are executed for the development of this project. The outcomes match to the knowledge of human gait definitions in static posture and normal walking.

Vision Based Human Decoy System for Spot Cooling Tan Chun Hou; Wan Nurshazwani Wan Zakaria; Tai Sue Jing; Razali Tomari; Tee Kian Sek; Anis Azwani Muhd Suberi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.7229

This project aims to reduce the energy consumption of air conditioner usage while maintaining occupant comfort. Cooling down the unoccupied space can be considered as waste of energy. Therefore, a human decoy system is proposed to track any human in the detection area. Image contains depth data in each pixel which can be used to detect the presence of target subject as well as their position. The acquired position data is processed by using MATLAB and subsequently is transmitted to Arduino Mega using serial communication to control stepper motors. The experimental results show that the air conditioner airflow is successfully can be directed to the target human subject with average response of 0.860 seconds per movement within detection area.

A simulation study of excitation coil design in single-sided mpi scanner for human body application Nurmiza Othman; Muhamad Fikri Shahkhirin Birahim; Wan Nurshazwani Wan Zakaria; Mohd Razali Md Tomari; Md Nor Ramdon Baharom; Luqman Hakim
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Magnetic particle imaging (MPI), a tomographic imaging method has been introduced for 3D imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements: tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high quality of image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this work focused on finding alternative design of excitation coil used in single sided MPI to produce up to 2 mT with high homogeneity of field distribution in the MNPs at the varied depth of 10 to 30 mm under the excitation coil. We proposed several designs with variation in physical properties and coil arrangement based on simulation study carried out by using Ansys Maxwell.

Investigation of white blood cell biomaker model for acute lymphoblastic leukemia detection based on convolutional neural network Syadia Nabilah Mohd Safuan; Mohd Razali Md Tomari; Wan Nurshazwani Wan Zakaria; Mohd Norzali Hj Mohd; Nor Surayahani Suriani
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Acute Lymphoblastic Leukemia (ALL) is a disease that is defined by uncontrollable growth of malignant and immature White Blood Cells (WBCs) which is called lymphoblast. Traditionally, lymphoblast analysis is done manually and highly dependent on the pathologist’s skill and experience which sometimes yields inaccurate result. For that reason, in this project an algorithm to automatically detect WBC and subsequently examine ALL disease using Convolutional Neural Network (CNN) is proposed. Several pretrained CNN models which are VGG, GoogleNet and Alexnet were analaysed to compare its performance for differentiating lymphoblast and non-lymphoblast cells from IDB database. The tuning is done by experimenting the convolution layer, pooling layer and fully connected layer. Technically, 70% of the images are used for training and another 30% for testing. From the experiments, it is found that the best pretrained models are VGG and GoogleNet compared to AlexNet by achieving 100% accuracy for training. As for testing, VGG obtained the highest performance which is 99.13% accuracy. Apart from that, VGG also proven to have better result based on the training graph which is more stable and contains less error compared to the other two models.

A non-invasive and non-wearable food intake monitoring system based on depth sensor Muhammad Fuad Kassim; Mohd Norzali Haji Mohd; Mohd Razali Md Tomari; Nor Surayahani Suriani; Wan Nurshazwani Wan Zakaria; Suhaila Sari
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2256

The food intake counting method showed a good significance that can lead to a successful weight loss by simply monitoring the food intake taken during eating. The device used in this project was Kinect Xbox One which used a depth camera to detect the motion of a person’s gesture and posture during food intake. Previous studies have shown that most of the methods used to count food intake device is worn device type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect camera and monitors the gesture of the user while eating. Then, the gesture data is collected to be recognized and it will start counting the food intake taken by the user. The system recognizes the patterns of the food intake from the user by following the algorithm to analyze the gesture of the basic eating type and the system get an average accuracy of 96.2%. This system can help people who are trying to follow a proper way to avoid being overweight or having eating disorders by monitoring their meal intake and controlling their eating rate.

A simulation study of excitation coil design in single-sided mpi scanner for human body application Nurmiza Othman; Muhamad Fikri Shahkhirin Birahim; Wan Nurshazwani Wan Zakaria; Mohd Razali Md Tomari; Md Nor Ramdon Baharom; Luqman Hakim
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Magnetic particle imaging (MPI), a tomographic imaging method has been introduced for 3D imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements: tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high quality of image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this work focused on finding alternative design of excitation coil used in single sided MPI to produce up to 2 mT with high homogeneity of field distribution in the MNPs at the varied depth of 10 to 30 mm under the excitation coil. We proposed several designs with variation in physical properties and coil arrangement based on simulation study carried out by using Ansys Maxwell.

A simulation study of excitation coil design in single-sided mpi scanner for human body application Nurmiza Othman; Muhamad Fikri Shahkhirin Birahim; Wan Nurshazwani Wan Zakaria; Mohd Razali Md Tomari; Md Nor Ramdon Baharom; Luqman Hakim
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Magnetic particle imaging (MPI), a tomographic imaging method has been introduced for 3D imaging of human body with some potential applications such as magnetic hyperthermia and cancer imaging. It involves three important elements: tracer development using magnetic nanoparticles (MNPs), hardware realization (scanner using excitation and pickup coils), and image reconstruction optimization. Their combination will produce a high quality of image taken from any biological tissue in the human body based on the secondary magnetic field signal from the magnetized MNPs that are injected into human body. A homogeneous and adequate magnetic field strength from an excitation coil is needed to enhance the quality of the secondary signal. However, the complex surface topography of human body and physical properties of an excitation coil influence the strength and the homogeneity of the magnetic field generation at the MNPs. Therefore, this work focused on finding alternative design of excitation coil used in single sided MPI to produce up to 2 mT with high homogeneity of field distribution in the MNPs at the varied depth of 10 to 30 mm under the excitation coil. We proposed several designs with variation in physical properties and coil arrangement based on simulation study carried out by using Ansys Maxwell.

Computer aided system for lymphoblast classification to detect acute lymphoblastic leukemia Syadia Nabilah Mohd Safuan; Mohd Razali Md Tomari; Wan Nurshazwani Wan Zakaria; Mohd Norzali Haji Mohd; Nor Surayahani Suriani
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 2: May 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i2.pp597-607

Acute lymphoblastic leukemia (ALL) is a disease that is detected by the presence of lymphoblast cell. Basically, lymphoblast cell is the abnormal cell of lymphocyte which is one of the White Blood Cell (WBC) types. Early prevention is suggested as this disease can be fatal and caused death. Traditionally, ALL is detected by using manual analysis which is challenging and time consuming. It can also yield inaccurate result as it is highly dependent on the pathologist’s skills. Industry has come out with hematology counter which is fast, accurate and automated. However, these machines are costly and cannot be afforded by some countries. For that reason, Computer Aided System (CAS) will be a great help to the pathologist for assisting purposes and it also can act as second opinion for the pathologist. This system contains six main steps which are color space correction, WBC segmentation, post processing, clumped area extraction, feature extraction and lymphoblast classification. Firstly, color space correction is apply by using l*a*b* color space to standardize the image’s intensity. Next, WBC segmentation is made to prune out WBC region using color space analysis with Otsu thresholding. However, segmented image contains noises that need to be eliminated and it is accomplished by applying morphological filter with Connected Component Labelling (CCL). There is an overlapping WBC which need to be separated by using Watershed method to extract the individual cells. Next, feature extraction is made to collect the cell’s data to be fed into the classifier. Classifier used in this system to classify lymphoblast is Support Vector Machine (SVM) and this system is able to achieve 96.69% of accuracy.

Retina blood vessel extraction based on kirsch’s template method Nur Syazlin Zolkifli; Ain Nazari; Mohd Marzuki Mustafa; Wan NurShazwani Wan Zakaria; Nor Surayahani Suriani; Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp318-325

Analysis on the retina blood vessels from fundus images have been widely used in the medical community to detect the disorder condition in the blood vessels. An automated tracing of retina blood vessel can help to provide valuable computer-assisted diagnosis for the ophthalmic disorders. Thus, it helps to reduce the time for the ophthalmologist to analyses and diagnose the result of the fundus image of patient. The purpose of this research is to build an algorithm to trace the retina blood vessels. The method to be used in this research consist of two parts which are the pre-processing part and the feature extraction by using the Kirsch’s template. Combining the pre-processing at the early stage and feature extraction at the next stage is applied to extract the edges of the blood vessels. The proposed algorithm was verified by using two online databases, DRIVE and HRF to validate the performance measures. Hence, proposed method is capable to extract the retina blood vessel and give the accuracy of 0.7917, the sensitivity of 0.9077 and the specificity of 0.7215. In conclusion, the extraction of the blood vessels is highly recommended as the early screening stage for the eye diseases beneficially.

Glaucoma detection of retinal images based on boundary segmentation Noraina Alia Zainudin; Ain Nazari; Mohd Marzuki Mustafa; Wan NurShazwani Wan Zakaria; Nor Surayahani Suriani; Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp377-384

The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed.

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