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PolyU research and supported start-ups shine at Geneva Inventions Expo

  1. Novel High Efficacy Nano Multi-ring Defocus Incorporated Spectacle Lens for Myopia Control
  2. ABarginase: First-in-class Drug for Treatment of Multiple Obesity-related Metabolic Diseases
  3. Mars Landing Surveillance Camera for Tianwen-1 Mars Soft Landing Mission
  4. AI-Assisted Design of Functional Clothing for Scoliosis Treatment
  5. MicroGlue: Microbial-derived Technology to Remove Microplastic Pollutants
  6. A Novel Wireless Self-adaptive Hydropower Harvesting System for Applications in Urban Water Supply Pipelines
  7. Advanced Real-time Prediction and Early Warning System for the Spread of Emerging Pathogens
  8. A Sport-Specific Soft Manikin System for Sports Bra Design 
  9. Revolutionary Mussel-inspired Polyester for Next Generation Sportswear and Functional Clothing
  10. Safe and Eco-friendly Antimicrobial Materials with High Efficiency
  11. Advanced Intelligent System for Radiation-free Scoliosis and Posture Evaluation
  12. Novel AI Automated Histological System for Carcinoma Detection
  13. A Portable Non-invasive and Ultrasensitive Saliva Glucose Sensor
  14. Gold-LAMP: A Portable Ultra-fast Nucleic Acid Testing System
  15. High-throughput Microfluidic Platform for CTCs Detection in Cancer Precision Diagnostics
  16. Long-lasting Self-disinfecting Materials Technology
  17. Durable, High-Selectivity, and Energy Efficient CO2 Electroreduction System
  18. One-Stop Solution with AI Visual Object Recognition for 3D Model Generation
  19. PolyPi: Edge-AI Empowered Robot for Autonomous In-pipe Inspection
  20. BioCharttery: A Climate-smart and Carbon-negative Growing Material
  21. System for Evaluation and Triage for Healthy Knee
  22. All-in-one Luminescence-based Point-of-care Testing Device for Virus Diagnosis
  23. Mutual Cognitive Human-robot Collaborative Manufacturing System
  24. Novel Smart Precast Porous Road System Against Flooding
  25. The Fleming Ankle – Lightweight and Wearable Exoskeleton for Mobility Enhancement
  26. HiVE: Hybrid Immersive Virtual Environment
  27. Modular Rail Particle Damper for Noise and Vibration Reduction in Railways
  28. Food Waste-derived 3D Printing Material

Novel High Efficacy Nano Multi-ring Defocus Incorporated Spectacle Lens for Myopia Control

Principal Investigators:Prof. Benny CHEUNG Chi-fai, 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
Prof. TO Chi-ho, Visiting Chair Professor of Experimental Optometry, School of Optometry
Mr Jackson LEUNG Tze-man, Co-founder, Vision Science & Technology Co Ltd (a PolyU Academic-led startup)

The novel Nano Multi-ring Defocus Incorporated Spectacle (NMDIS) lens is an advanced spectacle lens designed to slow the progression of myopia in children. The NMDIS lens combines two cutting-edge technologies – the Defocus Incorporated Soft Contact (DISC) lens and Ultra-precision Nano Multi-ring Machining Technology (UPNMMT) – to produce high-quality lenses.

The NMDIS lens features annular spaced correction zones and defocus zones. The correction zones function as a regular concave lens to correct vision at the centre of the retina, while the defocus zones focus light slightly in front of the retina to achieve myopia defocus. This effectively inhibits elongation of the eyeball, slowing the progression of myopia.

UPNMMT enables the precision moulding of NMDIS lenses by fabricating the unique tangential continuity nano multi-ring structure on the moulds. By optimising the width and height of the defocus zones, it enables a reasonable distribution of optical power to generate a smooth and seamless lens surface, and strikes a good balance between clear vision, comfort, and myopia control for children.

 

ABarginase: First-in-class Drug for Treatment of Multiple Obesity-related Metabolic Diseases

Principal Investigators:Prof. Thomas LEUNG Yun-chung, Professor, Department of Applied Biology and Chemical Technology and Lo Ka Chung Charitable Foundation Professor in Pharmaceutical Sciences, The Hong Kong Polytechnic University
Prof. Alisa SHUM Sau-wun, Associate Professor, School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong

ABarginase is an albumin-binding recombinant human arginase that is engineered using an advanced fusion protein strategy. This allows for an inexpensive and highly efficient fabrication process, making ABarginase affordable and widely adoptable for clinical applications.

ABarginase has a long circulating half-life and strong enzymatic activity, which helps to maintain arginine, a semi-essential amino acid, in circulation at low levels. The research team discovered that arginine starvation suppresses fat synthesis, promotes fat breakdown, and sensitizes cells to insulin. This breakthrough has led to the development of the world's first therapy to safely and effectively treat multiple metabolic diseases related to obesity and insulin resistance, including prediabetes and type 2 diabetes, and nonalcoholic fatty liver disease via arginine starvation.

 

Mars Landing Surveillance Camera for Tianwen-1 Mars Soft Landing Mission

Principal Investigator:
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, Department of Industrial and Systems Engineering, PolyU

This is a space qualified camera designed for use on Mars. The camera has a wide temperature range, low distortion, an ultra-wide 170-degree diagonal field of view, and can withstand 6200g of shock, making it suitable for use in the harsh environment of Mars.

Despite weighing only 390 grams, the camera features innovative design elements such as integrated thermo-dissipation and layered metallic radiation protection with a flexible shock absorbing structure.

The camera successfully landed on Mars in 2021 on board the landing platform of Tianwen-1 lander. It monitored the landing status and the deployment of the Mars Rover, including the unfolding of the solar panels and antennas, and the readiness of the Rover to descend onto the surface of Mars.

The many innovations and key technologies developed for this camera have been transferred to special products on earth, such as surgery robotics, for the benefit of society.

 

AI-Assisted Design of Functional Clothing for Scoliosis Treatment

Principal Investigator: 
Dr Joanne YIP Yiu-wan, Associate Dean and Associate Professor, School of Fashion and Textiles

This new approach offers a promising solution for improving the treatment of scoliosis and enhancing the quality of life for adolescent idiopathic scoliosis (AIS) patients.

Traditionally, scoliosis braces have been designed and evaluated based on the experience of orthotists, which can be challenging. To overcome this challenge, this project uses AI to create a series of tailor-made functional clothing for treating AIS. Patient data is used to train a decision tree and three neural networks to prescribe and configure the brace, which is then customised by professionals.

Optimised designs, such as the placement of padding, tightness of elastic straps, and configurable 3D structures, are suggested to reduce the spinal curvature of AIS patients and improve the functionality and comfort of the functional clothing. As a result, the heavy and uncomfortable traditional brace can be replaced by a series of tailor-made functional clothing.

 

MicroGlue: Microbial-derived Technology to Remove Microplastic Pollutants

Principal Investigators: Dr CHUA Song-lin, Assistant Professor, Department of Applied Biology and Chemical Technology Dr LIU Yang, GBA Startup Postdoctoral Fellow, Department of Applied Biology and Chemical Technology

MicroGlue is a microbial biotechnology that offers a safe, low-cost and efficient way to remove microplastics from water. It uses biodegradable microbial-derived polymers that aggregate hard-to-remove microplastic contaminants into clumps that are easily separable and removable from the environment.

MicroGlue can be integrated into the final purification stage in wastewater treatment plants, or used as stand-alone solution in other scenarios involving polluted sea water or fresh water. It is scalable, simple to install into existing processes, and has low operating costs. This makes it a convenient way to retrieve microplastics for resource recovery and plastic recycling.

MicroGlue supports the UN’s Sustainable Development Goals, especially Life Below Water, and Clean Water and Sanitation. By reducing the unwanted release of microplastics into the environment, it helps limit the harmful effects of microplastics on humans and ecosystems.

 

A Novel Wireless Self-adaptive Hydropower Harvesting System for Applications in Urban Water Supply Pipelines

Principal Investigator: 
Prof. YANG Hongxing, Professor, Department of Building Environment and Energy Engineering

The Water Supplies Department (WSD) of the Hong Kong SAR Government is establishing a Water Intelligent Network (WIN) to manage water supplies and reduce water leakage from its pipelines. The WIN relies on data monitoring meters and sensors, which are usually powered by chemical batteries due to space and location limits.  However, batteries have a limited capacity and service life.  They frequently need replacing, which results in high maintenance costs and requires a lot of labour.

The Self-adaptive Hydropower Harvesting System addresses this challenge by generating electric power to supply the WIN from water pipelines while limiting water head loss. The 4th-generation innovative power harvesting system has been successfully tested on WSD water pipelines for over one year, demonstrating superior performance in providing a continuous and reliable power supply to the WIN and other potential users.

This innovative micro power generation system offers significant economic value compared with traditional chemical battery power, and has the potential for use in water pipelines in other cities. It offers a more sustainable and cost-effective solution for powering data monitoring meters and sensors in water pipelines, reducing maintenance costs and improving reliability.

 

Advanced Real-time Prediction and Early Warning System for the Spread of Emerging Pathogens

Principal Investigator: Prof. John SHI Wenzhong, Otto Poon Charitable Foundation Professor in Urban Informatics, Chair Professor in GISci and Remote Sensing, Director, PolyU-Shenzhen Technology and Innovation Research Institute (Futian), Director, Smart Cities Research Institute, Academician, International Eurasian Academy of Sciences, Fellow, Academy of Social Sciences (UK)

This newly developed platform has two key features. First, it can provide daily predictions of early risk, including the risk of symptom onset, for different variants of pathogens at different locations. Second, it can provide active early warning of high-risk locations.

The platform uses novel patented spatiotemporal epidemic prediction models and automatic data collection/prediction engines to make real-time predictions with high accuracy and fine spatial resolution. This can support government control measures during the early spread of emerging variants and help the public make safer travel plans.

Since its inception in 2020, the system has successfully tracked different SARS-CoV-2 variants and supported COVID-19 control measures around the world. During the early stages of the Omicron outbreak, research reports based on this system were highly praised by the World Health Organization. The system has been reported on by global media about 100 times, highlighting its significance in the fight against emerging pathogens.

 

A Sport-Specific Soft Manikin System for Sports Bra Design

Principal Investigator: Dr YICK Kit-lun, Associate Professor, School of Fashion and Textiles

This soft manikin system offers a complete solution and scientific guidelines for designing effective sports bras. It uses simulated human running motion and breast tissue to measure the performance and pressure of sports bras in a scientific, objective, and reliable way. By incorporating the biomechanics of breast motion, it provides a complete solution for evaluating the fit, comfort, support, and protection offered by sports bras.

The manikin, with its soft simulated skin and breast tissue, replaces the need for human bra fit trials, which can be subject to uncontrollable noise and variations. The system measures bra pressure and sensation comfort, while also tracking the 3D motion of the body and breasts to assess the breast control performance of sports bras in all directions (X, Y and Z).

The system provides bra designers with valuable insights into the design features, materials and performance of sports bras, helping to optimise breast protection and comfort.

 

Revolutionary Mussel-inspired Polyester for Next Generation Sportswear and Functional Clothing

Principal Investigator: Prof. John XIN Haozhong, Lee Family Professor in Fashion & Textiles, Chair Professor of Textile Chemistry, School of Fashion and Textiles

This invention makes polyester clothing more comfortable and healthier to wear. Normal polyester is not good at absorbing water, resisting odours or preventing the build-up of static electricity. This new technology overcomes these problems by adding a special polymer that was inspired by the way that marine mussels stick to rocks. The polymer forms a strong long-lasting bond with the polyester.

When the spray is applied to one side of the polyester, it creates a special one-way water and sweat transport effect. This means that water and sweat can be absorbed by the clothing and move away from the body, keeping the wearer dry and comfortable. As well as being both more comfortable and hygienic to wear, clothes made with this new technology can withstand over 100 laundry cycles.

This technology has opened new possibilities for making more comfortable and better-performing sportswear and other types of clothing.

 

Safe and Eco-friendly Antimicrobial Materials with High Efficiency

Principal Investigators: Prof. TAO Xiaoming, Director, Research Centre of Smart Wearable Technology, Vincent and Lily Woo Endowed Professorship in Textiles Technology, Chair Professor of Textile Technology, School of Fashion and TextilesDr ZHANG Ziheng, Postdoctoral Fellow, School of Fashion and Textiles, CEO, Ecolar Technology Limited (a PolyU Academic-led start-up)

Novel proprietary technologies have been developed to prepare highly-efficient, eco-friendly antimicrobial polyhydroxyalkanoate oligomers (PHAOs), which can be used as disinfectants, finishing agents for personal protective equipment, and in PHAO/PA blend yarns.

The new PHAO materials are fully biodegradable, transparent, non-toxic and non-allergic, with excellent wide-spectrum antimicrobial properties. They can achieve a high antimicrobial reduction of > 99.99% against S. Aureus, K. pneumoniae, C. albicans and Methicillin-resistant S. aureus, the COVID-19 virus, and the H1N1 and H3N2 viruses, indicating their promising application as medical materials.

Compared with current commercial antimicrobial agents, these new PHAO materials are more effective against microbes. They are also safer, more biodegradable, cheaper, and emit less carbon. PHAOs make possible a greener, safer, more hygienic, and healthier way of life.

 

Advanced Intelligent System for Radiation-free Scoliosis and Posture Evaluation

Principal Investigators: 
Mr Jackal XU Zhenda, PhD Student, Department of Computing, Founder, Zero Dynamic Medical Technology Company Limited (a PolyU Academic-led startup)
Prof. GUO Song, Professor, Department of Computing, Chief Scientist, Zero Dynamic Medical Technology Company Limited (a PolyU Academic-led startup)

This innovative edge intelligence system provides a radiation-free, non-contact and cost-effective way to screen, diagnose, monitor, and provide real-time treatment feedback for common spinal deformities in teenagers, such as adolescent scoliosis and spinal-related posture problems (e.g. thoracic kyphosis, lumbar lordosis). Traditional methods for screening and diagnosing scoliosis, such as manual school screening and X-rays, can be cost-ineffective and harmful.

The AI + 3D infrared imaging system is based on intelligent light sensing technology, topographical technology, and artificial intelligence algorithms. Users can conduct AI-based online scoliosis screening and monitoring by using edge devices, such as smartphones, from the comfort of their own homes. Patients can also use the 3D infrared imaging system during monitoring and rehabilitation for a more comprehensive evaluation, including 3D spine reconstruction, visualisation and measurement.

The system enables accurate, easy, and safe mass scoliosis screening, frequent monitoring of scoliosis progression, and treatment optimisation for spinal deformity diagnosis and treatment without the need for costly and potentially harmful traditional methods.

 

Novel AI Automated Histological System for Carcinoma Detection

Principal Investigator: 
Dr Martin YEUNG Ho Yin, Research Assistant Professor, Department of Health Technology and Informatics, Co-Founder, Anatomic Technologies Limited (a PolyU startup)

This AI solution provides a more efficient and accurate approach to cancer diagnosis. It predicts and prioritises carcinoma cases for histopathological analysis—a medical process that involves examining tissue samples under a microscope to identify the presence of abnormal or cancerous cells—without requiring pixel-level annotation. It uses a down-sampling method to transform massive image information into countable features for disease diagnosis, and presents a computer-aided diagnosis by measuring relative cell density with suspicious significant histological features.

The system also offers a method for histopathological triage systems before implementation in a digital pathology setting. It solves the problem of triaging biopsies in clinical settings, developing decision support system without pixel-level annotation, and providing a bio-interpretable heatmap for highlighting significant histopathological features. As it requires a smaller dataset and no pixel-level annotation, it is cost- and time-effective.

Future improvements include building, testing, and training models to include carcinoma classification according to WHO standards, and improving the precision and accuracy of carcinoma detection using existing segmentation algorithms.

 

A Portable Non-invasive and Ultrasensitive Saliva Glucose Sensor

Principal Investigator: Prof. YAN Feng, ADoRI-IWEAR & Chair Professor of Organic Electronics, Department of Applied Physics

This is a new type of ultra-sensitive glucose sensor that is portable, cost-effective, and non-invasive. It is based on a flexible organic electrochemical transistor (OECT), and can detect saliva glucose levels in real-time using a portable meter and a smartphone.

The sensor has a stable sensing performance and high selectivity and sensitivity, with a detection limit of approximately 10 nM. Clinical trials have shown a consistent relationship (deviation approximately 10%) between fasting saliva and blood glucose levels in hundreds of human subjects of different genders and ages, including both those with and without diabetes.

By using this biosensor to measure saliva glucose levels, it is possible to calculate the corresponding blood glucose level in a non-invasive way. This invention paves the way for non-invasive and continuous blood glucose monitoring through saliva analysis.

 

Gold-LAMP: A Portable Ultra-fast Nucleic Acid Testing System

Principal Investigators: 
Prof. YIP Shea-ping, Chair Professor and Head, Department of Health Technology and Informatics, Co-Founder, Pocnat Limited (a PolyU Academic-led startup)
Dr Thomas LEE Ming-hung, Associate Professor and Associate Head (Academic), Department of Biomedical Engineering, Co-Founder, Pocnat Limited (a PolyU Academic-led startup)

There is a pressing need for decentralised, on-site nucleic acid testing. The current nucleic acid testing gold standard is real-time polymerase chain reaction (qPCR). This is typically performed in centralised settings and involves the use of bulky, expensive instruments.

Gold nanoparticle-based loop-mediated isothermal amplification (Gold-LAMP) technology offers a portable, fast, low cost, and highly accurate alternative to qPCR. It uses surface-functionalised gold nanoparticles that appear as a red dispersion in a negative LAMP sample (without a target nucleic acid sequence), but as red precipitates in a positive LAMP sample (with a target nucleic acid sequence).

Real-time precipitation monitoring using a handheld instrument takes just 10–20 minutes. Clinical validation was conducted for on-site COVID-19 testing in a hospital accident and emergency department. Gold-LAMP achieved 98.4% sensitivity and 100% specificity with reference to qPCR for 61 positive and 216 negative specimens, with a total assay time of 25–45 minutes. This makes Gold-LAMP a more convenient and efficient testing method, especially for on-site and decentralised testing where rapid results are critical for effective disease control measures.

 

High-throughput Microfluidic Platform for CTCs Detection in Cancer Precision Diagnostics

Principal Investigator: Prof. YANG Mo, Associate Head (Research) and Professor, Department of Biomedical Engineering

Early detection of tumours can be challenging, but circulating tumour cells (CTCs) that shed from tumours and enter the bloodstream can be used as biomarkers for early detection. However, isolating and analysing CTCs in clinical samples is difficult due to their small population in the blood.

The nanosensor-integrated digital microfluidic flow cytometry (Nano-DMFC) platform addresses this challenge by accurately isolating CTCs from clinical samples within 10 minutes with a CTC purity greater than 95%. It can also detect multiple characteristic tumour miRNAs in single CTCs to determine tumour heterogeneity for cancer precision diagnostics.

The portable device offers high-throughput, and rapid, accurate detection and analysis of CTCs in clinical samples at the single cell level. It has high potential to significantly improve non-invasive early diagnosis and prognosis of cancer, providing a more effective and more efficient method for the early detection and treating of tumours.

 

Long-lasting Self-disinfecting Materials Technology

Principal Investigators: 
Dr Chris LO Kwan-yu, Associate Professor, School of Fashion and Textiles, Co-Founder, Immune Materials Limited (a PolyU Academic-led startup)
Prof. KAN Chi-wai, Professor, School of Fashion and Textiles, Co-Founder, Immune Materials Limited (a PolyU Academic-led startup)

Immune Materials Limited has developed the world's first antiviral 3D printing technology. The resulting products can effectively eliminate E. coli, Klebsiella pneumoniae and Staphylococcus aureus, and human coronavirus.

These innovative products have a long-lasting performance of over three years, and can be custom-designed to fit any shape or size for a wide range of applications. Their antiviral rate is impressive, with a 70% reduction in virus count within two minutes, and a 99.2% reduction within 20 minutes. This makes them highly effective in preventing the spread of viruses and bacteria in a range of settings, including healthcare facilities, schools, and public transportation.

The self-disinfecting technology can deploy in high-quality, soft, safe and non-toxic materials, such as vegan leather.
This invention represents a breakthrough in the fight against viruses and bacteria, providing a safe and effective solution for a wide range of industries and applications.

 

Durable, High-Selectivity, and Energy Efficient CO2 Electroreduction System

Principal Investigator: Prof. Daniel LAU Shu-ping, Head, Director of UMF, Associate Director of PRI, Chair Professor of Nanomaterials, Department of Applied Physics

Reducing CO2 emissions is crucial, and this electroreduction system is a promising solution. It comprises a sandwich-structured membrane-electrode-assembly with a combined anion- and proton-exchange membrane separating the cathode and anode.

The system can efficiently convert CO2 to C2H4 with a high selectivity of up to 50% Faradaic efficiency and remain stable for over 1000 hours. Furthermore, it involves no chemical input, only requiring pure H2O as the electrolyte. The lab operating current can even exceed 10 A, which means that the system can be easily scaled up to an industrial scale.

This CO2 electroreduction system is durable, energy-efficient, offers high selectivity, and can accelerate the development of CO2 electrocatalysis technology. It can potentially revolutionise modern fossil fuel energy systems, offering a promising solution for reducing CO2 emissions.

 

One-Stop Solution with AI Visual Object Recognition for 3D Model Generation 

Principal Investigators: 
Dr LI Yaxin, Postdoc Fellow, Department of Land Surveying and Geo-informatics, CEO, Micro Dimension Limited (a PolyU startup)
Prof. CHEN Wu, Head and Professor, Department of Land Surveying and Geo-informatics

Depending on who you listen to, the metaverse might be the future of art, entertainment, and even education. But before its full potential can be realised, a 3D scene that accurately represents the real world is needed. This requires a surveyor to collect 3D information using an expensive laser scanner and create the 3D mapping manually. This is both time-consuming and costly.

This new technology makes 3D virtual tours more accessible and affordable by removing the need for professional software and high-performance hardware. The system creates a nearly fully automatic workflow using a robot-based 3D model generation system and a browser-based visualisation platform. Using only an electronic device with a browser, such as a cell phone, tablet or computer, users can experience immersive virtual tours anytime and anywhere.

This technology has the potential to revolutionise the way we create and experience virtual spaces and paves the way for a future where the metaverse is a part of our daily lives.

 

PolyPi: Edge-AI Empowered Robot for Autonomous In-pipe Inspection

Principal Investigator: 
Prof. CAO Jiannong, Dean of Graduate School, Otto Poon Charitable Foundation Professor in Data Science, Chair Professor of Distributed and Mobile Computing, Director of Research Institute for Artificial Intelligence of Things (RIAIoT), Associate Director of University Research Facility in Big Data Analytics (UBDA)

The PolyPi robot is an innovative autonomous robot developed for pipeline inspection. This robot stands out due to its three key features: real-time AI-based detection, deformable robot mechanism design, and autonomous control. Using advanced Edge-AI technology, the defect detection AI models are optimized with compression and embedded in the robot, enabling it to detect pipeline defects in real-time. This feature makes the robot effective for use in challenging environments, such as underground or underwater pipelines. Besides, its unique deformable design allows it to adapt and navigate through various pipe structures, such as curved, distorted, cross-branch, and broken pipes. The robot's self-control algorithms enable it to navigate autonomously without the need for manual operation. Overall, the PolyPi robot provides real-time, effective, and efficient pipeline inspection, benefiting safer and more sustainable infrastructure in future smart cities.

 

BioCharttery: A Climate-smart and Carbon-negative Growing Material

Principal Investigators:
Prof. Daniel TSANG Chiu-wa, Professor, Department of Civil and Environmental Engineering, Co-Founder, BioCharttery Limited (a PolyU Academic-led startup)
Dr HE Mingjing, Research Associate, Department of Civil and Environmental Engineering, Co-Founder, BioCharttery Limited (a PolyU Academic-led startup)

The current fertiliser market is facing several challenges due to the negative impact of traditional fertilisers such as chemical fertilisers and compost on soil pollution. Chemical fertilisers and compost also have a high carbon footprint due to their energy-consuming production processes.

Moreover, the increasing demand for food and limited agricultural land has resulted in excessive fertiliser use, leading to soil degradation and reduced soil fertility. This situation is especially challenging in urban areas where maintaining green spaces requires effective soil conditioners, or on contaminated land such as mining sites where soil restoration is required.

Biocharttery has developed a patented thermochemical technology and machine learning process that turns food waste into a carbon-negative biochar soil conditioner. Biochar products have a highly porous structure, a large surface area, and other features that retain water, nutrients and microbes, activate the soil ecosystem, and adsorb pollutants. This significantly enhances long-term soil health, reduces maintenance and costs, and reverses soil degradation.

System for Evaluation and Triage for Healthy Knee

Principal Investigators: 
Prof. Amy FU Siu-ngor, Peter Hung Professor in Pain Management, Assoc. Head (RS) & Professor, Department of Rehabilitation Sciences
Prof. CHEN Changwen, Chair Professor of Visual Computing, Department of Computing

This smart ageing solution improves the quality of life of older adults. A mobile app uses vision computing technology to assess physical health to determine the risk of developing common degenerative diseases through simple and convenient tests. It recommends exercise programmes tailored to individual needs and provides regular evaluations to track progress.

The app has four main functions: (1) step-to-step instructions for performing walking, sit-to-stand, and knee bending tests using a mobile phone; (2) computing walking speed, knee angles, and number of sit-to-stands in 30 seconds; (3) categorising knee health into fit, marginal, and at-risk groups based on individual performance compared to those of similar age and gender, and suggesting appropriate exercise/physical activities; and (4) tracking changes in knee health over time.

The app offers fast and easy screening, precise recommendations, and tracking of changes to monitor and improve knee health.

Knee pain can hinder mobility and affect quality of life for older adults. The app promotes early identification, intervention with precision medicine, helping to promote healthy living and reduce medical burdens.

 

All-in-one Luminescence-based Point-of-care Testing Device for Virus Diagnosis 

Principal Investigator: Prof. HAO Jianhua, Chair Professor of Materials Physics and Devices, Department of Applied Physics

Rapid and reliable virus detection is critical to defending ourselves from grave threats, but conventional detection techniques are either slow (PCR testing) or have limited sensitivity (RATs). More importantly, relying solely on one diagnostic method cannot provide a complete picture of the infection.

Unlike conventional techniques, this all-in-one point-of-care diagnostics platform detects all nucleic acids, antigens and antibodies in a single testing device, providing a more comprehensive and complementary diagnostic approach. This helps provide the full spectrum of information about infected patients, leading to more rapid and accurate diagnosis, and enabling better clinical treatment and infection control for different viruses.

The platform works with Bluetooth technology, allowing for rapid data transmission, thus reducing the risk of viruses spreading in the community.

This all-in-one point-of-care viral-testing device is highly accurate, rapid, and low-cost. It offers an early diagnosis scheme that can guide clinical treatment, infection control, and vaccine development for different viruses.

 

Mutual Cognitive Human-robot Collaborative Manufacturing System

Principal Investigator: Ir Dr ZHENG Pai, Assistant Professor, Endowed Young Scholar in Smart Robotics, Department of Industrial and Systems Engineering, Co-founder, CobotAI Limited (a PolyU Academic-led start-up)

This innovative technology offers a promising mutual-cognitive human-robot collaborative manufacturing system (MCHRCMS), that provides a safer and more intuitive way for humans and robots to work together. Its main features and advantages include:

  • Vision-based HRC holistic scene perception. Advanced machine learning techniques accurately predict human intentions, estimate object 6DoF positions, and segment the 3D working environment with an average accuracy rate of over 97%.
  • HRC safe interaction strategies. Digital twin and augmented reality (AR) technologies are adopted to ensure human-robot safety and prevent collisions. The system leverages deep reinforcement learning and inverse kinematics to plan robot motions and avoid errors with an accuracy rate of over 99.5%.
  • AR deployment of visual reasoning-based cognitive decisions. AR provides intuitive support for HRC instructions with an overall response time of less than 0.6s, making the system friendly to use.

This technology can be well-adopted in human-robot symbiotic manufacturing scenarios under Industry 4.0/5.0.

 

Novel Smart Precast Porous Road System Against Flooding

Principal Investigator:

Prof. WANG Yuhong, Professor, Department of Civil and Environmental Engineering

This precast modular road system is designed to replace conventional roads. Its features include a surface-induced drainage cover, filters in the drainage cover, a porous road base structure, and an optional IoT-based sensing subsystem for flood warnings.

The drainage cover features surface textures produced with 3D printing technology to direct rainwater flow, improve driving safety, and reduce traffic noise. The filter removes sediments from stormwater runoffs to prevent clogging and reduce water pollution.

The porous road base structure features optimised cavities to detain stormwater and spread heavy traffic loads. With the increasing frequency and intensity of heavy rainfall, extreme heat, and prolonged droughts due to climate change, the detained water can help mitigate flooding risks, cool road surfaces, and discharge gradually into natural bodies of water.

The light-weight, modular construction improves constructability and saves costs.

 

The Fleming Ankle – Lightweight and Wearable Exoskeleton for Mobility Enhancement

Principal Investigator: Dr Kelvin HEUNG Ho-lam, Research Assistant Professor, Department of Building and Real Estate, Co-Founder & CTO, Fleming MedLab Limited (a PolyU Academic-led startup)

This medical robotics start-up focuses on stroke rehabilitation using patented technologies based on neuroscientific principles and soft robotics. Fleming Ankle is a lightweight, easy-to-use, medical-grade, wearable robot that helps stroke patients rebuild neural pathways, and regain mobility and independence.

Sensors in the device can analyse the wearer’s intention to walk by detecting muscle movements and the electrical current inside those muscles. The soft robot at the ankle joint then exerts force to support the patient’s movement. At the same time, therapists can track patients’ rehabilitation progress through the device’s software and create appropriate rehabilitation plans.

Fleming Ankle is ready for a soft launch in this year, in collaboration with rehabilitation centres, physiotherapy clinics, and hospitals. The wearable robot is expected to be more affordable than similar products on the market, making it accessible to a wider range of patients.

 

HiVE: Hybrid Immersive Virtual Environment

Principal Investigators:  Dr Jacky CHUNG Kin-hung, Senior Engineering Manager (Building Services, Construction & Safety), Industrial CentreDr Kevin WONG Ka-fai, Senior Engineering Manager (Building Services, Construction & Safety), Industrial Centre

Hybrid Immersive Virtual Environment (HiVE) is the world’s first large-scale X-Reality hybrid classroom that uses fully immersive Cave Automatic Virtual Environment (CAVE) technology for practical and collaborative learning.

  • Fully immersive experience 6-sided CAVE: The 6-sided CAVE projection technology creates an extremely real immersive 2D or 3D environment to help students visualise abstract concepts and novel points of view that are impossible to display in a real environment.
  • Trapezoidal CAVE design: The inclined upper screen of trapezoidal CAVE conceals an empty projection area in the corner of the ceiling, enabling low-cost ultra-short throw projectors to achieve high-quality images comparable to high-end commercial-grade projectors.
  • Seamless transition of teaching mode: Hybrid CAVE allows teachers to seamlessly switch between face-to-face and immersive teaching, blending virtual technology with conventional learning.
  • X-Reality simulation for practical learning: X-Reality enables users to interact with real or digital objects simultaneously in a virtual environment for hands-on practical learning.
  • Multi-CAVE platform for collaborative learning: The Multi-CAVE Platform enables real-time interaction between geographically dispersed teams, allowing multiple student groups to work synchronously in the same virtual environment.

Modular Rail Particle Damper for Noise and Vibration Reduction in Railways

Principal Investigators: Prof. NI Yi-qing, 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)Dr AO Wai-kei, Research Assistant Professor, Department of Civil and Environmental Engineering

The modular rail particle damper (MRPD) is a novel rail damper that combines particle damping technology with a modular design. By adjusting the particle content in the damper, the MRPD can be tuned to target frequencies, effectively controlling rail vibration and rolling noise in the 1000-2000 Hz frequency range.

The MRPD is a lightweight alternative to the tuned mass damper. Content can be conveniently added to or removed from the damper without the use of heavy mass, thus solving the problem of less effective tuning mass in passive tuned mass dampers (PTMDs). The MRPD is also insensitive to extreme temperatures, ensuring long-term durability for rail applications.

This technology has the potential to reduce maintenance costs, increase rail lifespan, and benefit the local and global rail industry by reducing noise pollution at source. The development of the MRPD is crucial for addressing noise pollution, and can deliver multiple benefits to the rail industry.

 

Food Waste-derived 3D Printing Material

Principal Investigators: 
Prof. WONG Ka-hing, RiFood, Director, Research Institute for Future Food, Professor, Department of Food Science and Nutrition
Prof. Daniel TSANG Chiu-wa, Professor, Department of Civil and Environmental Engineering, Core Member, Research Institute for Future Food

This invention offers a promising way to reduce food waste while providing a sustainable filling material for 3D printing with many applications.

Food processing by-products, which are produced in large quantities worldwide, can be used as a sustainable filling material in the production of sustainable composites. Spent coffee grounds (SCG) and spent tea leaves (STL) are used to create food waste-polylactic acid (PLA) composite filaments that can be used in fused deposition modelling (FDM), the most popular 3D printing technology today. These FDM filaments can contain up to 40% food waste without compromising printability. They have a tensile strength of 10 - 40 MPa, making them suitable for a wide range of applications, such as modular furniture and display articles.

The sustainable FDM filaments can be customised to provide excellent ductility, which enables the printing of shock-absorbing designs. To ensure a low-carbon approach, the novel FDM filaments production is chemical-free and mainly relies on mechanical processing, making it easily adaptable for field-scale operation.

 

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