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Dr. Mas Sahidayana Mohktar
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Representative Publications
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Journal Article
Sami F KhalilMMMas Sahidayana Mohktar
Mas Sahidayana MohktarFIFatimah Ibrahim
Fatimah IbrahimBioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in body composition estimation and evaluation of clinical status. This paper reviews the main concepts of bioimpedance measurement techniques including the frequency based, the allocation based, bioimpedance vector analysis and the real time bioimpedance analysis systems. Commonly used prediction equations for body composition assessment and influence of anthropometric measurements, gender, ethnic groups, postures, measurements protocols and electrode artifacts in estimated values are also discussed. In addition, this paper also contributes to the deliberations of bioimpedance analysis assessment of abnormal loss in lean body mass and unbalanced shift in body fluids and to the summary of diagnostic usage in different kinds of conditions such as cardiac, pulmonary, renal, and neural and infection diseases.
Journal Article
MHMohammad Ashfak Habib
Mohammad Ashfak HabibMMMas Sahidayana Mohktar
Mas Sahidayana MohktarSKShahrul Bahyah Kamaruzzaman
Shahrul Bahyah KamaruzzamanKLKheng Seang Lim
Kheng Seang LimMTMaw Pin Tan
Maw Pin TanFIFatimah Ibrahim
Fatimah IbrahimThis paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers’ interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems.
1 January 2015 in Artificial Intelligence in Medicine
Journal Article
MMMas Sahidayana Mohktar
Mas Sahidayana MohktarSRStephen Redmond
Stephen RedmondNANick C. Antoniades
Nick C. AntoniadesPRPeter D. Rochford
Peter D. RochfordJPJeffrey J. Pretto
Jeffrey J. PrettoCMChristine McDonald
Christine McDonald +2
Journal Article
SUShah Mukim Uddin
Shah Mukim UddinFIFatimah Ibrahim
Fatimah IbrahimASAbkar Ahmed Sayad
Abkar Ahmed SayadATAung Thiha
Aung ThihaKPKoh Xiu Pei
Koh Xiu PeiKTKwai Lin Thong
Kwai Lin Thong +3
In recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP) on a microfluidic compact disk platform. The developed detection system utilizes a monochromatic ultraviolet (UV) emitter for excitation of fluorescent labeled LAMP amplicons and a color sensor to detect the emitted florescence from target. Then it processes the sensor output and displays the detection results on liquid crystal display (LCD). The sensitivity test has been performed with detection limit up to 2.5 × 10−3 ng/µL with different DNA concentrations of Salmonella bacteria. This system allows a rapid and automatic endpoint detection which could lead to the development of a point-of-care diagnosis device for foodborne pathogens detection in a resource-limited environment.
1 January 2013 in Medical Science Monitor
Journal Article
SOSiti Zawiah Omar
Siti Zawiah Omar
MMMas Sahidayana Mohktar
Mas Sahidayana MohktarFIFatimah Ibrahim
Fatimah IbrahimNRNur Farahana Mohd Rozi
Nur Farahana Mohd Rozi
JYJuhaida Mohd Yusof
Juhaida Mohd Yusof
KYKhong Su Yen
Khong Su Yen
+1
Background:Currently, the reference standard used to clinically assess sexual function among women is a qualitative questionnaire. Hence, a generalised and quantitative measurement tool needs to be available as an alternative. This study investigated...
Journal Article
Mohamed Osman BaloolaFIFatimah Ibrahim
Fatimah IbrahimMMMas Sahidayana Mohktar
Mas Sahidayana MohktarThis paper presents an optimization of the medication delivery drone with the Internet of Things (IoT)-Guidance Landing System based on direction and intensity of light. The IoT-GLS was incorporated into the system to assist the drone’s operator or autonomous system to select the best landing angles for landing. The landing selection was based on the direction and intensity of the light. The medication delivery drone system was developed using an Arduino Uno microcontroller board, ESP32 DevKitC V4 board, multiple sensors, and IoT mobile apps to optimize face detection. This system can detect and compare real-time light intensity from all directions. The results showed that the IoT-GLS has improved the distance of detection by 192% in a dark environment and exhibited an improvement in face detection distance up to 147 cm in a room with low light intensity. Furthermore, a significant correlation was found between face recognition’s detection distance, light source direction, light intensity, and light color (p < 0.05). The findings of an optimal efficiency of facial recognition for medication delivery was achieved due to the ability of the IoT-GLS to select the best angle of landing based on the light direction and intensity.
About Me
Mas S. Mohktar (M’87) received her BBMedEng (Hons) from University of Malaya and the Meng (BMed), from University of Malaya. She obtained her PhD from University of New South Wales, Australia. She has served as the Head of Universiti Malaya Science Technology Engineering Mathematics (STEM) Centre since 2018. She is very much involved with various Science, Technology, Engineering and Mathematics (STEM) projects. She is the coordinator for the My STEM Ambassador Program under the Ministry of Higher Education, MOSTI STEM Mentor–Mentee, and STEM Mini Theater under the National STEM Association and coordinator for Samsung Solve for Tomorrow Competition. She is also one of the evaluators for the Biomedical Engineering Program under the Engineering Accreditation Council. Her research areas of interest are STEM Integrated Projects and Decision Support System. She was awarded for her STEM studies: she has received Selangor First Place and Overall Winner, Selangor State Government, 2019; Gold Award PECIPTA, 2019; Ministry of Education, Malaysia, 2019; (National) ITEX 2018 Gold Medal; Malaysian Invention and Design Society, 2018; Best Award MTE 2018; Malaysian Association of Research Scientist, 2018; Gold Award MTE 2018; and Malaysian Association of Research Scientist, 2018.