Publications

@article{Siau2025,

title = {Sustainable and high performance triboelectric nanogenerator using water-processable and non-toxic Arabic gum-graphite composite green electrodes for enabling circular recyclability},

author = {Lei-Jun Siau and Wayne Yin-Hern Lim and Pei-Song Chee and Eng-Hock Lim and Chun-Hui Tan and Jen-Hahn Low},

doi = {10.1088/1361-665x/ae1915},

issn = {1361-665X},

year  = {2025},

date = {2025-11-01},

journal = {Smart Mater. Struct.},

volume = {34},

number = {11},

publisher = {IOP Publishing},

abstract = {Abstract

                  

                    Rapid advancement in the internet of things has led to the rise in power consumption, leading to the huge disposal of batteries that adversely affect the environment. Triboelectric nanogenerators (TENGs) using sustainable materials have gained substantial interest, however, electrodes used in TENGs are typically non-green and non-recyclable. In this work, we present a green and recyclable TENG featuring recycled paper as the positive friction layer and recycled polyvinyl-chloride as the negative layer, and employing Arabic gum-graphite composite as electrode for the first time, instead of conventional metal electrodes such as copper or aluminum. Remarkably, we found out that Arabic gum, a natural polysaccharide, can bind with the graphite well, exhibiting good mechanical and electrical properties, and opening new possibilities for recyclable electrodes. An optimum composition ratio of 15:10 (Arabic gum: graphite) of the green electrode, achieves an open-circuit voltage of 100 V and short-circuit current of 0.2

                    µ

                    A with the triboelectric active area of 5 × 5 cm

                    2

                    , which is about 20 times compared with that using copper as electrodes. Interestingly, the proposed green electrode can be conveniently disintegrated in water and reshaped into reusable electrodes again without significant performance degradation even after 10 000 working cycles. The proposed TENG, utilizing a green electrode, successfully functions as a self-powered input for a microcontroller-based custom-made game through hand tapping, while also demonstrating its ability to charge capacitors of various sizes and power low-power electronics such as a commercial calculator. This work paves the way toward fully sustainable and recyclable electrode materials for next-generation triboelectric energy harvesting devices.

                  },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Siau2025b,

title = {Sustainable and high performance triboelectric nanogenerator using water-processable and non-toxic Arabic gum-graphite composite green electrodes for enabling circular recyclability},

author = {Lei-Jun Siau and Wayne Yin-Hern Lim and Pei-Song Chee and Eng-Hock Lim and Chun-Hui Tan and Jen-Hahn Low},

doi = {10.1088/1361-665x/ae1915},

issn = {1361-665X},

year  = {2025},

date = {2025-11-01},

journal = {Smart Mater. Struct.},

volume = {34},

number = {11},

publisher = {IOP Publishing},

abstract = {Abstract

                  

                    Rapid advancement in the internet of things has led to the rise in power consumption, leading to the huge disposal of batteries that adversely affect the environment. Triboelectric nanogenerators (TENGs) using sustainable materials have gained substantial interest, however, electrodes used in TENGs are typically non-green and non-recyclable. In this work, we present a green and recyclable TENG featuring recycled paper as the positive friction layer and recycled polyvinyl-chloride as the negative layer, and employing Arabic gum-graphite composite as electrode for the first time, instead of conventional metal electrodes such as copper or aluminum. Remarkably, we found out that Arabic gum, a natural polysaccharide, can bind with the graphite well, exhibiting good mechanical and electrical properties, and opening new possibilities for recyclable electrodes. An optimum composition ratio of 15:10 (Arabic gum: graphite) of the green electrode, achieves an open-circuit voltage of 100 V and short-circuit current of 0.2

                    µ

                    A with the triboelectric active area of 5 × 5 cm

                    2

                    , which is about 20 times compared with that using copper as electrodes. Interestingly, the proposed green electrode can be conveniently disintegrated in water and reshaped into reusable electrodes again without significant performance degradation even after 10 000 working cycles. The proposed TENG, utilizing a green electrode, successfully functions as a self-powered input for a microcontroller-based custom-made game through hand tapping, while also demonstrating its ability to charge capacitors of various sizes and power low-power electronics such as a commercial calculator. This work paves the way toward fully sustainable and recyclable electrode materials for next-generation triboelectric energy harvesting devices.

                  },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lee2025,

title = {Fabric to energy storage via oxygen‐tuned graphene engineered by laser crafting},

author = {Soon Poh Lee and Kwok Feng Chong and Eng Hock Lim and Chun Hui Tan and Cao Guan and Pei Song Chee},

doi = {10.1002/flm2.70001},

issn = {2836-9106},

year  = {2025},

date = {2025-10-00},

journal = {FlexMat},

volume = {2},

number = {3},

pages = {290--302},

publisher = {Wiley},

abstract = {Abstract

                  

                    Fabric‐based energy storage devices are essential for next‐generation wearable electronics, requiring materials that combine lightweight structure, high conductivity, and mechanical durability. Laser‐induced graphene (LIG) is a promising candidate due to its tunable surface chemistry, excellent electrical properties, and compatibility with textile substrates. However, improving its electrochemical performance often involves chemical modifications with metal oxides or polymers, complicating processing and limiting scalability. Traditional synthesis methods for oxygen‐rich graphene rely on hazardous chemicals and labor‐intensive procedures. In this work, we present an eco‐friendly, one‐step laser‐scribing technique to fabricate oxygen‐functionalized LIG directly on Kevlar textiles, enabling the creation of flexible, fabric‐based energy storage devices without the need for chemical treatments. By carefully controlling the laser power (P) and scan speed (S), we achieve a precise balance between graphitization and oxygen functionalization. Density functional theory analysis reveals that specific oxygen groups—carboxyl, hydroxyl, epoxy, and carbonyl—play a key role in enhancing potassium‐ion adsorption. The optimized LIG‐P3S1 sample (laser power level 3, scan speed level 1) exhibits a high carbon content of 89.12 At%, with 67.51% of oxygen groups from C–O and C–OH bonds. This surface chemistry results in an areal capacitance of 88.92 mF cm

                    −2

                    at 0.3 mA cm

                    −2

                    , along with good cycling stability, retaining 66.67% capacitance after 10 000 cycles. The device also demonstrates stable performance under bending angles of up to 120°, making it suitable for wearable applications. This work offers a scalable, sustainable approach to flexible energy storage, with potential applications in wearable and biomedical electronics.

                  },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ganesan2025,

title = {Far-field ammonia gas sensing at room temperature with graphene nanoplatelets-infused PEDOT:PSS transparent thin film},

author = {Vinod K Ganesan and Chun Hui Tan and Pei Song Chee and Jen Hahn Low and Soon Poh Lee and Eng Hock Lim},

doi = {10.1016/j.talo.2024.100389},

issn = {2666-8319},

year  = {2025},

date = {2025-08-00},

journal = {Talanta Open},

volume = {11},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pan2025,

title = {Artificial intelligence in chemical exchange saturation transfer magnetic resonance imaging},

author = {Swee Qi Pan and Yan Chai Hum and Khin Wee Lai and Wun-She Yap and Yi Zhang and Hye-Young Heo and Yee Kai Tee},

doi = {10.1007/s10462-025-11227-5},

issn = {1573-7462},

year  = {2025},

date = {2025-07-00},

journal = {Artif Intell Rev},

volume = {58},

number = {7},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tiong2025,

title = {Improving human detection in the presence of cartoon characters using retrained deep learning models},

author = {Wei Jie Tiong and Yan Chai Hum and Ying Loong Lee and Khin Wee Lai and Kok Lim Yau and Wun-She Yap and Yee Kai Tee},

doi = {10.1007/s11760-025-04019-5},

issn = {1863-1711},

year  = {2025},

date = {2025-06-00},

journal = {SIViP},

volume = {19},

number = {6},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kow2025,

title = {Surrogate GPR139 Agonists Reverse Short‐Term Startle Habituation Impairment in Larval Zebrafish},

author = {Teck Fong Kow and Siew Ying Mok and Pek Yee Tang and Lor Huai Chong and Satoshi Ogawa},

doi = {10.1096/fj.202500594r},

issn = {1530-6860},

year  = {2025},

date = {2025-05-31},

journal = {The FASEB Journal},

volume = {39},

number = {10},

publisher = {Wiley},

abstract = {ABSTRACTGPR139, an orphan G‐protein coupled receptor predominantly expressed in the habenula, has recently been implicated in understanding neurobehavior and neuropsychiatric disorders. Surrogate agonists for human GPR139 have shown the potential to alleviate cognitive impairment associated with schizophrenia in rodent models and human clinical trials. Yet, the effect of GPR139 agonists on the neurophysiological properties of the habenula remains elusive. We examined the effect of GPR139 agonists (JNJ‐63533054 and TAK‐041) on short‐term startle habituation of 6‐day post‐fertilization (dpf) larval zebrafish (Danio rerio) in an automated solenoid setup and on reversing the pharmacologically impaired startle habituation. GPR139 agonists enhanced startle habituation at the lowest tested concentrations, whereas moderate and highest concentrations delayed startle habituation. Furthermore, GPR139 agonists reversed the non‐competitive N‐methyl‐d‐aspartate (NMDA) receptor antagonist MK‐801‐induced startle habituation impairment. Using exponential decay curve fit analysis, we found that the lowest concentration of GPR139 agonists performed better than moderate and highest concentrations in reversing the MK‐801‐induced impairment of startle habituation. Using in vivo GCaMP calcium imaging and phosphorylated extracellular‐signal‐regulated kinase (pERK) as a proxy for neural activity, we found that GPR139 agonists exerted effects on the habenula activities at the habituated state but not during the spontaneous state (without startle habituation paradigm), suggesting the GPR139 agonists‐evoked neural activation in the habenula is sensory stimuli‐dependent. Moreover, both GPR139 agonists differently reduced MK‐801‐induced hyperexcitability of the habenula at both spontaneous and habituated states. Taken together, we showed that GPR139 agonists reverse startle habituation impairment caused by MK‐801 via the normalization of hyperexcitability of zebrafish habenula.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bu2025,

title = {Bio-inspired hormonic electrolyte: negative feedback for ultra-stable zinc anodes},

author = {Fan Bu and Shaofei La and Wenbo Zhao and Yifan Deng and Yong Gao and Jizhang Jiang and Qinghe Cao and Jipeng Chen and Pei Song Chee and Salah A. Makhlouf and Cao Guan},

doi = {10.1039/d5ee01058f},

issn = {1754-5706},

year  = {2025},

date = {2025-05-20},

journal = {Energy Environ. Sci.},

volume = {18},

number = {10},

pages = {4632--4642},

publisher = {Royal Society of Chemistry (RSC)},

abstract = {A hormone-mimicked electrolyte is inspired by coagulation systems, which implements self-regulating negative feedback for stable Zn anodes at high current densities/capacities, facilitating practical Zn-ion batteries with high energy/power densities.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Voon2025,

title = {Trapezoidal Step Scheduler for Model-Agnostic Meta-Learning in Medical Imaging},

author = {Wingates Voon and Yan Chai Hum and Yee Kai Tee and Wun-She Yap and Khin Wee Lai and Humaira Nisar and Hamam Mokayed},

doi = {10.1016/j.patcog.2024.111316},

issn = {0031-3203},

year  = {2025},

date = {2025-05-00},

journal = {Pattern Recognition},

volume = {161},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{La2025,

title = {A thermal transfer-enhanced zinc anode for stable and high-energy-density zinc-ion batteries},

author = {Shaofei La and Yong Gao and Qinghe Cao and Jingzhu Chen and Abdelnaby M. Elshahawy and Yingyi Cui and Fan Bu and Salah A. Makhlouf and Pei Song Chee and Cao Guan},

doi = {10.1016/j.matt.2025.102013},

issn = {2590-2385},

year  = {2025},

date = {2025-05-00},

journal = {Matter},

volume = {8},

number = {5},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2025,

title = {Shape‐Controlled Reversible Li Plating‐Stripping for Stable and High‐Rate Anode‐Free Lithium Metal Batteries},

author = {Yuxuan Wang and Yuhao Li and Xiaohan Wang and Yong Gao and Chenhao Li and Ting Meng and Haifeng Zhang and Pei Song Chee and Salah A. Makhlouf and Cao Guan},

doi = {10.1002/adma.202420373},

issn = {1521-4095},

year  = {2025},

date = {2025-05-00},

journal = {Advanced Materials},

volume = {37},

number = {18},

publisher = {Wiley},

abstract = {AbstractAnode‐free lithium metal batteries are promising toward high‐energy‐density power sources with low‐cost, but their practical applications are challenged by poor cycling stability and low rate capability. Herein, a shape change‐free and lithium‐free anode that well controls the reversible Li plating‐stripping is reported, which is composed of a highly‐ordered hollow ZnO matrix with a surface‐coated lithium‐phosphorus‐oxynitride (LiPON) layer. The ZnO matrix supplies sufficient cavities and lithiophilic sites to facilitate uniform Li plating/stripping within the hollow cavity, while the LiPON layer maintains stable solid‐electrolyte interphase from mechanical and electrochemical damage. As a result, lithium is constrained within the cavity and the overall anode shape is effectively controlled during long‐term and high‐rate cycling. The assembled half‐cell stably works at 1.2 mA cm−2 for 335 cycles with Coulombic efficiency of 98.8%. Without Li pre‐deposition, full‐cells using modified‐LiFePO4 and LiNi0.5Co0.2Mn0.3O2 cathodes demonstrate 150‐cycles lifespan and high energy density of 617 Wh kg−1 at 2C rate.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Krishnan2025,

title = {The Effect of Menstrual Cycle Phases on Agility and Shoulder Endurance in Recreational Basketball Players},

author = {Kamala Krishnan and Muhammad Noh Zulfikri Mohd Jamali and Lee Phang Yoong and Premala Krishnan},

doi = {10.1177/23259671251334606},

issn = {2325-9671},

year  = {2025},

date = {2025-05-00},

journal = {Orthopaedic Journal of Sports Medicine},

volume = {13},

number = {5},

publisher = {SAGE Publications},

abstract = {

            Background:

            Basketball, a widely played sport globally, has seen an increase in injury rates among players, particularly in ankle and knee joints, due to high-intensity movements. Female players are more prone to injuries, and the menstrual cycle can significantly affect performance, with studies showing decreased performance during menstruation.

          

          

            Purpose:

            To investigate the effect of early or late follicular phase on agility and shoulder endurance in female recreational basketball players.

          

          

            Study Design:

            Descriptive laboratory study.

          

          

            Methods:

            

              A total of 30 eumenorrheic female recreational basketball players, with a mean ± SD age of 21.3 ± 1.4 years, were recruited for this study. Agility and shoulder endurance using the T-Drill Test and Shoulder Endurance test, respectively, during both the early (day 1) and the late (day 12) follicular phases of the menstrual cycle were assessed. Descriptive statistics were employed to analyze the data, and a paired-sample

              t

              test was conducted to compare the performances between the phases.

            

          

          

            Results:

            

              The results indicated that agility was higher during the late follicular phase compared with the early follicular phase (

              t

              29 = 4.25;

              P

              < .01; effect size, 0.47), while shoulder endurance was higher during early follicular compared with late follicular phase (

              t

              29 = 6.35;

              P

              < .01; effect size, 1.03).

            

          

          

            Conclusion:

            This study found that there were significant differences in agility and shoulder endurance between the early and late follicular phases of the menstrual cycle among recreational basketball players, potentially indicating risk of injury to the lower limb and shoulder during the early follicular phase.

          },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ngu2025,

title = {MSTransBTS—A Novel Integration of Mamba with Swin Transformer for 3D Brain Tumour Segmentation},

author = {Jia Qin Ngu and Humaira Nisar and Chi-Yi Tsai},

doi = {10.3390/math13071117},

issn = {2227-7390},

year  = {2025},

date = {2025-04-00},

journal = {Mathematics},

volume = {13},

number = {7},

publisher = {MDPI AG},

abstract = {This study focuses on the major challenges in ensuring the timely assessment and accurate diagnosis of brain tumors (BTs), which are essential for effective patient treatment. Hence, in this paper, a time-efficient, automated, and advanced deep learning (DL) solution, the Mamba Swin Transformer BT Segmentation (MSTransBTS) model, is introduced. This model employs the advanced Swin Transformer architecture, which is renowned for capturing long-range information and incorporates the latest Mamba approach for efficient long-range dependency modelling. Through meticulous customization and fine-tuning, the MSTransBTS achieves notable improvements in Dice scores, with scores of 89.53% for whole tumours (WTs), 80.09% for enhancing tumours (ETs), and 84.75% for tumour cores (TCs), resulting in an overall average Dice score of 84.79%. The employment of Test-Time Augmentation (TTA) further enhances performance and marks a significant advancement in BT segmentation accuracy. These findings not only address the critical need for timely assessment and diagnosis, but also emphasize the potential to enhance patient care through the automation of BT detection. By combining the features of Swin Transformer and Mamba techniques, this approach delivers a promising solution for accurate and efficient BT segmentation, which contributes to advancements in medical imaging.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vasu2025,

title = {Effects of autogenic relaxation training and progressive muscle relaxation on anxiety: an EEG-based experimental study},

author = {Deepak Thazhakkattu Vasu and Wei Yeh Chua and Lee Fan Tan},

doi = {10.31117/neuroscirn.v8i1.378},

issn = {2576-828X},

year  = {2025},

date = {2025-03-31},

journal = {Neurosci Res Notes},

volume = {8},

number = {1},

publisher = {Neurotak Publishing},

abstract = {Younger generations are shown to have a high prevalence rate of anxiety. This study examined the changes in the alpha brain signals based on autogenic relaxation training (ART) and progressive muscle relaxation (PMR) to determine their efficacy in reducing anxiety symptoms among undergraduate students. This study was a randomized controlled trial in which participants were randomly allocated to either the ART group or the PMR group. Seven supervised sessions of ART and PMR were conducted over three weeks, with each session lasting approximately 20 minutes. Electroencephalography (EEG) and Beck Anxiety Inventory scores (BAI) were used as outcome measures to assess the effectiveness of relaxation training on anxiety before and after the interventions. The study included 30 participants with a mean age of 19.60 ± 0.84 years. A paired sample t-test revealed that relaxation training significantly reduced anxiety. Additionally, ART demonstrated statistically significant effects in reducing anxiety (p=0.004), showing a greater decrease in post-intervention mean BAI scores compared to PMR. However, the difference between ART and PMR was not statistically significant (p=0.110). ART showed a greater reduction in post-intervention BAI scores, while PMR showed greater positive changes in EEG findings. The study outcome is an enhanced evidence-based physiotherapy program that may be used by physiotherapists in the neurological rehabilitation with anxiety.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ke2025,

title = {Advanced deep learning for multi-class colorectal cancer histopathology: integrating transfer learning and ensemble methods},

author = {Qi Ke and Wun-She Yap and Yee Kai Tee and Yan Chai Hum and Hua Zheng and Yu-Jian Gan},

doi = {10.21037/qims-24-1641},

issn = {2223-4306},

year  = {2025},

date = {2025-03-00},

journal = {Quant Imaging Med Surg},

volume = {15},

number = {3},

pages = {2329--2346},

publisher = {AME Publishing Company},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hian2025,

title = {Relationship between Turning difficulty and Fall risk among Geriatric Population: A Pilot Study},

author = {Goh Choon Hian and Premala Krishnan and Tee Yee Kai and Kamala Krishnan and Hum Yan Chai},

doi = {10.52711/0974-360x.2025.00116},

issn = {0974-360X},

year  = {2025},

date = {2025-02-27},

journal = {RJPT},

pages = {785--791},

publisher = {A and V Publications},

abstract = {Falls are the second leading cause of accidental or unintentional injury deaths worldwide and a great number of fatal falls are from the elderly population. Turning activity is a major contributor to fall in elderly. Most geriatrics suffering from turning difficulty complain of fall incidences. Fall from turning usually result in fracture of femur and the result was eight times more than fall during straight forward walking. Devastating consequence of fall such as long standings pain, functional impairment, disability, and death highlight the need for targeted fall assessment and management. To investigate the relationship between turning difficulty and fall risk among geriatric population using standardised physiotherapy outcome measures. A cross-sectional study design with simple random sampling method was adopted. A total of 138 participants were recruited within Klang Valley. Prior assessment, they were screened using a standardised health status questionnaire. They were assessed with Time Up and Go Test (TUG) for turning difficulty and Modified Fall Efficacy Scale (MFES) for fall risk. Descriptive statistics, independent t-test, and One-way ANOVA Test were used for data analysis. 80% of the participants completed TUG within 14 seconds. The mean score of MFES was 8.03. Age, coexist medical conditions, medications used, frequency of fall, reason for fall and use of assistive device were significantly associated with MFES. Age, coexist medical conditions, medications used, and use of assistive device were significantly correlated with TUG. Independent t-test showed TUG was significantly associated with MFES. Turning difficulty and fall risk are correlated among the geriatrics. Hence, preventive measures need to be taken to reduce the fall risk.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wong2025,

title = {A triboelectric sensor with an inverted pendulum design for machine and human movement monitoring in freestanding mode},

author = {Kwong Long Wong and Qi Lun Goh and Chun Hui Tan and Eng Hock Lim and Pei Song Chee},

doi = {10.1088/1361-665x/ada331},

issn = {1361-665X},

year  = {2025},

date = {2025-02-01},

journal = {Smart Mater. Struct.},

volume = {34},

number = {2},

publisher = {IOP Publishing},

abstract = {Abstract

               The vast availability of ambient mechanical vibrations in the natural environments and our daily activities has spurred the advancement of triboelectric sensors for vibration sensing. However, the operation of the traditional triboelectric vibration sensors (VSs) is usually constrained to contact–separation mode, limiting their functionality to transverse vibrations and making them unsuitable for longitudinal and rotary movements. The inherent wear and tear associated with the contact–separation mode further restricts their practical application. To address these limitations, this study presents a new design for a VS that employs a spring-assisted inverted pendulum structure. The VS exhibits a 10 Hz resonant frequency and produces maximum triboelectric output at the vibration amplitude of 5 mm. As a proof of concept, the VS successfully detects balanced and unbalanced fan blades by analyzing the obtained data via fast Fourier transform analysis. Besides machine monitoring, the proposed VS can be integrated into a wearable device for tracking human wrist movements. Combined with a machine learning algorithm, the sensor has achieved an accuracy level of greater than 95% in recognizing four distinct wrist motions: bending, rotating, waving, and handshaking. These findings have proven that the proposed triboelectric sensor design can be effectively integrated into wearable technologies, smart factories, and virtual/augmented reality systems, significantly broadening the triboelectric sensor applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Owen2024,

title = {Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension},

author = {Claire M. Owen and Jaume Bacardit and Maw P. Tan and Nor I. Saedon and Choon‐Hian Goh and Julia L. Newton and James Frith},

doi = {10.1113/ep091876},

issn = {1469-445X},

year  = {2025},

date = {2025-02-00},

journal = {Experimental Physiology},

volume = {110},

number = {2},

pages = {230--247},

publisher = {Wiley},

abstract = {AbstractGravity, an invisible but constant force

, challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequate haemodynamic control observed in orthostatic hypotension. This prevalent condition is characterized by drops in blood pressure upon standing; however, the contrary phenomenon of blood pressure rises has recently piqued interest. Expanding on the currently undefined orthostatic hypertension, our study uses continuous non‐invasive cardiovascular data to explore the full spectrum of blood pressure profiles and their associated frailty outcomes in community‐dwelling older adults. Given the richness of non‐invasive beat‐to‐beat data, artificial intelligence (AI) offers a solution to detect the subtle patterns within it. Applying machine learning to an existing dataset of community‐based adults undergoing postural assessment, we identified three distinct clusters (iOHYPO, OHYPO and OHYPER) akin to initial and classic orthostatic hypotension and orthostatic hypertension, respectively. Notably, individuals in our OHYPER cluster exhibited indicators of frailty and sarcopenia, including slower gait speed and impaired balance. In contrast, the iOHYPO cluster, despite transient drops in blood pressure, reported fewer fallers and superior cognitive performance. Surprisingly, those with sustained blood pressure deficits outperformed those with sustained rises, showing greater independence and higher Fried frailty scores. Working towards more refined definitions, our research indicates that AI approaches can yield meaningful blood pressure morphologies from beat‐to‐beat data. Furthermore, our findings support orthostatic hypertension as a distinct clinical entity, with frailty implications suggesting that it is worthy of further investigation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ng2025,

title = {Design of Dual-Band UHF RFID Tag Antenna Using Even and Odd Modes of Asymmetric Split Ring for Anti-Metal Applications},

author = {Gene-Jinhan Ng and Eng-Hock Lim and Pei-Song Chee and Muthukannan Murugesh},

doi = {10.1109/tap.2024.3495220},

issn = {1558-2221},

year  = {2025},

date = {2025-01-00},

journal = {IEEE Trans. Antennas Propagat.},

volume = {73},

number = {1},

pages = {64--73},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ferdowsi2025,

title = {Clinical Application of Artificial Intelligence in the Diagnosis, Prediction, and Classification of Coronary Heart Disease},

author = {Mahbuba Ferdowsi and Choon-Hian Goh and Haipeng Liu and Gary Tse and Jeremy Man Ho Hui and Xinhong Wang},

doi = {10.15212/cvia.2025.0009},

issn = {2009-8782},

year  = {2025},

date = {2025-00-00},

journal = {CVIA},

volume = {10},

number = {1},

publisher = {Compuscript, Ltd.},

abstract = {Coronary heart disease (CHD), the most common cause of mortality globally, poses a formidable challenge to modern healthcare systems. Artificial intelligence (AI) is playing an increasingly important role in multiple diagnostic applications of CHD, by facilitating early intervention and personalized treatment. This mini review describing the state of the art provides clinicians with updated insights into the transformative potential of AI to enhance CHD detection. AI can be used to increase diagnostic and prognostic accuracy. However, its reliance on homogeneous numerical data might potentially lead to misdiagnoses and unnecessary radiation exposure in diagnosing CHD. Multimodal data fusion brings new potential for accurate diagnosis and personalized medicine. Finally, unmet challenges and future research directions in ethical, regulatory, and technical aspects are discussed. This mini review is aimed at bridging the gap between AI advancements and practical applications in clinical settings, to achieve a future in which AI empowers CHD diagnosis in the context of a modern healthcare ecosystem.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Alagiasundaram2025,

title = {Compact Folded Dipolar Patch Antenna With Broad Tuning Range for On-Metal Tag Design},

author = {Subbiah Alagiasundaram and Kim-Yee Lee and Eng-Hock Lim and Pei-Song Chee},

doi = {10.1109/jrfid.2025.3561277},

issn = {2469-7281},

year  = {2025},

date = {2025-00-00},

journal = {IEEE J. Radio Freq. Identif.},

volume = {9},

pages = {170--179},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ooi2025,

title = {Compact ZOR Patch Antenna With Embedded Meandered Lines for UHF RFID Tag Design on Metal Platform},

author = {Shin-Yi Ooi and Eng-Hock Lim and Pei-Song Chee and Chun-Hui Tan and Jen-Hahn Low},

doi = {10.1109/jrfid.2025.3544414},

issn = {2469-7281},

year  = {2025},

date = {2025-00-00},

journal = {IEEE J. Radio Freq. Identif.},

volume = {9},

pages = {80--87},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sheikh2025,

title = {Motorised bionic arms using SSVEP with enhanced hand gesture accuracy and reliability},

author = {Jahanzeb Sheikh and Tan Tian Swee and Maheza Irna Mohamad Salim and Michael Loong Peng Tan and Hum Yan Chai and Tengku Ahmad T. Alang},

doi = {10.1504/ijbet.2025.145218},

issn = {1752-6426},

year  = {2025},

date = {2025-00-00},

journal = {IJBET},

volume = {47},

number = {4},

pages = {332--347},

publisher = {Inderscience Publishers},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Syed2025,

title = {Short-term solar irradiance forecasting using deep learning models},

author = {Saad Ahmed Syed and Wei Bin Chang and Humaira Nisar and Hannan Naseem Riaz and Kim Ho Yeap and Nursaida Mohamad Zaber},

editor = {H. Nisar and S. Sethupathi and Y.L. Pang and K.T. Tan and N. binti Abdul Aziz and K.M.C. Wong},

doi = {10.1051/e3sconf/202560303003},

issn = {2267-1242},

year  = {2025},

date = {2025-00-00},

journal = {E3S Web Conf.},

volume = {603},

publisher = {EDP Sciences},

abstract = {Population growth and evolving consumer technology have resulted in an ever-increasing demand for energy and power. Traditional energy sources such as coal, oil, and gas are not only quickly depleting but have also contributed to global pollution. As a result, the demand for renewable energy for power generation has increased tremendously. Short-term solar irradiance is a critical area in renewable energy for the optimal operation and power prediction of grid-connected photovoltaic (PV) plants and other solar energy applications. However, solar irradiance is complex to handle due to the nonuniform characteristics of inconsistent weather conditions. Deep Learning techniques have shown outstanding performance in modeling these complexities. In this paper, short-term solar forecasting models are proposed using deep learning to reliably predict the amount of solar irradiance for optimal power generation. Furthermore, it is also evaluated whether the model can forecast the amount of Global Horizontal Irradiance (GHI) within one hour given the current recorded features including air temperature, azimuth, cloud opacity, and zenith. The data for Penang, Malaysia is used in this research. A Dense Neural Network (DNN) with 32 units achieved a validation MAE of 21.33 and MSE of 1343.68 in the 6th fold. Long-Short Term Memory (LSTM) with 256 units achieved a validation MAE of 8.23 and MSE of 246.98 in the 7th fold. On test data, the DNN achieved MAE and MSE of 31.71 and 2560.80 respectively whereas the LSTM model achieved MAE and MSE of 5.78 and 106.65 respectively.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ma2025,

title = {The predictive value of non-enhanced CT radiomics in differentiating early and advanced T-staging of colon cancer},

author = {Kun Ma and Haobo Shi and Tian Swee Tan and Jahanzeb Sheikh and Muhammad Amir As'ari and Yan Chai Hum and Wei Huang and Kah Meng Leong and Matthias Foh Thye Tiong and Zhibo Wen},

doi = {10.1097/md.0000000000042454},

issn = {1536-5964},

year  = {2025},

date = {2025-00-00},

volume = {104},

number = {20},

publisher = {Ovid Technologies (Wolters Kluwer Health)},

abstract = {This study aimed to assess the diagnostic value of non-enhanced CT radiomics in preoperatively differentiating early-stage (T1–T2) from locally advanced (T3–T4) colon cancer, addressing the limitations of conventional empirical staging. A retrospective analysis was conducted on 170 patients with surgically confirmed primary colon cancer who underwent non-enhanced CT scans within 1 week before surgery. Three-dimensional segmentation of colonic tumors was performed on the non-enhanced images, followed by automated extraction of radiomic features. Feature selection was executed using the minimum redundancy maximum relevance (mRMR) algorithm, and key features associated with cancer stage were identified using the least absolute shrinkage and selection operator logistic regression. The performance of the radiomics model was compared with conventional T-staging by radiologists. The cohort comprised 170 patients with an average age of 61.69 ± 13.22 years, 43.3% of whom were female, and 75 (44.1%) presented with early-stage disease. Eight radiomic features from non-enhanced imaging were ultimately included. The radiomics model achieved an area under the curve (AUC) of 0.85 (95% confidence interval: 0.78–0.92) in the training set and 0.84 (95% confidence interval: 0.74–0.95) in the test set, with corresponding accuracies of 0.70 and 0.78, sensitivities of 0.87 and 0.87, and specificities of 0.69 and 0.71, respectively. Additionally, in the training set, the radiomics model (AUC = 0.85) significantly outperformed empirical T-staging by radiologists (AUC = 0.71, P < .009). A similar trend was observed in the test set, where the radiomics model (AUC = 0.85) surpassed empirical T-staging (AUC = 0.76), although this difference was not statistically significant (P = .27). Non-enhanced CT radiomics demonstrated superior performance over conventional radiologists’ T-staging in distinguishing early from advanced colon cancer stages.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lim2024,

title = {Electrophoretically deposited graphene oxide/molybdenum disulfide composite on quartz crystal microbalance for ethyl acetate VOC detection},

author = {Wei Yin Lim and Choon-Hian Goh and Keenan Zhihong Yap and Narayanan Ramakrishnan},

doi = {10.1007/s10853-024-10465-2},

issn = {1573-4803},

year  = {2024},

date = {2024-12-00},

journal = {J Mater Sci},

volume = {59},

number = {46},

pages = {21277--21293},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kew2024,

title = {Machine learning and brain-computer interface approaches in prognosis and individualized care strategies for individuals with amyotrophic lateral sclerosis: A systematic review},

author = {Stephanie Yen Nee Kew and Siew-Ying Mok and Choon-Hian Goh},

doi = {10.1016/j.mex.2024.102765},

issn = {2215-0161},

year  = {2024},

date = {2024-12-00},

journal = {MethodsX},

volume = {13},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Deng2024,

title = {Stretchable liquid metal based biomedical devices},

author = {Yifan Deng and Fan Bu and Yujie Wang and Pei Song Chee and Xiangye Liu and Cao Guan},

doi = {10.1038/s41528-024-00298-z},

issn = {2397-4621},

year  = {2024},

date = {2024-12-00},

journal = {npj Flex Electron},

volume = {8},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractPursuit of improved living quality has stimulated great demand for high-performance conformal healthcare devices in modern human society. However, manufacturing of efficient, comfortable and stretchable biomedical apparatus faces huge challenges using traditional materials. Liquid metals (LMs) show remarkable potential to solve this problem due to their extraordinary biocompatibility, stretchability, thermal and electrical conductivity. In recent years, tremendous explorations have attempted to make stretchable biomedical devices with LMs. Herein, we review the stretchable LM-based biomedical devices on the topics of disease treatment and human function augmenting. The representative and up-to-date neural interfaces, alloy cement, e-vessels, soft heaters, exoskeletons, and e-skins are summarized. The existing issues of LMs applied for biomedical devices are also discussed. This review can provide guidance for the follow-up research in LM-based biomedical devices.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ooi2024,

title = {Non-invasive parameters of autonomic function using beat-to-beat cardiovascular variations and arterial stiffness in hypertensive individuals: a systematic review},

author = {Jia Hui Ooi and Renly Lim and Hansun Seng and Maw Pin Tan and Choon Hian Goh and Nigel H. Lovell and Ahmadreza Argha and Hooi Chin Beh and Nor Ashikin Md Sari and Einly Lim},

doi = {10.1186/s12938-024-01202-6},

issn = {1475-925X},

year  = {2024},

date = {2024-12-00},

journal = {BioMed Eng OnLine},

volume = {23},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {Abstract

                Purpose

                Non-invasive, beat-to-beat variations in physiological indices provide an opportunity for more accessible assessment of autonomic dysfunction. The potential association between the changes in these parameters and arterial stiffness in hypertension remains poorly understood. This systematic review aims to investigate the association between non-invasive indicators of autonomic function based on beat-to-beat cardiovascular signals with arterial stiffness in individuals with hypertension.

              

                Methods

                Four electronic databases were searched from inception to June 2022. Studies that investigated non-invasive parameters of arterial stiffness and autonomic function using beat-to-beat cardiovascular signals over a period of > 5min were included. Study quality was assessed using the STROBE criteria. Two authors screened the titles, abstracts, and full texts independently.

              

                Results

                Nineteen studies met the inclusion criteria. A comprehensive overview of experimental design for assessing autonomic function in terms of baroreflex sensitivity and beat-to-beat cardiovascular variabilities, as well as arterial stiffness, was presented. Alterations in non-invasive indicators of autonomic function, which included baroreflex sensitivity, beat-to-beat cardiovascular variabilities and hemodynamic changes in response to autonomic challenges, as well as arterial stiffness, were identified in individuals with hypertension. A mixed result was found in terms of the association between non-invasive quantitative autonomic indices and arterial stiffness in hypertensive individuals. Nine out of 12 studies which quantified baroreflex sensitivity revealed a significant association with arterial stiffness parameters. Three studies estimated beat-to-beat heart rate variability and only one study reported a significant relationship with arterial stiffness indices. Three out of five studies which studied beat-to-beat blood pressure variability showed a significant association with arterial structural changes. One study revealed that hemodynamic changes in response to autonomic challenges were significantly correlated with arterial stiffness parameters.

              

                Conclusions

                The current review demonstrated alteration in autonomic function, which encompasses both the sympathetic and parasympathetic modulation of sinus node function and vasomotor tone (derived from beat-to-beat cardiovascular signals) in hypertension, and a significant association between some of these parameters with arterial stiffness. By employing non-invasive measurements to monitor changes in autonomic function and arterial remodeling in individuals with hypertension, we would be able to enhance our ability to identify individuals at high risk of cardiovascular disease. Understanding the intricate relationships among these cardiovascular variability measures and arterial stiffness could contribute toward better individualized treatment for hypertension in the future.

                Systematic review registration: PROSPERO ID: CRD42022336703. Date of registration: 12/06/2022.

              },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ferdowsi2024b,

title = {Classification of vasovagal syncope from physiological signals on tilt table testing},

author = {Mahbuba Ferdowsi and Ban-Hoe Kwan and Maw Pin Tan and Nor’ Izzati Saedon and Sukanya Subramaniam and Noor Fatin Izzati Abu Hashim and Siti Sakinah Mohd Nasir and Imran Zainal Abidin and Kok Han Chee and Choon-Hian Goh},

doi = {10.1186/s12938-024-01229-9},

issn = {1475-925X},

year  = {2024},

date = {2024-12-00},

journal = {BioMed Eng OnLine},

volume = {23},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {Abstract

                Background

                The diagnostic test for vasovagal syncope (VVS), the most common cause of syncope is head-up tilt test (HUTT) assessment. During the test, subjects experienced clinical symptoms such as nausea, sweating, pallor, the feeling of palpitations, being on the verge of passing out, and fainting. The study's goal is to develop an algorithm to classify VVS patients based on physiological signals blood pressure (BP) and electrocardiography (ECG) obtained from the HUTT.

              

                Methods

                After 10 min of supine rest, the subject was tilted at a 70-degree angle on a tilt table for approximately a total of 35 min. 400 µg of glyceryl trinitrate (GTN) was administered sublingually after the first 20 min and monitoring continued for another 15 min. Mean imputation and K-nearest neighbors (KNN) imputation approaches to handle missing values. Next, feature selection techniques were implemented, including genetic algorithm, recursive feature elimination, and feature importance, to determine the crucial features. The Mann–Whitney U test was then performed to determine the statistical difference between two groups. Patients with VVS are categorized via machine learning models including Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), Multinomial Naïve Bayes (MNB), KNN, Logistic Regression (LR), and Random Forest (RF). The developed model is interpreted using an explainable artificial intelligence (XAI) model known as partial dependence plot.

              

                Results

                A total of 137 subjects aged between 9 and 93 years were recruited for this study, 54 experienced clinical symptoms were considered positive tests, while the remaining 83 tested negative. Optimal results were obtained by combining the KNN imputation technique and three tilting features with SVM with 90.5% accuracy, 87.0% sensitivity, 92.7% specificity, 88.6% precision, 87.8% F1 score, and 95.4% ROC (receiver operating characteristics) AUC (area under curve).

              

                Conclusions

                The proposed algorithm effectively classifies VVS patients with over 90% accuracy. However, the study was confined to a small sample size. More clinical datasets are required to ensure that our approach is generalizable.

              },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Voon2024b,

title = {IMAML-IDCG: Optimization-based meta-learning with ImageNet feature reusing for few-shot invasive ductal carcinoma grading},

author = {Wingates Voon and Yan Chai Hum and Yee Kai Tee and Wun-She Yap and Khin Wee Lai and Humaira Nisar and Hamam Mokayed},

doi = {10.1016/j.eswa.2024.124969},

issn = {0957-4174},

year  = {2024},

date = {2024-12-00},

journal = {Expert Systems with Applications},

volume = {257},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lee2024d,

title = {WiFi-Powered Sensor Integrated into a Smart Glove with a Fully Fabric Antenna for the Human–Machine Interface},

author = {Kok-Tong Lee and Eng-Hock Lim and Chun-Hui Tan and Jen-Hahn Low and Kwong-Long Wong and Cao Guan and Pei-Song Chee},

doi = {10.1021/acsami.4c12371},

issn = {1944-8252},

year  = {2024},

date = {2024-11-13},

journal = {ACS Appl. Mater. Interfaces},

volume = {16},

number = {45},

pages = {62914--62924},

publisher = {American Chemical Society (ACS)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lee2024c,

title = {A review on laser-induced graphene in flexible energy storage: From materials selection to biomedical applications},

author = {Soon Poh Lee and Pei Song Chee and Chun Hui Tan and Kwok Feng Chong and Eng Hock Lim and Cao Guan},

doi = {10.1016/j.cej.2024.156110},

issn = {1385-8947},

year  = {2024},

date = {2024-11-00},

journal = {Chemical Engineering Journal},

volume = {499},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}