The 50th International Exhibition of Inventions of Geneva

Surface Sampling and Packing System for Chang'E-5 and 6 Lunar Sample Return Missions

Principle Investigator:

Ir Prof. YUNG Kai Leung, Sir Sze-yuen Chung Professor in Precision Engineering, Director of Research Centre for Deep Space Explorations, Chair Professor of Precision Engineering and Associate Head of Department of Industrial and Systems Engineering

This Surface Sampling and Packing System, developed and manufactured by PolyU, collected over 1.5kg of surface samples on the lunar front side and 1.6kg on the far side, significantly contributing to our understanding of the universe. On the Chang’e-6 mission, it performed the historic first lunar far-side surface sampling.

The system includes two samplers, two high temperature nearfield cameras, and a sample packing system, designed to sample all types of lunar regolith. The packing system automatically performs all sample packing operations, such as unlocking after landing, lifting the container lid, swiping a funnel over the container to protect the rim from contamination while allowing smooth deposition of the sample into the container, sealing the container with the lid, and releasing the container for transfer to the ascender. The accompanying cameras provide visual guidance for sample acquisition, deposition, precision pickup of the container, and insertion into the ascender for return to Earth.

Hearing Hope: A Smart Sensor for Enhanced Safety and Precision in Hearing Restoration Procedures

Principle Investigator: 

Prof. TAM Haw Yaw, Chair Professor of Photonics, Department of Electrical and Electronic Engineering and Associate Director of Photonics Research Institute (PRI)

This medical device is designed to enhance surgical precision and minimise trauma during cochlear implantation procedures. It features an optical fibre sensor embedded within the electrode array of a cochlear implant, which is the most crucial component requiring precise insertion into the scala tympani. The optical fibre has specifically engineered novel structures to aid in the navigation of the electrode array during cochlear implantation.

Our invention tackles two main challenges: maintaining the contact force with the cochlear wall below the damage threshold to minimise trauma, and achieving an optimal insertion depth of approximately 20mm.

This innovative solution can be adapted for various medical applications, offering a versatile and advanced approach to improving the outcomes of delicate procedures. It sets a new standard for safety, precision and effectiveness in medical device placement, addressing key challenges in modern surgical practices.

Seeing the Invisible: Generating Non-invasive Angiography as an Alternative to Invasive Retinal Examinations

Principle Investigator:

Dr SHI Danli, Research Assistant Professor, School of Optometry

This innovation addresses diabetic retinopathy (DR), a leading cause of blindness, by replacing invasive and expensive fundus fluorescein angiography (FFA) with a non-invasive, cost-effective solution using generative artificial intelligence (GenAI). It converts colour fundus photography into high-resolution, realistic FFA images, preserving critical lesion details without the need for dye injections.

Our innovation also supports ultra-widefield imaging and dynamic lesion-preserving video generation. Validated by retinal specialists, our method enhances DR screening accuracy, reduces costs and improves patient comfort. Ongoing multi-centre clinical trials will assess the diagnostic performance, treatment outcomes and efficiency compared with traditional FFA.

This GenAI-driven innovation offers a safe, scalable and impactful solution that revolutionises DR evaluation, making the evaluation process more accessible and efficient in clinical practice.

A Customisable Wearable Saliva Sensing Platform

Principle Investigator: 

Prof. YAN Feng, Associate Director, Research Institute for Intelligent Wearable Systems; Chair Professor of Organic Electronics, Department of Applied Physics

This personalised, comfortable, saliva sensing platform integrates multi-gate organic electrochemical transistors, a wireless circuit, an ultrathin battery and a wearable substrate designed for intraoral use. Positioned near the sublingual glands, it ensures direct detection of fresh saliva, enabling real-time, continuous monitoring of critical biomarkers such as glucose, uric acid and lactate.

The platform effectively records dynamic changes in these metabolites during daily activities such as eating, drinking, running and working. Clinically, it has achieved accurate glucose monitoring, showing a strong positive correlation (90%) between fasting saliva and blood glucose levels in 500 subjects, including both diabetic and healthy individuals. This suggests that saliva glucose levels can non-invasively estimate fasting blood glucose.

The ability of the platform to track glucose variations in both saliva and blood offers a promising approach to non-invasive continuous glucose monitoring, marking a significant advancement in wearable sensors for personalised healthcare.

Smart Fire Extinguisher for Spacecraft

Principle Investigator:

Prof. HUANG Xinyan, Associate Professor, Department of Building Environment and Energy Engineering; Co-founder, Widemount Dynamics Tech Limited (a PolyU startup)

Water cannot be used to extinguish fires in spacecraft because suspended water droplets can cause short circuits. Our air vortex ring fire extinguishing device addresses this, using AI to automatically detect and target fires. It generates air vortex rings via a pressure regulation system to extinguish flames efficiently and autonomously. The vortex rings propagate stably in microgravity, offering stronger fire-extinguishing capabilities and better energy efficiency than traditional firefighting blowers.

The compact device is easy to integrate into various areas of a spacecraft. By using only ambient air as a medium, it avoids the storage space and residue issues associated with traditional fire extinguishers. It can also be combined with advanced systems such as carbon dioxide, inert gases, UAVs and robots to achieve superior results, enhancing the safety of space missions and astronaut well-being. By incorporating a vacuum pump, this technology can also be adapted for diverse firefighting scenarios on Earth.

CO₂-driven Superhydrophobic Carbon-sink Concrete

Principle Investigator:

Ir Prof. POON Chi Sun, Michael Anson Professor in Civil Engineering; Chair Professor of Sustainable Construction Materials; Head of Department of Civil and Environmental Engineering; Director of Research Centre for Resources Engineering towards Carbon Neutrality

The excessive emission of CO₂ poses a significant environmental challenge. Our CO₂-driven superhydrophobic carbon-sink foam concrete (SCFC) revolutionises the capture and use of carbon in construction.

By incorporating ultra-stable CO₂ foam – 50 times more stable than commercial alternatives – into a high-strength, low-carbon paste, SCFC achieves exceptional performance. The material captures over 100 kg of CO₂ per cubic metre through internal carbonation, creating a rough microstructure that enables superhydrophobicity, or water resistance.

SCFC offers more than three times the strength of traditional foam concrete, along with superior durability, self-cleaning capabilities, thermal insulation and soundproofing properties.

This innovation addresses critical environmental challenges by reducing carbon emissions while providing energy-efficient, sustainable solutions for modern green buildings. SCFC enhances structural performance and reduces ecological impact. It exemplifies multifunctional design for a low-carbon future.

Highly Integrated Wireless Ultrasonic Motor System for Fully Enclosed Environments

Principle Investigator:

Prof. CHAU Kwok Tong, Chair Professor of Electrical Energy Engineering, Department of Electrical and Electronic Engineering

How to control motor systems in fully enclosed environments without batteries, controllers or power cables? We present a highly integrated wireless ultrasonic motor system designed to wirelessly power and control motors in such environments. Our innovative system features a single integrated magnetic coupler connected to the motor, achieving remarkable simplicity and integration.

Key benefits:
• Battery and cable free: Eliminates the need for batteries and cables, reducing maintenance.
• Controller and sensor independence: Operates without additional controllers or sensors, streamlining design.
• Modular design: Easily adaptable to various applications, facilitating seamless integration.

Our system is ideal for environments where traditional cabling is impractical, such as in robotic arms, thereby enhancing mobility and flexibility. In enclosed environments such as underground pipelines or underwater propellers, it avoids complications from perforated installation cables, preventing gas or liquid leaks. This innovation offers new solutions for advanced applications in robotics and industrial automation.

High-efficiency GaN Converter Module for Wireless Power Transfer Facilities

Principle Investigator:

Prof. LIU Wei Lucian, Assistant Professor, Department of Electrical and Electronic Engineering

This invention integrates gallium nitride (GaN) chips into high-performance power converters, achieving low stray inductance and low switching loss for gate driver. The gate driver has minimal ringing and voltage overshoot, ensuring smooth switching characteristics of GaN switches. An insulated metal substrate printed circuit board design is used to lower thermal resistance while ensuring electrical isolation.

Compared with insulated-gate bipolar transistors, silicon-based metal-oxide-semiconductor field-effect transistors (MOSFET), or silicon carbide MOSFET converters, the GaN high-electron-mobility transistor (HEMT) offers higher efficiency, higher power density, and higher switching frequency. Additionally, compared with other GaN converters at the same power level, our invention offers better drive performance and lower cost, promoting the commercialisation of GaN–HEMT power converters.

This technology can be applied in various wireless power transfer facilities, including wireless charging for electric vehicles and other high-frequency, high-power-density wireless charging scenarios.

Highly Efficient Brushless Dual-rotor Contra-rotating Wind Power Generation System

Principle Investigator:

Prof. NIU Shuangxia, Professor, Department of Electrical and Electronic Engineering

The most common wind turbines on the market feature a horizontal-axis single-rotor design, which, according to Betz's theory, can extract a maximum of only 59% of the available wind energy. To effectively utilise this wake energy and enhance power generation, our invention introduces a compact, brushless, high-efficiency contra-rotating generator and systems, increasing wind energy utilization by 10%–20%.

Key benefits:
• Integrated and compact design: Unlike traditional dual-rotor systems with two separate units, our system integrates both into a single, compact structure, reducing space requirements and simplifying installation.
• Brushless and maintenance-free: The magnetic-geared structure eliminates mechanical wear, ensuring long-term, maintenance-free operation.
• Improved energy conversion efficiency: Contra-rotating rotors boost energy conversion rates, increasing wind energy utilization by 10%–20%.

This technology doubles the induced voltage at low wind speeds, reduces system volume, and greatly improves wind energy efficiency, making it ideal for residential and commercial applications.

SweatMD: Health-monitoring Wearable Sweat Sensor

Principle Investigator: 

Prof. SHOU Dahua, Associate Director of PolyU-Xingguo Technology and Innovation Research Institute, Associate Director of Research Centre of Textiles for Future Fashion, Limin Endowed Young Scholar in Advanced Textiles Technologies, Associate Professor, School of Fashion and Textiles

SweatMD is a cutting-edge, all-textile wearable sensor that noninvasively tracks biomarkers in sweat, such as glucose and potassium ion levels. It decodes health conditions at the molecular level with exceptional accuracy, comfort and durability.

By continuously detecting multiple biomarkers and displaying real-time data on an intelligent mobile app, SweatMD empowers users to seamlessly monitor their health metrics and gain valuable insights into their well-being. The innovative textile-based microfluidic design features a nature-inspired sweat collection system, enabling the rapid and directional transport of fresh sweat for precise analysis – even against gravity. Advanced electrochemical sensing yarns, wrapped in skin-friendly fibres, further ensure superior durability and comfort.

This breakthrough technology sets new standards in wearable healthcare, revolutionising how individuals manage their well-being while fostering global awareness. By combining accessibility, user-friendliness and comfort, SweatMD has the potential to transform disease prevention and health management strategies on a global scale.

Radome Assessment and Transmission Test System (RATTS)

Principle Investigator:

Mr Robert VOYLE, Chief Executive Officer, Aviation Services Research Centre (ASRC)

The Aviation Services Research Centre (ASRC) has developed a device to test the transmittance of aircraft radomes. Radomes, which protect radar equipment, are prone to damage and need regular maintenance. Traditional radome testing requires high-power radar and a testing distance of 50 metres, which is costly and space-consuming.

To address this, ASRC has developed a compact, low-cost system that evaluates radome transmissivity and displays the results as a heat map. The system uses a low-power vector network analyser to provide signals for the radar antennas, which are mounted on two robots. The system includes a turntable to scan the entire radome surface. By simulating the weather radar aperture, the system calculates the average transmittance of the radome in 45 specific test directions.

This new system is significantly more affordable, costing about 10% of traditional systems. Its small size makes it suitable for use in workshops.

A Multi-objective Yaw-control System for Wind Farm Optimisation Based on Novel 3D Wake Model

Principle Investigator: 

Ir Prof. YANG Hongxing, Professor, Department of Building Environment and Energy Engineering

This digital yaw optimisation system is designed for large-scale wind farms. It combines an innovative 3D yaw wake model with a machine learning module to accurately calculate power and loads based on given yaw angles. The system then uses multi-objective optimisation strategies to balance energy output and structural loads. Currently, it is at Technology Readiness Level 6.

For the 60-turbine Princess Amalia Wind Farm, located offshore of IJmuiden in the Netherlands, our system can increase power production by up to 8.79% in the main wind direction. It is effective for both upgrading the performance of existing wind farms, and in the early design phase of new wind farms, enabling optimised wind turbine locations and energy capture from the outset.

Our invention improves the operational efficiency and reliability of wind farms, offering significant economic and social benefits for wind power development.

AI-empowered Digital Twin for Smart Building Management

Principle Investigator:

Prof. XIAO Fu, Associate Dean, Faculty of Construction and Environment and Professor, Department of Building Environment and Energy Engineering

The building sector is the largest contributor to global energy demand and greenhouse gas emissions, significantly impacting climate change. Advanced technologies such as artificial intelligence (AI), digital twin (DT), the Internet of Things (IoT), and augmented/mixed reality (AR/MR) are transforming building operations. An innovative AI-powered digital twin management platform offers a transformative approach to smart building management. It optimises energy efficiency, reduces carbon emissions and enables predictive maintenance, all while ensuring optimal indoor comfort and air quality.

By seamlessly integrating DT, AI, IoT and AR/MR technologies, our platform provides real-time operational insights that empower building managers to make informed decisions. It has achieved over 20% energy savings in long-term trials, from single buildings to building clusters.

Designed for desktop and MR devices, the platform will soon expand to mobile, setting a new benchmark in sustainable building management.

Multi-mode Optical Characterisation Interferometer (MOCI)

Principle Investigator:

Ir Prof. CHEUNG Chi-fai Benny, Chair Professor of Ultra-precision Machining and Metrology, Department of Industrial and Systems Engineering and Director of State Key Laboratory of Ultra-precision Machining Technology

Optical characterisation is essential for determining whether an optical system or element meets specific performance requirements. This process has wide applications in various industrial fields. However, many existing optical characterisation instruments can only measure individual optical parameters for specific industrial fields.

This invention introduces a novel multi-mode optical characterisation interferometer (MOCI). Based on wavefront and shear interferometry measurement principles, the MOCI uses light wavefronts to determine the optical properties of materials. These properties affect the functional performance of an optical system or element.

The MOCI offers versatile measurement capabilities, allowing it to evaluate multiple optical properties in a single instrument. It can be used across different applications, including power maps, cylindrical distribution, and astigmatism axis for optometry products including myopia defocus spectacle lenses. Additionally, it assesses phase distributions, reflective index and modulation transfer function for metastructures, and evaluates the surface roughness and flatness of wafers for semiconductor applications.

Smart Structural Integrity Monitoring System

Principle Investigators:

Sr Prof. WONG Man Sing Charles, Associate Dean, Faculty of Construction and Environment; Associate Director, Research Institute for Sustainable Urban Development and Professor, Department of Land Surveying and Geo-Informatics

Mr CHAN Pak Kwan, Managing Director & Co-founder, LeafIoT Technology Limited (a PolyU startup)

The Smart Structural Integrity Monitoring System (LiFY-S) was co-developed by LeafIoT and the Drainage Services Department of the Hong Kong Special Administrative Region to enhance construction site safety. This cutting-edge solution revolutionises structural monitoring by integrating Artificial Intelligence of Things (AIoT) sensing, big data analytics, structural simulation, and digital twin technology, transforming traditional surveying methods into a real-time continuous monitoring system with a developed sensitivity six times greater than conventional techniques.

Key components of LiFY-S include real-time displacement monitoring sensors that precisely measure structural micromovement; a centralised AIoT cloud platform for monitoring structural health and integrity; and seamlessly integrated with smart watches that deliver early warning alerts to design and construction teams on excessive movement, ensuring timely communication and investigation.

LiFY-S optimises resource allocation in structural health monitoring, greatly reducing deployment costs to less than 30% of traditional manual surveying while significantly improving operational efficiency and site safety. As a transformative solution for the construction industry, LiFY-S sets a new benchmark for safety, efficiency, and innovation in structural integrity management.

Artificial Reef for Oyster Reef Restoration in Topological Approach

Principle Investigator:

Mr Dean CHAN, PolyU School of Design alumnus; Engineer, Team Orz Limited (a PolyU startup)

This project aims to restore ecosystems through innovative topological artificial oyster reefs, improving water quality and promoting marine biodiversity. The artificial oyster reefs use specially designed structures to mimic the function of natural oyster reefs, providing habitats for marine life and helping filter harmful substances from the water.

These reef structures feature a unique topological design that enhances oyster growth rates and contributes to improving the marine environment. Our solution combines eco-friendly technology and innovative design, using recyclable materials in 3D printing to achieve cost-effective and efficient ecological restoration.

In addition to restoring marine ecosystems, this project also includes long-term water quality monitoring. The reef structures are equipped with water quality monitoring systems that can track various indicators in real time, such as water temperature, salinity, and pH levels. The data is relayed to a control panel, providing continuous support for ecological environment data. We plan to conduct trials in real marine areas to verify the effects of water quality improvement and use this as a basis to promote larger-scale applications.

Our product not only effectively improves water quality but also positively impacts local biodiversity, offering a sustainable solution for the marine conservation sector.

Behaviour Recognition Method, Device and Wearable Device

Principle Investigators:

Prof. Mingguang HE, Henry G. Leong Professor in Elderly Vision Health and Chair Professor of Experimental Ophthalmology, School of Optometry; Director of Research Centre for SHARP Vision

Dr TO Yuen Ying Elaine, Postdoctoral Fellow in Ophthalmology, School of Optometry

We have developed a smart health-monitoring watch and platform that analyses multiple types of data in real-time, providing alerts on health patterns, events and behavioural changes.

The core of the system features an intelligent health-monitoring technology designed to recognise and process multiple sources of data in real-time. It continuously monitors a diverse range of sensor inputs, including non-identifiable sound, GPS, accelerometer and photoplethysmography (PPG), and sends the data to a cloud-based 4G network.

Using deep learning, the system analyses behavioural patterns, health fluctuations and specific health events, presenting its findings through a visual alert interface to provide users with immediate feedback.

Last-centimetre Drone Delivery in Urban Environments

Principle Investigator: 

Prof. HUANG Hailong, Assistant Professor, Department of Aeronautical and Aviation Engineering

Drone flight in urban areas is challenging due to the unreliable and inaccurate Global Navigation Satellite System service. This innovation includes hardware and algorithms that enable drones to deliver parcels directly to apartment balconies using Light Detection and Ranging (LiDAR), which does not require human intervention. The key features include:

• An advanced perception algorithm, enabling precise localisation for both drone and balcony, significantly enhancing landing accuracy.
• A LiDAR-based obstacle detection algorithm that does not rely on pre-training, making it versatile and adaptable to various scenarios.
• A robust control algorithm for stability and safety, enabling the drone to navigate with precision through disturbances such as wind.

This comprehensive solution integrates cutting-edge perception, obstacle detection and control technologies, enabling seamless parcel delivery and safe drone operation in complex urban environments.

IHAC Film: Intelligent Humidity Control and Atmospheric Water Collection Film

Principle Investigator: 

Prof. YAN Jinyue Jerry, Chair Professor of Energy and Buildings, Department of Building Environment and Energy Engineering

Intelligent Humidity Control and Atmospheric Water Collection Films (IHAC films) manage humidity and supply fresh water without using energy. They combine hydrophilic PAN/CNT nanofiber layers with water-retaining PAM hydrogels, offering exceptional water adsorption and storage. These lightweight, portable and cost-effective ($16.94/m²) films are scalable and durable in various conditions.

IHAC films significantly outperform traditional dehumidifying materials, they reduce humidity from 90.7% to 21.6% in one hour and produce freshwater yield of 1.1kg/m² daily. Unlike conventional methods, IHAC films require no external energy to operate and prevent bacterial growth. They also contribute to environmental sustainability by lowering energy consumption by 30 kWh/(year·m²) and CO₂ emissions by 16.5kg/(year·m²).

IHAC films enable energy-free humidity control and clean water in both indoor and outdoor settings, fostering plant growth, reducing CO₂, and improving air quality. With a remarkably fast cost recovery period of just 48 days, this approach shows great promise for broader applications.

Intelligent Construction Site Layout Design Platform

Principle Investigator:

Dr WANG Dong, Postdoctoral Fellow, Department of Building and Real Estate; Founder, ICC (Hong Kong) Limited (a PolyU startup)

This invention is the world’s First Generative AI-powered Design Platform for generating optimal crane and site layouts in construction projects. This innovative tool streamlines the traditionally labour-intensive decision-making process, offering the following significant benefits:

• Accelerates the design process by over 90%
• Lowers collision risks on site by 59%
• Improves operator's visibility by 49%
• Enhances crane operation efficiency by 27%
• Reduces module installation degrees by 26%
• Reduces carbon emissions by 800kg

Our platform provides engineers with multiple design channels, including local software, online platforms and CAD plugins. Engineers can further customise their designs based on the real-time visualised effects of the AI-generated solutions.

This invention is set to revolutionise traditional manual site layout design practices, advancing the construction industry towards enhanced safety, increased productivity and greater sustainability.

AI-based Railway Obstacle Intrusion Detection System with Multimodal Transformers

Principle Investigator:

Ir Prof. NI Yiqing, Yim, Mak, Kwok & Chung Professor in Smart Structures; Chair Professor of Smart Structures and Rail Transit; Director of National Rail Transit Electrification and Automation Engineering Technology Research Centre (Hong Kong Branch); Director of The Hong Kong Polytechnic University-Hangzhou Technology and Innovation Research Institute

Rail accidents caused by obstacles on the tracks are a major concern. Developing intelligent obstacle intrusion detection systems (OIDS) is crucial for train safety. Our advanced OIDS has three main components: (1) sensors, including a camera and LiDAR, (2) a real-time data collection and warning module, and (3) a transformer-based detection model.

First, the visual sensors are calibrated for optimal performance and mounted on locomotives. The collected multimodal data are then synchronised and fed into the transformer-based detection model. This model extracts features from both images and point clouds, detecting obstacles that are currently or potentially encroaching on the rail area by analysing the combined data. Based on the detection results, real-time warnings are sent to operating trains to prevent potential accidents.

The transformer model is trained using both real and synthetic samples in different weather and lighting conditions, enhancing the robustness and versatility of the OIDS in diverse scenarios.

LungRT Pro: Advanced Radiotherapy Support System

Principle Investigator: 

Prof. CAI Jing, Head and Professor, Department of Health Technology and Informatics; Technical Advisor, InsightRT Limited (a PolyU startup)

Our product enhances lung radiotherapy by automating the analysis of patient CT images and simplifying clinical procedures. With just a few clicks, it identifies organs and creates lung ventilation and perfusion maps, providing a comprehensive visual representation of lung function. This streamlined process helps clinicians make informed treatment decisions, improving patient outcomes.

The product uses cutting-edge image processing algorithms and AI techniques to ensure high accuracy and consistency. It features a user-friendly interface, a powerful backend, and 3D visualisation capabilities. Automating manual tasks reduces workload and minimises human error.

Designed with functionality and user experience in mind, our product is compatible with major operating systems and is distributed digitally, reducing environmental impact. Its innovative combination of automation, advanced visualisation and broad accessibility makes it a valuable tool in lung radiotherapy. It enhances precision and effectiveness, contributing to improved patient care.

Virtual Patient Simulation System

Principle Investigator:

Prof. CHAN Wing Chi Lawrence, Associate Professor, Department of Health Technology and Informatics; Founder, Advantage Data Vision Limited (a PolyU startup)

This invention is an algorithm that generates synergistic markers to predict treatment outcomes, such as cancer treatment responses and relapse. Using genomic (DNA) or phenotypic (observable traits) data, the Virtual Patient Simulation System simulates clinical outcomes with probability estimates and decision curve visualisations. The system is compatible with high-end standalone workstations and cloud platforms, offering flexibility and scalability.  Key advantages include personalised treatment planning, faster clinical decision-making, and improved patient outcomes by reducing trial-and-error approaches.

By providing accurate, data-driven insights, the system helps healthcare providers optimise treatment strategies, reduce costs, and enhance overall healthcare efficiency.

Our invention has the potential to revolutionise personalised medicine, enabling more precise, effective treatments and improving overall care management. It empowers clinicians to make more informed decisions, ultimately leading to better patient care and outcomes.

EmoFriends

Principle Investigator:

Prof. WANG Jia Stephen, Professor, School of Design

EmoFriends is a modular toolkit that transforms plush toys into intelligent companion robots. Using patented Emosense technology, it tracks stress through touch and delivers AI-driven, personalised, emotion-aware conversations and haptic stimulation. The modular design allows easy integration into any plush toy, making it accessible and customisable for a range of users.

The toolkit features advanced stress tracking, emotion-aware AI conversations, haptic stimulation and modularity for seamless customisation. The intuitively-designed technology is the first to understand emotional states through touch, and is adaptable across various plush toys. The modular components, made from TPU via injection moulding, ensure durability and scalability for mass production.

EmoFriends provides stress management, emotional support and companionship in a comforting, relatable form. It tackles the global stress epidemic by offering a unique, accessible tool for mental health support. It improves emotional well-being, fosters trust and user engagement, while its sustainable design enhances its societal and environmental value.

The EyeFatigue Tracker: Exploring Visual Health through Wearable Devices and Deep-learning Technology

Principle Investigator:

Dr CHEN Yanxian, Research Assistant Professor, School of Optometry

The EyeFatigue Tracker is a diagnostic tool designed to objectively measure and manage visual fatigue. It features advanced capabilities such as eye movement analysis, blink pattern detection and pupil size monitoring, along with critical flicker fusion technology for precise fatigue assessment. The interface is easy-to-use and tailored for clinical settings.

The EyeFatigue Tracker has several advantages over traditional methods. It delivers objective data for accurate diagnosis and supports pre- and post-treatment comparisons to effectively monitor progress. Additionally, its portable design allows for versatile use in hospitals, clinics and research labs.

Its benefits include enhancing diagnostic accuracy, enabling personalised treatment approaches, saving time, and improving patient outcomes. By integrating objective metrics and streamlining clinical workflows, the EyeFatigue Tracker revolutionises visual fatigue assessment and ultimately enhances patient care. Its introduction paves the way for wider adoption of standardised fatigue measurement tools in healthcare, promising a more effective approach to fatigue management.

STARS: Smartphone AI Refraction System

Principle Investigators:

Prof. DO Chi Wai, Associate Professor, School of Optometry
Prof. Grace NGAI, Associate Professor, Department of Computer

STARS is an AI-powered smart system for the early detection and simplified monitoring of myopia, lazy eye risks and strabismus for our next generation. Unlike traditional exams that require professional training and the use of bulky and expensive instruments, STARS offers a compact, user-friendly solution. Its multi-lingual interface makes vision screenings accessible and easy for anyone to use, especially benefitting those in remote and developing regions.

Developed and patented by PolyU, the AI algorithms in STARS are continuously optimised using large data sets. With deep learning, the technology becomes increasingly precise over time.

Our AI-assisted photorefraction ensures precision and user comfort. Built on more than 30,000 real-life clinical eye profiles, our algorithms enable STARS to quickly provide reliable and reproducible results.

Suture Anchor-Tendon Hybrid Graft

Principle Investigator:

Prof. Elmer Dai Fei KER, Associate Professor, Department of Biomedical Engineering

This bone-tendon graft combines a suture anchor and tendon graft to restore biomechanical function. Our simple approach uses a single stem/progenitor cell treated with the same biochemical cues to simultaneously generate fibrocartilage and tendon, enhancing biological healing.

Mechanically, combining a suture anchor with a tendon graft reduces potential failure points, such as suture breakage at the anchor eyelet. This was not possible with previous devices, which lacked our biocompatible, photocrosslinkable material. This material’s properties can be adjusted to approximate the mechanical properties of bone and tendon. Biologically, our straightforward method streamlines the regulatory approval process by using only one cell type and inducer to produce both fibrocartilage and tendon.

This invention aims to revolutionise the century-old practice of using separate devices for bone-tendon repair, such as suture anchors for bone fixation and tendon grafts for tendon replacement. It shows promise for improving rotator cuff repair.

Advanced Self-cleaning Oil Fume Purification System for Commercial Kitchens

Principle Investigators:

Prof. LEE Shun Cheng, Professor, Department of Civil and Environmental Engineering; Technical Advisor, AeroGreen Technology Company Limited (a PolyU startup)

Dr LI Xinwei, Postdoctoral Fellow, Department of Civil and Environmental Engineering; Founder, AeroGreen Technology Company Limited (a PolyU startup)

Dr HAN Shuwen, Alumni, Department of Civil and Environmental Engineering; Chief Technology Officer, AeroGreen Technology Company Limited (a PolyU startup)

The Advanced Self-Cleaning Oil Fume Purification System for Commercial Kitchens offers an innovative solution for efficiently removing oil fumes. It features a self-cleaning mechanism, ensuring optimal performance with minimal maintenance. The system includes a cooking device and a purification unit with a rotatable carrier body that allows gas and liquid to pass through. An oil fume purification ring cleans fumes during rotation, with its inner cavity directed towards the exhaust for enhanced efficiency. A liquid supply provides cleaning liquid to the ring, while a suction component extracts and releases purified gas.

Our system effectively cleans oil fumes using a self-developed surface-active agent, achieving a purification efficiency of 60–80% for volatile organic compounds and 90% for particulate matter in commercial kitchens. This makes it a valuable addition to modern restaurants.

Next-generation Sportswear with Polylactic Acid, Auxetic Knitting Structure and Ergonomic Design

Principle Investigator: 

Prof. Erin CHO, Dean and Limin Professor in Integrated Strategies and Leadership in Fashion, School of Fashion and Textiles; Advisor, Leopitorca Global Limited (a PolyU startup)

Our ergonomic sportswear solution uses polylactic acid (PLA), a natural eco-substitute for polyester, combined with AKS textile engineering. This combination delivers improved shaping, support and fit without using Lycra or polyurethane, enhancing antibacterial properties, UV protection, flame retardancy, and temperature and moisture management.

The ergonomic construction maximises athletic performance by aligning with muscle groups, allowing full-range motion and effective temperature regulation. PLA is 100% sustainable, and the auxetic knitting structure ensures superior shaping, elasticity and support.

By using PLA and AKS, our solution offers better protection against bacteria. The ergonomic design provides a better-contoured fit, improving protection against injury and offering better body support.

Our solution improves environmental sustainability in textile production waste management and sportswear functionality. It enhances performance for athletes and physically fit individuals who exercise rigorously. It also improves the exercise experiences of individuals in less-than-perfect physical condition by providing better safety, functionality, support and fit.

3D-printed Superior Light and Breathable Wearable Textiles

Principle Investigator:

Prof. JIANG Shou-xiang Kinor, Professor, School of Fashion and Textiles

Our innovative 3D-printed material has fabric-like qualities, resulting in a flexible material that is lightweight and exceptionally breathable. The material is produced using the Low Force Stereolithography printing system with flexible photosensitive resin based on a 3D model, and consists of multiple unit structures systematically arranged along the X, Y and Z axes. Each unit structure features a cubic diamond configuration made of truss rods, with dimensions ranging from 2mm to 2.5mm in length, width and height, and truss rod diameters between 0.2mm and 0.3mm.

Incorporating a cubic diamond structure as the fundamental unit of the microcrystalline fabric significantly enhances its breathability, lightness, durability and aesthetic appeal. It also accommodates various body shapes and movement conditions, ensuring comfort and adaptability.

The material is soft and skin-friendly, offering breathability that surpasses traditional woven fabrics, and exhibiting excellent elasticity. This advancement significantly improves the performance and comfort of 3D-printed textiles.