Wan Azani Wan Mustafa
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Preferred name
Wan Azani Wan Mustafa
Official Name
Wan Azani, Wan Mustafa
Alternative Name
Mustafa, W.
Azani Mustafa, Wan
Mustaffa, Wan Azani
Wan Mustafa, Wan Azani
Main Affiliation
Scopus Author ID
57219421621
Researcher ID
J-4603-2014

Research Output
Now showing 1 - 3 of 3
  • Publication
    PPG Segmentation Using Deep Learning
    (IEEE, 2023)
    Mohammad Tabbakha
    ;
    Hassan Al Masri
    ;
    Abdullatif Hammad
    ;
    Mohammed Alsulatie
    ;
    Hiam Alquran
    ;
    Wan Azani Wan Mustafa
    ;
    Muntather Almusawi
    ;
    Abbas Hameed Abdul Hussein
    As an indicator regarding cardiovascular health, vascular dynamics, and more, Photoplethysmography (PPG) consists of a baseline with two pulsatile peaks that reflect the blood flow variations. In the absence of critical studies and a precise understanding of PPG signal this study proposes a deep learning approach to predict and define each phase of PPG waveform utilizing Gated recurrent unit (GRU) due to its optimal performance in the short-term dependencies in sequences, the model is composed mainly of GRU layer with 20 hidden units applying tanh and sigmoid activation function, followed by dropout layer and a fully connected layer, afterward a softmax layer was added, we conducted our study on a dataset combined of an accessible Bed-Based Ballistocardiography Dataset (BBB), after that, the data was manually labeled. Following up, hyperparameters such as learning rate, batch size, and other parameters were adjusted after numerous trials, which resulted in test accuracy, precision, and recall of 0.875, 0.892, and 0.854, respectively in the used dataset. These promising results might be the first step of more future investigations concerning PPG.
  • Publication
    Unveiling The Digital Realm: A Systematic Review on Regulating Blockchain for Online Breast Milk Services
    ( 2023)
    Amirah ‘Aisha Badrul Hisham
    ;
    Nor Ashikin Mohamed Yusof
    ;
    Zilal Shaari
    ;
    Hafiza Abas
    ;
    Shazana Mustapa
    ;
    Syakirah Zahar
    ;
    Wan Rusydiah Salehudin
    ;
    Syamilah Saliman
    ;
    Muntather Almusawi
    ;
    Wan Azani Wan Mustafa
    ;
    Farah Norwahidah Mohd Yunus
    The traditional or modern practice of sharing breastmilk raises concern regarding security, traceability, safety, and quality assurance. This systematic review explores the application of blockchain technology in addressing these issues, aiming to enhance the security and efficiency of breastmilk sharing in healthcare settings. This systematic review delves into the burgeoning intersection of blockchain technology and online breast milk services, exploring the multifaceted landscape encompassing healthcare data management, privacy, safety, security, quality assurance, governance, interoperability, and legal and regulatory challenges. Employing a comprehensive research methodology, we conducted an extensive review of scholarly articles of Scopus, Web of Science and PubMed databases using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique. The final main data is n = 26 and analyzed using synthesis approach. Four main themes were generated: (i) blockchain for healthcare data management, (ii) privacy of data, safety, security, and quality assurance for donated breastmilk, (iii) governance and interoperability, (iv) legal and regulatory challenges. This systematic review highlighted the vast potential, capabilities, opportunities, and challenges of using blockchain for a noble cause of sharing or donating breastmilk. The inputs are useful for policymakers, healthcare professionals, and researchers in fostering an introducing better policy, policy interventions and legal mechanisms for a better, secure, transparent, and ethical digital ecosystem in maternal and child healthcare.
      4  15
  • Publication
    Women's Health Diary: Tracker System for Menstruation, Intermenstrual, Ovulation, and Postnatal Bleeding Using Rules-Based Technique
    ( 2023)
    Nursyuhada binti Abdullah
    ;
    Azwa bin Abdul Aziz
    ;
    Wan Azani Wan Mustafa
    ;
    Muntather Almusawi
    ;
    Abbas Hameed Abdul Hussein
    Menstruation, a natural physiological process in women, entails regular vaginal bleeding as part of the monthly menstrual cycle. While existing systems facilitate menstrual cycle tracking, they often lack the capability to differentiate between various types of vaginal bleeding, such as menstruation (haid), intermenstrual bleeding (istihadah), or postnatal bleeding (nifas). To address this limitation, the Women's Health Diary: Tracker System for Menstruation, Intermenstrual, Ovulation, and Postnatal Bleeding) was developed using a rule-based technique. This system employs an iterative method comprising eight phases: initial planning, planning, requirements, analysis and design, implementation, testing, evaluation, and deployment. By ensuring the optimal development and performance of this system, women can effectively manage their menstrual blood, a vital aspect of their overall health. Moreover, this system holds particular significance for every women, as it facilitates tracking and identification of regular and irregular cycles, enabling them to uphold the legitimacy of their worship.
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