Wan Khairunizam Wan Ahmad
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Preferred name
Wan Khairunizam Wan Ahmad
Official Name
Wan Khairunizam, Wan Ahmad
Alternative Name
Wan, Khairunizam
Ahmad, Wan Khairunizam Wan
Khairunizam, W. A. N.
Main Affiliation
Scopus Author ID
57200576499
Researcher ID
E-6072-2011

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  • Publication
    An emotion assessment of stroke patients by using bispectrum features of EEG Signals
    ( 2020)
    Choong Wen Yean
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Murugappan Murugappan
    ;
    Yuvaraj Rajamanickam
    ;
    Abdul Hamid Adom
    ;
    Mohammad Iqbal Omar
    ;
    Bong Siao Zheng
    ;
    Ahmad Kadri Junoh
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states. The estimated bispectrum mapped in the contour plots show the different appearance of nonlinearity in the EEG signals for different emotional states. Bispectrum features were extracted from the alpha (8–13) Hz, beta (13–30) Hz and gamma (30–49) Hz bands, respectively. The k-nearest neighbor (KNN) and probabilistic neural network (PNN) classifiers were used to classify the six emotions in LBD, RBD and NC. The bispectrum features showed statistical significance for all three groups. The beta frequency band was the best performing EEG frequency-sub band for emotion classification. The combination of alpha to gamma bands provides the highest classification accuracy in both KNN and PNN classifiers. Sadness emotion records the highest classification, which was 65.37% in LBD, 71.48% in RBD and 75.56% in NC groups.
  • Publication
    Parametric design optimization of an ankle rehabilitation robot using SolidWorks
    ( 2020-12-18)
    Muhammad Nazrin Shah Shahrol Aman
    ;
    Shafriza Nisha Basah
    ;
    Khairul Salleh Basaruddin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Bin Ahmad S.A.
    ;
    Wan Azani Wan Mustafa
    This paper presents the approach to determine most suitable dimensions and volume of the proposed ankle rehabilitation robot design. This design aim is the robot needs to be portable without compromising the workspace of the proposed robot and it must fulfill all required basic ankle motions. To do this, optimisation was used to generate possible initial dimensions in order to achieve suitable length for the outer frame through minimization of the dimensions. Based on the selected variables and constraints, the result of the optimization shows minimization of the proposed design has been achieved through reduction of the dimension of the outer frame of the robot in which translate the reduction of the weight of the robot.
  • Publication
    Path tracking simulation of the buggy car by using Fuzzy information of the steering wheel
    ( 2020-01-01)
    Halin H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Haris H.
    ;
    Zunaidi I.
    ;
    Bakar S.A.
    ;
    Zuradzman Mohamad Razlan
    ;
    Wan Azani Wan Mustafa
    The steering wheel control is the method used for the navigation of an autonomous vehicle. In order to control the autonomous vehicle, the steering wheel controller must be able to adapt as the road condition and surrounding environment can change abruptly. The existed autonomous system currently in the testing phase. The system still needs to improve because there is some report regarding an accident caused by the test autonomous vehicles. The aim of this research is to implement the human driving capability into the Fuzzy controller. One of the human capabilities is the ability to make a decision based on the current situation. The fuzzy system is developed based on human driving data while controlling a buggy car. The experiments used to collect data such as position, speed, heading and steering wheel angle. Data then use to develop the membership function for the fuzzy inputs and output. The simulation is performed in order to study the performance of the Fuzzy controller. The performance of the Fuzzy controller is satisfactory and can be improved. The maximum path tracking error recorded is 9 m and 7.5 m for right and left turn simulations.
  • Publication
    Thermal Management System Analysis Concentrate on Air Forced Cooling for Small Space Compartment and Heat Load
    ( 2021-12-01)
    Yahaya M.N.
    ;
    Ghani A.Z.A.
    ;
    Zuradzman Mohamad Razlan
    ;
    Rahman A.A.
    ;
    Bakar S.A.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Harun A.
    ;
    Hashim M.S.M.
    ;
    Mohd Khairul Faizi Abd Rahman
    ;
    Ishak Ibrahim
    ;
    Kamarrudin N.S.
    Battery thermal management system (BTMS) plays an important thing as to control of the battery thermal behaviours. Recently, most of the manufacturer either in automobile, motorcycle, and electric vehicle (EV) industry are using this application of BTMS for their product. It is because BTMS promising the extend the period and lifespan of the battery and the battery system controlling the temperature distribution and circulation on the system. Lithium-ion battery is one of the common usages in BTMS. Lithium-ion battery promising the goals such as higher performance, better cycle stability, and improved protection are being followed with the selection and engineering of acceptable electrode materials. It also shows a goal for future such as high of the energy storage due to higher energy density by weight among other rechargeable batteries. However, there still have factor that are limiting the performance/application when using lithium-ion as battery thermal management system (BTMS). For example, the performance, cost, life, and protection of the battery. The main reason is therefore important in order to achieve optimum efficiency whenworking under different conditions. Hence, the best range of temperature and the cooling capacity of lithium-ion battery need to evaluate in order to increasing the lifespan of lithium-ion battery at the same time can increasing the performance of the cell. This study found that the higher the velocity of air, the higher the cooling capacity that gain from the surrounding. It also was strongly related to the dry bulb temperature of surrounding air.
  • Publication
    Contrast enhancement approaches on medical microscopic images: a review
    ( 2021-01-01)
    Nahrawi N.
    ;
    Wan Azani Wan Mustafa
    ;
    Siti Nurul Aqmariah Mohd Kanafiah
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Khairunizam Wan Ahmad
    Nowadays, there are many method for medical identification that exist for example based on microscopic and nonmicroscopic. Microscopic is a method that use microscope to capture an image and identify the disease based on the image captured. The image quality of medical image is very important for patient diagnosis. Image with poor contrast and the quality of the image is not good may lead to the mistaken decision, even in experienced hands. Therefore, contrast enhancement methods was proposed in order to enhance the image quality. Contrast enhancement is a process that improves the contrast of an image to make various features more easily perceived. Contrast enhancement is widely used and plays important roles in image processing application. This paper review the contrast enhancement techniques was used in microscopic images. There are microscopic images for cervical cancer, leukemia, malaria, tuberculosis and anemia.
  • Publication
    Development of Driving Simulation Experiment Protocol for the Study of Drivers’ Emotions by using EEG Signal
    ( 2024-06-01)
    Abdul Hafiz Abd Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Saidatul Ardeenawatie Awang
    The Brain-Computer Interface (BCI) is a field of research that studies the EEG signal in order to elevate our understanding of the human brain. The applications of BCI are not limited to the study of the brain wave but also include its applications. The studies of human emotions specific to the vehicle driver are limited and not vastly explored. The EEG signal is used in this study to classify the emotions of drivers. This research aims to study the emotion classifications (surprise, relax/neutral, focus, fear, and nervousness) while driving the simulated vehicle by analyse the EEG signals. The experiments were conducted in 2 conditions, autonomous and manual drive in the simulated environment. In autonomous driving, vehicle control is disabled. While in manual drive, the subjects are able to control the steering angle, acceleration, and brake pedal. During the experiments, the EEG data of the subjects is recorded and then analyzed.
  • Publication
    Blood vessel detection monitoring system and mobile notification for diabetic retinopathy diagnosis
    ( 2020-01-01)
    Mahmud A.S.
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Mohd Al-Hafiz Mohd Nawi
    Disease diagnosis based on retinal image analysis is very popular in order to detect a few critical diseases such as diabetic retinopathy, high blood pressure, cancer and glaucoma. The important part of the retinal is a blood vessel. Besides, the blood vessel study plays an important part in different medical areas such as ophthalmology, oncology, and neurosurgery. The significance of the vessel analysis was helped by the continuous overview in clinical studies of new medical technologies intended for improving the visualization of vessels. In this paper, a new blood vessel detection based on a combination of Kirsch’s templates and Fuzzy C-Means (FCM) was proposed. The main objective of this study is to improve the detection result of FCM and achieved more effective performance compared to the Kirsch’s templates result. The proposed method experimented on 20 images is utilized namely from Digital Retina Images for Vessel Extraction (DRIVE) dataset. The resulting images are compared with the benchmark images based on a few image quality assessment (IQA) such as accuracy, sensitivity and specificity. The total average of accuracy is 92.64%, while sensitivity and specificity obtained was 95.73% and 60.45% respectively. The three parameters of the IQA will then be displayed in a column on the GUI. The second part of the system is for the mobile notification system to send SMS to a mobile phone. In order for the user to obtain the image analysis results, there must be a notification system on the mobile phone. By using the GSM module integrated with Arduino Uno, notification regarding image analysis will be sent to the mobile phone.
  • Publication
    Breast Cancer Detection and Classification on Mammogram Images Using Morphological Approach
    ( 2022-01-01)
    Wan Azani Wan Mustafa
    ;
    Azmi A.A.
    ;
    Mohd Aminudin Jamlos
    ;
    Alquran H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Ismail S.
    ;
    Alkhayyat A.
    ;
    Haron J.
    Breast cancer is one of the most common cancers affecting women worldwide. Mammography is the most well-known and effective method to detect early signs of breast cancer. The purpose of this paper is to detect breast cancer on the mammogram image to classify the disease through morphological techniques. Using conventional methods makes radiology difficult to detect cancer found in the patient's breast. This proposal can be divided into several elements, which are input database, image preprocessing, image segmentation, morphological analysis, and object recognition. First, image preprocessing will be done using the Weiner and Median filters. Second, the thresholding method for image segmentation will be performed, and lastly, morphology will remove imperfections introduced during the image segmentation process. Finally, the image is classified into two classes: normal and cancerous images. A median filter and 0.95 thresholding achieve an accuracy of 93.71%, a sensitivity of 94.36%, and a specificity of 82.53% for the cancerous images.
  • Publication
    Endometrial Cell Images Segmentation: A Comparative Study
    ( 2022-01-01)
    Wan Azani Wan Mustafa
    ;
    Salim N.U.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Ismail S.
    ;
    Alquran H.
    Uterine cancer, also known as endometrial cancer, is a form of cancer that affects the female reproductive system. Nowadays, there are 2 step methods that the physician or health care provider tend to use to diagnose cancer, which is using ultrasound technique and endometrial biopsy. The biopsy procedure is used to extract the cell and sent to the pathologist for histopathological image analysis. The histopathological image analysis is the crucial step in all the procedures because it determines the situation for the patient, whether positive or negative. They are two types of cell images known as high grade squamous intraepithelial lesion (HSIL) and low grade squamous intraepithelial lesion (LSIL). The problem occurs when both LSIL and HSIL are different, needing different medical treatment techniques but showing slighter differences in nucleus size cell histopathological image analysis. Therefore, the pathologist usually requires more time to identify whether it is LSIL or HSIL. Based on the limitation, the paper aims to compare a few popular detection methods, which are the Wolf method, Bernsen method, Otsu method and Feng method. Based on the Image Quality Assessment (IQA), the Wolf method shows good performance compared to the others. In a precise term, this finding could benefit the health care community to reduce the diagnosis time to categorize the cell and lead to early treatment of endometrial cancer.
  • Publication
    Simulation studies of the hybrid human-fuzzy controller for path tracking of an autonomous vehicle
    ( 2021-01-01)
    Halin H.
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Haris H.
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Zunaidi I.
    ;
    Wan Azani Wan Mustafa
    Human intelligence and experience help them in making a decision and recognize a pattern. This ability enables the driver to take action even in an unexpected situation. The hybrid integration between human intelligence/experience and machine controller able to improve the autonomous vehicle path tracking capability. The path tracking capability is the main concern of the autonomous vehicle. The Fuzzy developed from the experiment’s data. The experiments (human navigation experiments) used to gather the appropriate data from humans while controlling the buggy car. Data then use to develop the membership functions for inputs and output of the Fuzzy controller. The simulation uses to study the performance of the Fuzzy controller. The recorded path tracking error from the simulations for the right and left turn maneuver is 9 m and 7.5 m, respectively.