Journal of Human Centered Technology
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description: Author Guidelines Journal of Human Centered Technology (HumEnTech) is an open-access international journal, covering new insight in science and technology related to analysis and application on human. HumEnTech provides a peer-reviewed forum for the publication of research and review articles which encompasses new methods/innovative practices, new discoveries, latest research findings, critical evaluations and critical surveys on human related subjects/topics. The journal welcomes contribution from the following research areas but not limited to: Human-computer interaction Assistive technology Sport technology Rehabilitation Health informatics Human-systems integration Nutritional technology Artificial intelligence for human technology Ergonomics Artificial organs Medical instrumentation & system Technology for Flexible Learning more Information on article submission are available at the Author Guidelines. All authors are required to read the Publication Ethics and the Privacy Statement prior an article submission. Indexed by: MyJurnal Indexed by: MyCite
publisher: Penerbit UTM Press
language: en
publication name: Journal of Human Centered Technology
issn: 2821-3467
items: Human-Centered Design and Evaluation of a Gamified 2D Animation with Visual Effects for Environmental Awareness
items: Integrating RNLE and REBA to Evaluate Manual Handling Risks among Semiconductor Technicians
items: Ergonomics and Psychosocial Predictors of Work-Related Musculoskeletal Disorders among Nursing Professionals
items: Preliminary Modelling of Accident and Near Miss Risk Factors Among Gig Delivery Workers in Malaysia
items: Incorporating Anthropometric Measurement and Pressure Distribution Assessment in Car Seat for Fatigue Management: An Exploratory Ergonomic Analysis
items: Sperm Detection Based on You Only Look Once-Neural Architecture Search (YOLO-NAS)
items: Validity and Reliability of the Commuting Safety Management Practices Questionnaire
items: Development and Optimization of Wearable Sensors for Vital Signs Monitoring Using the Internet of Things
items: SmartResume: A Resume Parser Application using Natural Language Processing
items: Honey Hydrogel Patch Assisted by Ultraviolet Exposure: Characterization and Adhesion Analyses
items: Design and Implementation of IoT-Based Remote Vital Sign Monitoring System
items: Effects of Intermittent Fasting on Body Compositions Using Bioimpedance Analyzers
items: Vision Based Screening of Children with Autism Spectrum Disorders Via Deep Learning Approach
items: Development of Mobile and Real-Time Vital Signs Monitoring System with Camera Integration
items: Image Colour Correction of Smartphone-based Imaging Devices for Medical Application: A Literature Review
items: Adapting The Bruininks-Oseretsky Test of Motor Proficiency (BOT-2) for Young Athletes
items: An UX Evaluation Framework for Islamic Design and Content-Based Digital Therapeutics for Mental Health: A Proposed Approach
items: Extensive Review on Humidity and Moisture on Skin Device Analysis
items: Online Platform for Home-Based Medical Device Lifecycle Management: A User-Centric Approach
items: Eating Disorder Biomarkers: Macronutrient Regulation of Ghrelin and Leptin
items: Advanced Human-Centered Food Quality Assessment: Second Derivative Linear Prediction of Raw Broiler Shear Force Using Near-Infrared Spectroscopy
items: Strain Gauge Sensors in Industrial Instrumentation: A Review for Human Technology Integration
items: Innovative Approaches to Gas Sensing: Bridging Theory and Human Applications
items: K-Nearest Neighbor-Based Detection of Chokanan Mango Maturity for Agricultural Technology Applications
items: Nutritional Characterization of Moringa oleifera as a Potential Equine Feed and Human Application
items: In-vitro Biocompatibility Analyses on Co-electrospun of Polyurethane/Chitosan and Polyvinyl Alcohol/Elastin Vascular Membrane
items: Review on Fundamental of Electroencephalography and Detection Techniques in Substance and Behavioral Addiction
items: Cyborg Technology in Bio Engineering: Enabling Technologies, Implications, Applications and Future Trends
items: Research on Capture the Flag Exercises for Cybersecurity Skill Training Among Malaysian Undergraduates
items: Digital Immersion in Melaka: Enhancing Historical Learning through Technology on the Malaccan Sultanate

Human-Centered Design and Evaluation of a Gamified 2D Animation with Visual Effects for Environmental Awareness
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description: This study examines a human-centered approach to design and evaluate a gamified two dimensional (2D) animation enhanced with dynamic visual effects (VFX) for promoting environmental awareness. Framed within the domain of Human–Computer Interaction (HCI), the research explores how visual design, narrative structure, and embedded gamification elements influence user engagement, usability, and perceived behavioural intention. The development process followed the Multimedia Development Life Cycle (MDLC), integrating core serious game elements such as goal framing, narrative conflict, feedback cues, and reward visualisation into the animated storyline. A mixed-method evaluation was conducted with participants from diverse age groups, including adolescents and adults, combining post-exposure quantitative surveys and qualitative feedback to assess four dimensions: knowledge acquisition, technical readiness and media familiarity, visual and design appeal, and perceived impact. The results indicate strong perceived performance in technical readiness (M = 4.32) and visual engagement (M = 3.94), alongside increased awareness of littering issues (M = 3.87). However, perceived motivation to take direct anti-littering action remained moderate (M = 3.60), highlighting the challenge of translating awareness into behavioural intention. Overall, the findings suggest that gamified 2D animation with dynamic VFX can serve as an effective human-centered communication tool for environmental awareness by fostering engagement and perceived attitudinal influence. The results are interpreted as self-reported perceived impact rather than direct measurement of behavioural change, indicating the need for future studies employing longitudinal or experimental designs to examine actual behavioural outcomes.
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creator: Hamzah Asyrani Sulaiman
creator: A. Z. Labra
creator: Abdullah Bade
creator: Iznora Aini Zolkifly
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 70
ending page: 78
doi: 10.11113/humentech.v5n1.121

Integrating RNLE and REBA to Evaluate Manual Handling Risks among Semiconductor Technicians
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description: Manual handling of wafer pods persists in semiconductor fabrication despite high levels of automation, exposing technicians to work-related musculoskeletal disorders (WMSDs). This case study evaluated ergonomic risks associated with lift-and-load wafer pod tasks in the Fab Integration Department of a semiconductor facility in northern Malaysia. Eight technicians performing routine transfers from upper and lower trolley levels to tool loading ports were assessed using direct observation, task analysis, and physical measurements. Lifting demands were quantified using the Revised NIOSH Lifting Equation (RNLE) to determine the Recommended Weight Limit (RWL) and Lifting Index (LI), while postural risk was evaluated using the Rapid Entire Body Assessment (REBA). RNLE analysis showed LI values ranging from 1.01 to 2.00, indicating increased to high lifting risk, particularly for lower trolley tasks. Excessive horizontal reach and asymmetric trunk rotation were identified as the main contributors, reflected by reductions in the Horizontal Multiplier (HM) and Asymmetry Multiplier (AM). Postural assessment revealed high REBA risk levels (scores 6–8) associated with trunk flexion, neck extension, and asymmetric lifting. Based on these findings, targeted ergonomic interventions were proposed, including limiting twisting angles, maintaining safe horizontal reach distances, adopting squatting techniques for low-level lifting, and providing ergonomics training. The integrated RNLE–REBA approach offers a practical framework for identifying high-risk manual handling tasks in semiconductor manufacturing. Future research should extend this assessment to other departments and evaluate digital ergonomic monitoring tools for continuous risk management.
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creator: Asuvani Nadarajan
creator: Nooraizedfiza Zainon
creator: Muhammad Syahril Bahari
creator: Norashiken Othman
creator: Marina Marzuki
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 62
ending page: 69
doi: 10.11113/humentech.v5n1.129

Ergonomics and Psychosocial Predictors of Work-Related Musculoskeletal Disorders among Nursing Professionals
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description: Work-related musculoskeletal disorders (WMSDs) are common occupational health issues among nurses resulting from the combined effects of physically demanding tasks and psychosocial pressures. These conditions lead to reduced productivity, increased absenteeism, and strain on healthcare systems. This study aimed to determine the prevalence of WMSDs among nurses in a teaching hospital and to examine demographic, ergonomic, and psychosocial factors associated with their occurrence. A cross-sectional survey was conducted among 45 registered nurses recruited from various wards of a tertiary teaching hospital. Data were collected using a structured self-administered questionnaire, which included the Nordic Musculoskeletal Questionnaire (NMQ) and measures of demographic, ergonomic, and psychosocial variables. Descriptive statistics were applied to summarize characteristics and prevalence, while binary logistic regression was used to identify significant predictors. More than half of the respondents reported WMSDs in the past 12 months, with the ankles/feet (35.6%), neck (33.3%), and lower back (31.1%) most frequently affected. Significant predictors included female (AOR = 6.48, 95% CI: 1.07–39.23), being married (AOR = 5.11, 95% CI: 1.07–24.40), having children (AOR = 5.58, 95% CI: 1.20–25.83), heavy lifting without assistance (AOR = 6.36, 95% CI: 1.31–32.80), high workload (AOR = 5.01, 95% CI: 1.17–21.42), and low supervisory support (AOR = 4.72, 95% CI: 1.04–21.36).In conclusion, WMSDs among nurses are influenced by overlapping personal, ergonomic, and psychosocial risks. Integrated prevention strategies combining ergonomic interventions, such as assistive devices and safe patient-handling, with organizational measures, including workload management, adequate staffing, and supportive supervision, are essential to safeguard nurses’ health and maintain healthcare system resilience. This study contributes novel evidence by integrating both ergonomic and psychosocial predict…
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creator: Nurul Izzah Abdul Samad
creator: Nurfadzlina Deruis
creator: Nurhidayah Sabri
creator: Nursuhaili Mohd Amin
creator: Nurul Atikah Che Hasan
creator: Nurul Ainun Hamzah
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 30
ending page: 37
doi: 10.11113/humentech.v5n1.124

Preliminary Modelling of Accident and Near Miss Risk Factors Among Gig Delivery Workers in Malaysia
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description: This study explores the risk factors of accidents and near misses among gig delivery motorcyclists in Klang Valley, Malaysia. Using a customized questionnaire, this cross-sectional study collected 235 responses through closed Facebook groups. Sociotechnical aspects such as Rider Behaviour (RB), Rider Safety Awareness (RA), Work Conditions (WC), Environmental Factors (EF), Motorcycle Design and Safety (MDS), and Platform Safety Management (PSM) have been evaluated using an initial 74-item questionnaire. The Partial Least Squares Structural Equation Modelling (PLS-SEM) was utilized resulting a final model with 56 items. The study outcomes have good validity and reliability with Cronbach’s alpha between 0.67 and 0.95, Average Variance Extracted (AVE) > 0.50, and Composite Reliability (CR) > 0.80. Path analysis identified WC (β = -0.337, p < 0.001) and ORU (β = 0.198, p = 0.003) as critical predictors for accident. MDS (β = 0.177, p = 0.026), EF (β = 0.175, p = 0.009), and PSM (β = -0.207, p = 0.001) were significant predictors of near misses. By combining Sociotechnical System Theory and Multiple Causation Theory, the findings showed the complex relationship of various factors in gig delivery workers’ safety. Immediate reforms in platform policies, better road infrastructure, improved motorcycle safety design, and enhancing road users’ safety awareness are much needed. This research contributes to the limited literature on gig worker safety in Malaysia and provides a foundation for future studies and policy recommendations.
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creator: Syiikhah Abd Rahman
creator: Rozlina Md Sirat
creator: Jafri Mohd Rohani
creator: Mohd Firdaus Mohd Taib
creator: Kuan Yew Wong
creator: Mohamed Zul Fadhli Khairuddin
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 55
ending page: 61
doi: 10.11113/humentech.v5n1.125

Incorporating Anthropometric Measurement and Pressure Distribution Assessment in Car Seat for Fatigue Management: An Exploratory Ergonomic Analysis
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description: An ergonomically designed driver's seat is essential for assuring quality, comfort, and safe driving. Comprehending the influence of anthropometric characteristics on seat-body contact can facilitate the development of comfort-optimized seating systems. This exploratory study examined the relationship between anthropometric dimensions and pressure distribution patterns in drivers deployed within a simulated driving environment. A pressure mapping system (Tactilus®, SPI, USA) was used to capture seat pan pressure profiles, while key anthropometric variables were recorded using an anthropometer. Eleven participants completed the driving posture protocol, and multiple regression analysis was applied to model pressure distribution outcomes. Results revealed a strong, statistically significant positive relationship between buttock-popliteal length and pre-buttock pressure (r = 0.914, p<0.01), with the regression model explaining 81.8% of the variance in pre-buttock pressure. The results emphasize buttock-popliteal length as an important indicator of localized seat pressure, underscoring the necessity for seat designs that accommodate variations in thigh length. These findings establish an ergonomic foundation for incorporating anthropometric-pressure mapping assessments into the development of proactive driver assistance systems, aimed at preventing fatigue occurrences.
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creator: Nor Kamaliana Khamis
creator: Mohd Faizal Mat Tahir
creator: Mohd Zaki Nuawi
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 38
ending page: 44
doi: 10.11113/humentech.v5n1.123

Sperm Detection Based on You Only Look Once-Neural Architecture Search (YOLO-NAS)
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description: Computer-Aided Sperm Analysis (CASA) systems are vital for male reproductive diagnostics. However, the CASA systems are prone with detection challenges. Therefore, this study explores You Only Look Once-Neural Architecture Search (YOLO-NAS) for precise, rapid sperm analysis, addressing its underexplored efficacy in this domain. Using the Sperm Videos and Images Analysis (SVIA) dataset (3,590 images, 125,000 objects), XML annotations were converted to YOLO TXT format. YOLO-NAS models (S, M, L) were trained for 40 epochs on Google Colab Pro using AdamW, batch size 32, and learning rates 0.002 (initial 0.0005). The performance was evaluated using mAP@0.50, Recall@0.50, Precision@0.50, and F1 Score@0.50, with an IoU threshold of 50%. The YOLO-NAS-L was most effective for sperm/impurity detection, achieving 0.8163 mAP@0.50 and 0.8203 precision@0.50. Increased model complexity enhances feature extraction, especially for small objects while higher precision may decrease recall. From the outputs, this study has successfully developed and evaluated a YOLO-NAS model for sperm detection. Future works include more epochs, diverse datasets, and offline training in sperm clustering, as well morphology and motility analyses.
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creator: Aleeyah Nur Sabrina Dzuren
creator: Muhammad Amir As'ari
rights: Copyright (c) 2026 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 45
ending page: 54
doi: 10.11113/humentech.v5n1.116

Validity and Reliability of the Commuting Safety Management Practices Questionnaire
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description: Commuting accidents are a major contributor to worker fatalities and economic losses in Malaysia. Despite the seriousness of this issue, many organizations lack structured approaches to manage commuting risks. This study aimed to develop and evaluate the validation and reliability of the Commuting Safety Management Practices Questionnaire (CoSMaP-Q), an instrument designed to assess organizational practices in commuting safety. Content validation was carried out using a two-round modified Delphi method involved five road safety experts. In the first round, seven items with Content Validity Index (CVI) scores below 1.0 were revised, removed, or reclassified based on expert input. Five additional items were refined for clarity, one new item was added, and a new domain, “Continual Improvement,” was introduced. In the second round, the revised 28-item questionnaire achieved full consensus, with I-CVI, S-CVI/Ave, and S-CVI/UA scores of 1.00. To assess reliability, a pilot test was conducted with 30 organizations, resulted in an overall Cronbach’s Alpha value of 0.74, indicating acceptable internal consistency for the 28-item instrument. In conclusion, the CoSMaP-Q demonstrates strong content validity and acceptable reliability, offering a practical tool for assessing how organizations manage commuting safety. Its application includes evaluating the efficacy of pre- and post-intervention programs and establishing a foundation for future research in commuting safety management.
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creator: Mohd Hafzi Md Isa
creator: Harun Bakar
creator: Ahmad Khushairy Makhtar
creator: Wan Mazlina Wan Mohamed
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 8
ending page: 14
doi: 10.11113/humentech.v5n1.122

Development and Optimization of Wearable Sensors for Vital Signs Monitoring Using the Internet of Things
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description: As the global elderly population grows, there is an increasing need for reliable and easy to use health monitoring tools that support independent living and reduce strain on healthcare system. This study presents the development of a wearable, Internet of Things (IoT) enabled device designed to monitor vital signs and environmental conditions in real time. The system integrated two low-cost sensors: the MAX30100 for tracking blood oxygen saturation (SpO₂) and heart rate, and the BME680 for measuring temperature, humidity, gas resistance (for VOCs), and air pressure. These sensors were connected to ESP8266 microcontroller that transmitted data through Wi-Fi to a mobile dashboard using the Blynk platform. To improve accuracy, especially during motion, signal processing techniques such as a moving average filter were implemented. The device was tested against commercial health monitoring tools and demonstrated strong performance, with an average error of ±2% for SpO₂ and ±5 BPM for heart rate. It also included threshold-based alerts to notify users or caregivers when readings exceed safe limits. This study contributes to the advancement of affordable, remote health monitoring systems by offering a practical solution that combines physiological and environmental sensing in a compact, user-friendly design. Its potential applications include elderly home care, telehealth services, and mobile health clinics.
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creator: Abusnina M. Mukhtar
creator: Mohd Riduan Mohamad
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 21
ending page: 29
doi: 10.11113/humentech.v5n1.119

SmartResume: A Resume Parser Application using Natural Language Processing
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description: In today’s dynamic business environment, Information and Communication Technology (ICT) serves as a pivotal force driving innovation, particularly in human resource management. One notable advancement is the emergence of smart resume applications, which are reshaping traditional recruitment practices. These systems utilize advanced technologies such as artificial intelligence (AI), machine learning, and natural language processing (NLP) to facilitate the automation of resume screening and candidate evaluation processes. This paper presents the development of an Automated Resume Parsing designed to reduce the operational load on human resource professionals. By utilizing NLP techniques, the system extracts key candidate information including name, contact details, educational background, and skills from the resume documents. A custom Named Entity Recognition (NER) model is employed to enhance the accuracy and relevance of extracted data. The model was trained using the SpaCy NLP framework to achieve an overall accuracy of 92.4% and an F1-score of 0.90. The extracted data are presented through an interactive web interface for HR personnel, enabling structured and efficient review of applicant information. The results demonstrate that integrating NLP and machine learning in recruitment systems can significantly enhance automation, consistency, and fairness in candidate evaluation processes. The system's effectiveness was demonstrated through successful extraction and structured presentation of applicant information, aligned with organizational hiring criteria. Beyond technical functionality, this study highlights the potential of such human-centered technologies to enhance decision-making, increase recruitment efficiency, and transform the recruiter-applicant interaction by fostering transparency and fairness in the hiring process.
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creator: Muhammad Alif Imran Mohammad Fadzir
creator: Shakirah Hashim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 15
ending page: 20
doi: 10.11113/humentech.v5n1.118

Honey Hydrogel Patch Assisted by Ultraviolet Exposure: Characterization and Adhesion Analyses
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description: Wound treatment is one of the challenging issues, faced in healthcare despite the development of various advanced technologies. Hydrogels are known to be used in wound treatment and received a lot of attention in the biomedical field due to its ability to store and absorb a significant amount of water which is advantageous for wound healing. The incorporation of honey within the hydrogel increases the resistance towards bacterial infection and induce advanced cell proliferation. However, the fragile structure of honey hydrogel has limited its placement on wounds. The utilization of ultraviolet (UV) light to harden the physical properties of honey hydrogels able to improve and assist the formation of honey hydrogel patches. Therefore, this study aimed to fabricate honey hydrogel patches through UV exposure and evaluate the physio-chemical properties and mucous adhesion strength of the hydrogel patches. The stingless bee honey was incorporated into the matrix of cellulose hydrogel, followed by the exposure of 365 nm UV light at different distances of 1, 2 and 6 cm. The morphology of the hydrogel patches at 1 cm UV exposure was observed to be flatten and possessed more regular structure compared to the other variation of hydrogel patches. The most hydrophilic surface (26.1 ± 0.8)˚ and the greatest ultimate strength (0.52 ± 0.3´10-3 kPa) were also recorded on the similar sample. Therefore, at a shorter UV light exposure distance, distinct hydrogel patches with greater adhesion capability were fabricated for the use in wound healing management.
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creator: Belal Yahya Hussein Al-Tam
creator: Rathosivan Gopal
creator: Le Ee Ling
creator: Syafiqah Saidin
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2026-02-06
publication date: 2026-02-06
starting page: 1
ending page: 7
doi: 10.11113/humentech.v5n1.117

Design and Implementation of IoT-Based Remote Vital Sign Monitoring System
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description: The ability to save data on physiological parameters in a database has become more important in modern healthcare since it paves the way for analysis, enabling long-term patient monitoring, personalized medication, remote patient monitoring, and collaborative medical decision-making. This study presents the development of an online monitoring system that able to remotely monitor the patient at any time via web server. Using internet of things (IoT) technology, it is possible to develop an online patient monitoring system that read parameters, transmit data to database, store data, and display data. The system utilized the ESP32 microcontroller to collect physiological parameters through various sensors. The sensors for each parameter were selected: AD8232 was used for the Electrocardiogram (ECG), GY-MAX30100 was used for the Heart Rate and Blood Oxygen Saturation (SpO2), and MLX90614 was used for the body temperature. In addition, Google Firebase was adopted as the Web Server for this system, along with the implementation of statistical method. The accuracy test was then performed to check the accuracy of the reading. The physiological data were collected and monitored where the developed device was able to display the collected data in a connection with the database. The development of an online patient monitoring system using IoT technology enables remote monitoring, accurate data storage, and analysis of physiological parameters, leading to improved healthcare outcomes and reduced workload for medical professionals.
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creator: Muhammad Nor Luqman
creator: Mohd Riduan Mohamad
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 155
ending page: 165
doi: 10.11113/humentech.v4n2.113

Effects of Intermittent Fasting on Body Compositions Using Bioimpedance Analyzers
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description: Advancements in bioimpedance technology have enabled convenient tools such as smart scales for monitoring body composition. This study aimed to evaluate the accuracy of bioimpedance analyses using two types of bioimpedance analyzers (BIAs) during alternate day fasting (ADF). In this study, Bioimpedance Analyzer 450 (a professional-grade device) and the Mi Body Composition Scale (a consumer-grade device) were used to assess changes during a four-week ADF intervention. Six healthy participants, aged 20–30 years underwent ADF: Alternating between 500 kcal intake on fasting days and unrestricted eating on non-fasting days. Body fat percentage, lean mass, and total body water were measured before and after the intervention using both devices. The results showed no statistically significant changes across all parameters (p>0.05); however, the Biodynamics Analyzer detected +0.56% increment in the body fat and −0.56% decrement in the lean mass. While the Mi Scale showed −0.16% changed in the body fat and +0.13% in the lean mass. These discrepancies highlight the higher sensitivity of the professional-grade BIA in capturing subtle physiological changes. The total body water remained stable in both groups. The results suggest that although consumer-grade devices offer accessibility, they may lack the precision needed for detecting minor shifts during dietary interventions. This study emphasizes the importance of using validated tools in clinical and research settings. It also provides preliminary insights into the metabolic effects of ADF, including possible compensatory eating behavior on non-fasting days and minor fluid shifts. These findings underscore the limitations of consumer-grade BIAs in scientific monitoring and support further research to validate their use in long-term health tracking.
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creator: Nurul Diyana Zainal
creator: Mohd Riduan Mohamad
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 172
ending page: 177
doi: 10.11113/humentech.v4n2.112

Vision Based Screening of Children with Autism Spectrum Disorders Via Deep Learning Approach
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description: Researchers have discerned unique facial characteristics in children with autism, leading to the application of face recognition methods for early diagnosis. Notwithstanding the efficacy of deep learning (DL) models in image classification, issues such as overfitting and limited training datasets continue to exist. This research intends to develop a Convolutional Neural Network (CNN) Deep Learning model for the detection of faces of children with autism. The study employed the Kaggle Autistic Children Facial Dataset to create CNN models through transfer learning, utilizing MobileNet, GoogleNet, and VGG-16. Their performance was assessed using measurements of accuracy, sensitivity, and specificity. The results indicated that MobileNet attained the superior overall performance with accuracy of 0.94, sensitivity of 0.97, and specificity of 0.90, exhibiting robust generalization capabilities. Nonetheless, limits including dataset size and resource limitations were recognized, indicating that future research should prioritize the augmentation of the dataset and the utilization of cloud computing resources for enhanced model training efficiency.
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creator: Atiqah Alias
creator: Muhammad Amir As'ari
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 148
ending page: 154
doi: 10.11113/humentech.v4n2.114

Development of Mobile and Real-Time Vital Signs Monitoring System with Camera Integration
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description: Pre-hospital and emergency department staff play important roles to treat patients where these two departments are correlated to each other. However, there are few misalignments between them such as dissimilar training and clinical abilities, language barriers, and high-risk clinical environments which are characterized by noise, interruption, and time restriction. The objective of this study was to develop an Internet of Things (IoT) based health monitoring system with real-time camera inside an ambulance. With this system, the emergency department can monitor the current patient’s condition in an ambulance while measuring data when paramedics are having difficulties. In conducting the study, the IoT health monitoring system was developed by using ESP32 as the main microprocessor. Few sensors were used including DS18B20, MAX30102, and ESP32-CAM. In addition, the Blynk application was used as the IoT and connected through Wi-Fi, provided by the ESP32. Five respondents were assigned for the data measurement of vital signs specifically heart rate, body temperature, and SpO2 using both standard and proposed monitoring system to calculate average and percentage error. From the results, the percentage error for heart rate was recorded as 21.56 ± 8.40%, body temperature was measured as 3.14 ± 3.41%, and SpO₂ was recorded as 2.13 ± 0.87%. Moreover, during the device construction, the camera functional was delayed for approximately 5 second. In conclusion, integrating real-time video with vital sign data in IoT-based health monitoring systems provides a comprehensive view of a patient's condition, enabling proactive treatment adjustments and better outcomes.
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creator: Muhammad Ikmal Danish Azemi
creator: Mohd Riduan Mohamad
creator: Muhammad Harist Danish Md Rajuna
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 166
ending page: 171
doi: 10.11113/humentech.v4n2.111

Image Colour Correction of Smartphone-based Imaging Devices for Medical Application: A Literature Review
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description: Smartphone technology has revolutionised the field of digital imaging, especially in healthcare and medical applications. Smartphones equipped with built-in high-resolution imaging capabilities, smartphone-based imaging devices have become cost-effective and powerful tools for health monitoring and diagnosis. However, the colour information of the images captured by different smartphone models varies from one to another, which introduces the colour distortion. These colour distortions may negatively impact image interpretation, diagnosis accuracy, and subsequent deep learning based medical analysis. In this context, the field of colour constancy algorithms has become extremely important in providing accurate and consistent colour representation in digital images. Colour constancy has gained significant scientific interest in the last two decades due to its crucial role in mitigating colour distortions caused by varying image acquisition conditions. These algorithms are essential pre-processing steps to standardise colour representation across different devices and imaging conditions, thus reproducing images that accurately represent real-world scenes. Over the years, many studies have been conducted on the colour constancy topic to improve its effectiveness and accuracy in various domains. This paper reviews significant contributions to colour constancy algorithms over the past 10 years, including the fundamentals of image formation, colour correction algorithms in conventional applications, and colour correction algorithms in the medical field. By offering a comprehensive overview of these key topics, the paper highlights the potential of smartphone-based imaging and colour constancy algorithms in advancing healthcare applications and enhancing diagnostic accuracy.
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creator: Wee Li Low
creator: Yuan Wen Hau
creator: Chia Yee Ooi
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 136
ending page: 147
doi: 10.11113/humentech.v4n2.106

Adapting The Bruininks-Oseretsky Test of Motor Proficiency (BOT-2) for Young Athletes
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description: The original Bruininks-Oseretsky Test of Motor Proficiency, Second Edition (BOT-2) is heavily used to detect motor impairments. It has shown limitations when applied to athletic population due to ceiling effects and low score variability among skilled youth. This pilot study aimed to evaluate an adapted version of BOT-2 tailored for young athletes aged 13–17 by incorporating dynamic and time-based components to enhance discrimination and engagement. The adapted BOT-2 included tasks spanning four motor domains: Drawing Lines and Folding Paper (Fine Motor Precision), and Transferring Pennies (Manual Dexterity), modified with time constraints. Descriptive statistics, reliability analysis (Cronbach’s Alpha), ceiling effect inspection, and correlation matrix analysis were conducted to assess the performance variation and internal consistency. The obtained results revealed that specific retained tasks, particularly Drawing Lines and Folding Paper, exhibited strong ceiling effects. In contrast, the time-adapted tasks such as Dribbling and One-Legged Hop showed greater score variability and stronger differentiation. Principal Component Analysis further supported the multifactorial nature of motor proficiency, identifying four distinct components that accounts for 82.23% of total variance. These component groupings reflected agility, balance-related control, and fine motor integration. These findings highlight the potential of sport-specific BOT-2 adaptations and offer insights into optimizing motor proficiency assessments for developmental athletic populations, meriting further investigation.
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creator: Muhamad Izzan Ismail
creator: Mohd Syafiq Miswan
creator: Hosni Hasan
creator: Nurul Farha Zainuddin
creator: Mohd Irzat Rozaidy Mohamad Roseli
creator: Farith Zaris Erfan Zeini Effendey
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 125
ending page: 135
doi: 10.11113/humentech.v4n2.108

An UX Evaluation Framework for Islamic Design and Content-Based Digital Therapeutics for Mental Health: A Proposed Approach
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description: With the rise in the occurrence of mental health issues among youths, especially students, an urgent need might have arisen for intervention strategies that respect cultural intricacies. Digital Therapeutic (DTx) quite interestingly serves as a frontier wherein technology is used to give evidence-based support for mental health. In an unfortunate case of neglect, however, there has been a lack of adaptation of these platforms for the considered needs of Muslim users in terms of accommodating Islamic principles and understanding. This paper took a huge jump forward in filling this gap by offering an innovative and thorough User Experience (UX) evaluation framework that holistically integrates Islamic design architecture featuring geometric patterns, calligraphy, and content imbued with spiritual significance. It also offers places for gateways into Islamic teachings, reminders to pray, and guided meditation. The framework looks very closely at and gives guidelines on important elements for Turkish developer to create DTx solutions within an Islamic framework such as usability, accessibility, engagement, and user satisfaction. Having developed through an exhaustive literature review and established frameworks, this model acts as a basic tool for appraising and thereby improving systematically the user experience of digital therapeutics within Islamic contexts. This research contribution attempts to improve the mental health outcomes for Muslim youth through digital health technologies alongside cultural inclusivity to suggest the importance of culturally attuned mental health interventions in today's digital realm.
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creator: Nahreen Zannat
creator: Murni Mahmud
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 113
ending page: 124
doi: 10.11113/humentech.v4n2.107

Extensive Review on Humidity and Moisture on Skin Device Analysis
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description: Moisture and humidity influence the skin properties, particularly in the coefficient of friction (CF). In the process of dexterous manipulation, changing in skin hydration will trigger the mechanical properties of object interface and alter the required minimum force to slip any object on the surface. The moisture level of the skin can be obtained based on two principles either the principle of capacitance or conductance. However, there are only few studies reported on the device to measure skin moisture with limited information on the device capacity. On the other hand, currently available devices in the market are mostly manual reported, and it is difficult to find a complete research study on the device prior to marketing. Other devices that are familiar in the aforementioned fields are normally established based on the lab scale standard in comparison with the developed devices, which are not for universal use. For example home-based monitoring or personal skin care routine. Not to mention, the measurement varies from image sensor and many others. Therefore, in this study, the fundamental concept of a device based on pressure sensor was discussed. The information on the quantitative skill measurement was also provided. In the last part, all the devices that are related to moisture and humidity measurement were tabulated and their performances were highlighted.
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creator: Nurul Asmak Md Lazim
creator: Siti Hamidah Mohd Setapar
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 101
ending page: 112
doi: 10.11113/humentech.v4n2.104

Online Platform for Home-Based Medical Device Lifecycle Management: A User-Centric Approach
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description: The growing access to medical devices in home settings that is driven by the advancements in telemedicine and home monitoring technologies, has significantly increased their usage, especially in post-pandemic era. However, home-based medical device users often face challenges in accessing reliable information and support for device operation, maintenance and training. This study addressed these issues by developing a user-friendly online platform using Wix to support individuals managing medical devices in home settings. The platform integrates multiple functionalities, including access to product specification, warranty management, rental request, maintenance request submission, regulatory compliance information and user training resources. The usability testing with 40 diverse participants revealed high satisfaction rates with 92% agreeing that the platform effectively supports medical device management and 96% acknowledge the clarity and value of the educational resources. This study highlights the platform’s potential to empower home users by improving their competency in medical device utilization and improve health outcomes in home-care environments.
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creator: Yee Hui Tan
creator: Maheza Irna Mohamed Salim
creator: Rania Hussein Alashwal
creator: Ahmad Zahran Md Khudzari
creator: Tian Swee Tan
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 93
ending page: 100
doi: 10.11113/humentech.v4n2.101

Eating Disorder Biomarkers: Macronutrient Regulation of Ghrelin and Leptin
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description: This review examines the potential of ghrelin and leptin as biomarkers in eating disorders by analysing their roles in appetite regulation, energy balance, and eating behaviour. Ghrelin stimulates hunger, whereas leptin suppresses appetite and maintains energy homeostasis. Dysregulation of these hormones, often influenced by high-fat and high-sugar diets, is linked to overeating, obesity, and eating disorders. Imbalances in ghrelin and leptin signalling are associated with conditions such as hyperphagia and binge eating. This review also explores effects of stress and hormonal resistance on these hormones. Understanding how ghrelin and leptin interact with central and peripheral systems offers insights into appetite regulation and potential therapeutic targets for metabolic and psychological disorders.
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creator: Balqis Mohd Mazlan
creator: Farah Hanis Juhari
creator: Nik Ahmad Nizam Nik Malek
creator: Mohd Aizuddin Mohd Lazaldin
creator: Maheza Irna Mohamad Salim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 68
ending page: 77
doi: 10.11113/humentech.v4n1.100

Advanced Human-Centered Food Quality Assessment: Second Derivative Linear Prediction of Raw Broiler Shear Force Using Near-Infrared Spectroscopy
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description: This study investigates the application of linear predictive models and a low-cost Near-Infrared Spectroscopy (NIRS) system for non-invasive texture measurement of raw broiler meat, emphasizing its impact on food safety, consumer health, and industrial efficiency. Traditional meat quality assessment methods are often destructive, time-consuming, and labor-intensive, highlighting the need for more efficient, non-invasive alternatives. This research evaluated the effectiveness of Principal Component Regression (PCR) and Partial Least Squares (PLS) in predicting meat texture, demonstrating that the PLS outperformed the PCR with fewer latent variables and higher predictive accuracy. The results showed that the prediction accuracy of the PLS model for shear force estimation reached 64.01% for breast meat and 64.94% for drumstick samples, surpassing the performance of the PCR model. The application of second-order Savitzky-Golay derivative filtering and optimized spectral pre-processing further enhanced the model performance. By eliminating the need for invasive testing, this approach advances smart food technology, providing a fast, cost-effective, and non-destructive solution for automated meat quality assessment. These findings contribute to the development of AI-driven, real-time monitoring systems, improving food processing, supply chain efficiency, and ultimately ensuring better food quality and safety for consumers.
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creator: Rashidah Ghazali
creator: Nur Athirah Syafiqah Noramli
creator: Herlina Abdul Rahim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-08-06
publication date: 2025-08-06
starting page: 86
ending page: 92
doi: 10.11113/humentech.v4n2.102

Strain Gauge Sensors in Industrial Instrumentation: A Review for Human Technology Integration
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description: This study offers an in-depth exploration of strain gauge sensors, emphasizing their critical role in industrial instrumentation and their broader impact on human-centric technologies. Strain gauges are indispensable for precise measurement of material deformation across diverse industrial applications, directly influencing advancements in structural monitoring, safety systems, and ergonomic designs. The paper thoroughly examines sensor types, applications, technical specifications, operational principles, interfacing with other devices, microcontroller programming, and circuit analysis. Furthermore, it highlights potential innovations and directions for developing advanced sensors, tailored to evolving industrial and societal needs. Through comprehensive studies, simulations, and programming insights, this research provides engineers and researchers with a robust understanding of strain gauge technology. By addressing its integration into human-focused systems, the paper outlines pathways for leveraging strain gauges to enhance human safety, efficiency, and functionality in various domains. This work aims to foster advancements in sensor technology, bridging industrial precision with human-oriented applications.
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creator: Muhammad Hafizi Mohd Diah
creator: Muhammad Haziq Faris Sahli Hazimin
creator: Nur Athirah Syafiqah Noramli
creator: Herlina Abdul Rahim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 50
ending page: 55
doi: 10.11113/humentech.v4n1.97

Innovative Approaches to Gas Sensing: Bridging Theory and Human Applications
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description: In this study, a comprehensive analysis of gas sensor technology was conducted, focusing on various types and their applications in industrial instrumentation. The technical characteristics of different gas sensors, both static and dynamic, are explored, along with an examination of working principles. Connection methods with other devices were demonstrated using simulation software for wiring diagrams and microcontroller programming. An analysis of circuit characteristics was presented, with a focus on input-output relations such as amplitude and sensitivity. Additionally, a conceptual design for a new type of gas sensor was proposed, utilizing existing components. This study not only contributes to the understanding of current gas sensor technologies but also outlines key directions for future innovations, specifically focusing on optimizing sensor efficiency for human-based technology applications.
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creator: Osama Gamal Mahmoud
creator: Nur Athirah Syafiqah Noramli
creator: Herlina Abdul Rahim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 43
ending page: 49
doi: 10.11113/humentech.v4n1.96

K-Nearest Neighbor-Based Detection of Chokanan Mango Maturity for Agricultural Technology Applications
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description: This study presents a novel application of machine learning, specifically the K-Nearest Neighbors (KNN) algorithm implemented in Python, to detect the maturity of Chokanan mangoes. The research addressed a critical need in agriculture and food technology by providing an automated system for evaluating fruit maturity, thereby enhancing post-harvest processes and ensuring high-quality production for consumers. The proposed method involved the extraction of key features from mango images and training a KNN classifier with labeled data. The trained model was then utilized to classify mango samples into distinct maturity stages. The experimental results demonstrated the system's high accuracy in classifying mango maturity, showcasing its potential as a practical solution for fruit quality assessment. By integrating this approach, the fruit industry can improve their operational efficiency, reduce waste, and better meet consumer expectation for premium-quality fruits.
subject: Articles
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creator: Nur Athirah Syafiqah Noramli
creator: Hajar Izzati Mohd Ghazalli
creator: Herlina Abdul Rahim
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 35
ending page: 42
doi: 10.11113/humentech.v4n1.93

Nutritional Characterization of Moringa oleifera as a Potential Equine Feed and Human Application
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description: The demand for high-quality horse feed in Malaysia has led to a reliance on imported products. Locally grown Moringa oleifera is a promising protein source for horse feed and possible human application. Hence, this study aimed to characterize Moringa oleifera as a potential horse feed, projecting into possible human use. In this study, Moringa pellets were formulated to compose of rice bran, molasses, corn meal, palm kernel cake (PKC), calcium carbonate, mineral premix and salt. The formulation was designed based on the nutritional needs of maintenance horses (11% CP and 11 MJ/kg DM ME). The production process involved drying Moringa leaves, weighing of ingredients according to formulation followed by mixing, and pelletizing of the components. The nutritional composition of the Moringa pellets was analyzed following standard Association of Official Analytical Chemists (AOAC). It was found that the Moringa pellets contained 90.4% dry matter (DM), 11.7% crude protein (CP), 9.7% crude fiber (CF), and 4.9% ether extract (EE). The Moringa pellets have met the requirement for maintenance horse. Hence, the use of locally sourced ingredients ensures that the Moringa pellets provide balanced nutrition, supporting the overall health and wellness of horses while reducing dependence on imported feed ingredients. The individual protein and fibers compositions are also useful for human applications such as for topical use and oral consumption. However, further exploration and modification should be done for the purpose of human application.
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creator: Maisarah Madihah Matriffin
creator: Mira Panadi
creator: Ahmad Zahran Md. Khudzari
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 17
ending page: 24
doi: 10.11113/humentech.v4n1.89

In-vitro Biocompatibility Analyses on Co-electrospun of Polyurethane/Chitosan and Polyvinyl Alcohol/Elastin Vascular Membrane
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description: The demand for vascular grafts and membranes is rising, particularly in Malaysia, where cardiovascular diseases are the leading cause of death. Chitosan (CS) and elastin (EL) are commonly used in cardiovascular applications for their cell adhesion and proliferation properties, promoting functional tissue formation. This study blended these natural polymers with synthetic materials, polyurethane (PU) and polyvinyl alcohol (PVA), to create co-electrospun vascular membranes. Glutaraldehyde (GA) was used as a crosslinking agent to enhance membrane stability. The study aimed to investigate the biocompatibility of co-electrospun membranes before and after GA crosslinking, focusing on cell viability and proliferation using cardiomyocytes. The results obtained from cell viability show that all co-electrospun membranes were very toxic, with the highest cell viability found in PU-CS/PVA at 26.36 ± 4.52% and PU-CS/PVA-EL at 22.27 ± 12.56%. However, in the cell proliferation analysis, the PU-CS/PVA-EL membrane was able to support cell proliferation at 85.88 ± 4.47% on day 3 and 78.34 ± 1% on day 7. After crosslinking, all the co-electrospun membranes experienced a significant reduction in cell proliferation that led to cytotoxicity. Therefore, due to their toxicity, this study did not support crosslinked PU-CS/PVA-EL membrane for cardiovascular applications.
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creator: Fakhira Alanna Shabira
creator: Kugambikai Vangetaraman
creator: Sarawut Kumphune
creator: Sivakumar Sivalingam
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 10
ending page: 16
doi: 10.11113/humentech.v4n1.88

Review on Fundamental of Electroencephalography and Detection Techniques in Substance and Behavioral Addiction
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description: Addiction is a chronic relapsing brain disease associated with substantial individual and societal burden. It includes complex phyco-physiological conditions and can be recognized by compulsive and harmful behaviors towards a substance or activity, despite negative consequences or “bio-psycho-social-spiritual” disorder. This paper aims to comprehensively review previous research which applied machine learning to electroencephalography (EEG) signals for automatic detection of addiction. A systematic search was done on 200 relevant papers published between 2018 - 2023. The previous studies applied a variety of machine learning algorithms including support vector machines, neural networks, logistic regressions and brain networks to classify addicted individuals against controls based on resting state, cue-reactivity paradigms and neurofeedback tasks. The features utilized spectral power, functional and effective connectivity, graph theoretical measures and event-related potentials. The output accuracy often exceeded 95% across multiple substances including alcohol, nicotine, cannabis and opioids. In this review, the challenges and open questions around data quality, model interpretation and transition to clinical settings were also discussed. In overall, automatic EEG analysis shows significant potential as an objective and accessible tool for addiction diagnosis, treatment monitoring and relapse prevention that projects worthy of continued refinement and validation.
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creator: Sadeem Nabeel Saleem Kbah
creator: Tian Swee Tan
creator: Jahanzeb Sheikh
creator: Noor Kamal Al-Qazzaz
creator: Maheza Irna Mohamad Salim
creator: Yan Chai Hum
creator: Michael Loong Peng Tan
creator: Fujie Qiu
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 78
ending page: 85
doi: 10.11113/humentech.v4n1.98

Cyborg Technology in Bio Engineering: Enabling Technologies, Implications, Applications and Future Trends
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description: Medical technology has made notable progress in recent decades with the assistance of engineering and information and communication technology. With the aid of miniaturized electronic devices with intelligence and communication capabilities can be used to monitor patients and older people remotely and streamline all the healthcare services required in times of need with minimum human interventions. The advances made in the field of microelectronics have enabled us to manufacture devices that are small enough to be embedded within the human body. When a human being is fitted with a device for the purpose of assisting an underperforming organ or to enhance some biological function, he is known as a cyborg. Cyborg is a portmanteau of two words cybernetics and organism where a biological organism is embedded (or fitted) with some machine elements for the purpose of enhancing some of its biological functions. In this article, the authors take a critical look at cyborgs from different angles with the view of understanding the implications of this technology at individual and social levels along with giving their own interpretations and comments. As this article looks at cyborg technology from multiple directions, it will be a useful reference for anybody who is willing to embark on this fascinating research area.
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creator: Mohamed Fazil Mohamed Firdhous
creator: Adshayani Pirapaharan
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 56
ending page: 67
doi: 10.11113/humentech.v4n1.90

Research on Capture the Flag Exercises for Cybersecurity Skill Training Among Malaysian Undergraduates
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description: Cybersecurity education is crucial for addressing the growing skills gap in industries, with Capture the Flag (CTF) exercises emerging as a promising gamified approach for engaging and training students in cybersecurity skills. This study introduces SKRCTF, an integrated framework that adapts CTF principles for Malaysian undergraduate cybersecurity education. Through a systematic integration of gamification elements and pedagogical principles, SKRCTF was designed to cater to the specific needs and challenges of Malaysian undergraduates in cybersecurity skill development. The framework's effectiveness was evaluated through a quasi-experimental study involving two Malaysian universities, using pre-test and post-test assessments. While initial results showed limited improvement in overall performance, the second iteration with enhanced scaffolding demonstrated significant progress in specific areas such as operating system threats and cryptography pattern recognition. These findings, though partially negative, provide valuable insights into the prerequisites and conditions necessary for effective CTF implementation in Malaysian higher education. The study contributes to the understanding of how gamified cybersecurity training should be adapted for different educational contexts, particularly highlighting the importance of fundamental computing knowledge and structured support systems. The SKRCTF framework and its implementation findings offer a foundation for developing more effective cybersecurity training programs tailored to Malaysian undergraduate education.
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creator: Li Jing Khoo
creator: Maizatul Hayati Mohamad Yatim
creator: Yoke Seng Wong
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 1
ending page: 9
doi: 10.11113/humentech.v4n1.87

Digital Immersion in Melaka: Enhancing Historical Learning through Technology on the Malaccan Sultanate
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description: This article presents an evaluation on the “Enjoy Melaka” game, which aims to create an engaging educational tool that informs and enlightens the public society on the historical riches of Malaccan Sultanate. The main objectives of this study were to develop an interactive three-dimensional (3D) game that provides an immersive learning experience and to assess its effectiveness as a medium for disseminating historical information. The game was set around the Melaka River attraction site, allowing human players to explore a virtual world filled with historical landmarks and facts. The game was designed for the players to collect items to activate in-game checkpoints that displayed educational content about the Malaccan Empire. There were four checkpoints, each elaborating on different historical aspects of the Sultanate. The accumulated scores allowed the players to progress through the game until they achieved the maximum score. The game development involved creating a detailed 3D environment and integrating educational content into the gameplay. Data were collected through testing activities conducted with a target group of public users. This group provided feedback on the game's effectiveness in making historical information more engaging compared to traditional textual forms such as books, brochures, newspapers and online articles. The important contribution of this study is highlighted through the interactive 3D games which can serve as a more engaging and effective medium for historical education. By transforming the approach in conveying information about the Malaccan Sultanate, the “Enjoy Melaka” game has the potential to enhance public interest and understanding on historical period.
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creator: Hamzah Asyrani Sulaiman
creator: Chia Yen Toh Darren
creator: Che Ku Nuraini Che Ku Mohd
rights: Copyright (c) 2025 Journal of Human Centered Technology
date: 2025-02-06
publication date: 2025-02-06
starting page: 25
ending page: 34
doi: 10.11113/humentech.v4n1.99