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The latest Singapore National Population Health Survey has reported a concerning diabetes trend. From 2019-2020, 9.5% of the adults had diabetes, slightly dropping to 8.5% from 2021-2022. About 1 in 12 (8.5%) of residents aged 18 to 74 were diagnosed, with an age-standardised prevalence of 6.8% after accounting for population ageing. Among the diabetes patients, close to 1 in every 5 (18.8%) had undiagnosed diabetes, and 61.3% did not meet glucose control targets. Prediabetes is also prevalent, with 35% progressing to type 2 diabetes within eight years without lifestyle changes. Untreated Type 2 diabetes can lead to severe health issues. Tackling this challenge requires a holistic approach, focusing on awareness, early diagnosis, and lifestyle adjustments for diabetes and prediabetes. Recognising the need for innovation to address this, the technology owner develops a cost-effective and non-invasive AI-powered solution, Blood Glucose Evaluation And Monitoring (BGEM), that detects glucose dysregulation in individuals to monitor and evaluate diabetic risks. BGEM allows users to track their blood glucose levels regularly, identify any adverse trends and patterns, and adopt early intervention and lifestyle changes to prevent or delay the onset of diabetes. Clinically validated in 2022, with a research paper published in October 2023, the technology is open for licensing to senior care/home care providers, telehealth platforms, health wearables companies, and more. The BGEM technology is an end-to-end managed AI platform that leverages Photoplethysmography (PPG) enabled wearable sensors to monitor various heart rate variability (HRV) features associated with blood glucose fluctuation. The solution comprises the following features: Optimised and validated AI algorithm Mobile Demo App Including UI/UX design guideline User-friendly visualisations SaaS Scalability Security API Integration The BGEM technology offers a cost-effective, non-invasive approach to predicting an individual's diabetes risk. The applications include: Population Health Perspective: The technology leverages the high growth rate of smart wearables and hearables, presenting an opportunity to identify undiagnosed diabetes individuals within the population. Preventive Health Monitoring: With the ability to monitor blood glucose changes regularly at minimal cost, the technology empowers high-risk users to adopt a healthier lifestyle and, therefore, prevent or delay the onset of diabetes. Diabetes around the world in 2021: 537 million adults (20-79 years) are living with diabetes, 1 in 10. This number is predicted to rise to 643 million by 2030 and 783 million by 2045. Over 3 in 4 adults with diabetes live in low- and middle-income countries. Diabetes is responsible for 6.7 million deaths in 2021 - 1 every 5 seconds. Diabetes caused at least USD 966 billion dollars in health expenditure – a 316% increase over the last 15 years. 541 million adults have Impaired Glucose Tolerance (IGT), which places them at high risk of type 2 diabetes. Overview of the wearable technology market: The market is projected to expand at a compound annual growth rate (CAGR) of approximately 12.5% between 2023 to 2030. Estimated to be worth USD 55.5 billion in 2022, with a projected revenue of USD 142.4 billion by 2030. Current blood glucose monitoring technologies either require finger pricking for blood extraction or the insertion of sensors into the skin and discomfort through wearing patches for extended periods. Instead, the technology uses external sensors and algorithms to detect and predict diabetes risk. No object needs to be inserted into the user's body or continuously worn throughout the day, resulting in minimal pain and discomfort. Additionally, the only equipment required for testing is the wearable device. No additional disposable equipment needles or test strips are needed, which makes blood glucose monitoring much more convenient and cost-effective than other "State-of-the-Art" solutions. The Unique Value Proposition of BGEM include: Market-ready: It is a market-ready non-invasive diabetes risk detection and prediction AI solution that leverages consumer-grade wearables to detect blood glucose dysregulation. Performance: Demonstrates outstanding prediction and detection capabilities. Cloud-based: Operates on a cloud-based platform for seamless integration. Third-party compatibility: Easily implemented with third-party devices and apps. Sustainability: Reduction in bio-medical waste such as needles, test strips etc User-friendly: Non-invasive, convenient and allows frequent measurement. Non-invasive measurement, blood glucose, diabetes mellitus, preventive healthcare, AI, ML, Wearables, PPG, Blood Glucose Monitoring, Diabetes Monitoring, Diabetes Evaluation, Non-Invasive Diabetes Monitoring, Diabetic Risk Assessment Infocomm, Artificial Intelligence, Healthcare, Diagnostics

In Singapore, more than 30,000kg of okara are generated from soya milk and tofu production. Due to the high amount of insoluble dietary fiber and a unique, poignant smell of okara, it is often discarded as a waste product. Despite okara's low palatability, it is rich in nutrients. Therefore, the technology owner has developed a cost-effective formulation to include okara in feed for abalone. The formulation can potentially be adapted and customised for other aquatic species. The technology owner is seeking potential partners to license and commercialise the technology. The technology allows for an alternative nutrient source for animal feed allowing for the sustainability of food supply and reduction of food waste. The formulation consists of a cost-effective plant-based functional ingredient, lowering the costs of feed for aquaculture farms. The nutritional composition can be tailored for different species to increase growth rates and survivability. Okara is used as a cost-effective feed for high-value abalone, a commonly cultured species of mollusc. Okara-based feed results in the beautiful purple colouration of the shell and increased growth and survivability of abalone. In comparison, the okara-based feed costs ~30% less than commercial feed used in the industry. There is potential for okara to be included in feed for other aquatic species such as shrimp and fish. The success of this method will valorise okara, transferring them into a nutrient-dense aquatic feed while promoting a more environmentally sustainable food production chain.       okara, aquatic feed Foods, Ingredients

After a skin injury or surgery, a scar may form as the wound heals. In this body's repair mechanism, the myofibroblast cells produce new collagens and they form an extracellular matrix (ECM) to repair a wound. Over time, most scars become flat and pale. However, in some abnormal cases, the body produces excessive collagens. The excessive ECM formation and deposition of these scar tissue will result in raised scars such as hypertrophic scar and keloid scar. These raised scars may leave lifelong marks on the skin. Although the raised scars are not dangerous or life-threatening, they create aesthetic concern, restrict physical movement and may also lead to itching, tenderness, pain or even depression and anxiety. The currently available scar removal products such as silicon patches and topical products may cause skin irritation, which has led researchers to look for safer and more effective solutions. The present technology is a series of phytonutrient-based remedial fluids, which can be used as a general topical agent or complemented with a nano sprayer for the management of raised scars. The product developed from this technology is a safe, non-invasive and convenient approach to suppress hypertrophic and keloid scars. The technology provider is looking for collaboration opportunities to co-develop skincare products incorporated with this series of plant-based remedial fluids for scar management, collaborators for conducting clinical studies to evaluate effects of the current prototypes as well as other partnership mode including IP licensing.  Hypertrophic and keloid scars are two different fibroproliferative disorders of the dermal tissue upon skin injury. The activation and local proliferation of myofibroblasts in the dermal layer is considered prerequisite for excessive ECM formation, including the overproduction of collagens for filling up the wounds. The phytonutrient-based remedial fluids consist of small-molecule flavanol glycosides extracted from ferns. Experimental results showed that these plant-based fluids could significantly suppress the activation and proliferation of skin myofibroblasts in patients with hypertrophic scars or keloids. These small molecules could also largely reduce the deposition of ECM. As a result, the formation of raised scar can be prevented. The prototypes of the phytonutrient-based remedial fluids have been developed and are currently undergoing product testing. They are designed to reduce raised scars and improve skin conditions. Over 50 volunteers with various types of scars and different skin conditions have tried the prototypes in the initial trial. Overall, positive feedback were received, including notable improvement in scar appearance, alleviation of itchy feeling and prevention of excessive scar tissues. This phytonutrient-based formulation can be used in scar treatment in the form of skincare products such as a general topical agent or nano-mist. They could help shrink, soften and flatten the raised scars, especially for hypertrophic scars and keloids. In addition, this technology can also be used for therapeutic purposes, such as inhibiting the development of fibrosis.  Since many scar treatment gel sheets or creams contain silicone, this natural, non-toxic product provides another option for the people who are allergic to silicone. Customers can be benefited from these herbal-based products with their non-irritating, refreshing texture. Personal Care, Cosmetics & Hair, Healthcare, Pharmaceuticals & Therapeutics

Conventional diagnostic imaging of the skin involves the use of dermatoscopes. Dermatoscopes use skin surface microscopy to examine dermal and sub-dermal tissues to diagnose skin problems. However, these devices can be costly and provide a limited view of the immediate skin surface. This limitation meant that dermatoscopes have to be used in direct contact with the patient's skin. Because of this, they can only be used to image patients in the same physical location as the clinician conducting the examination. The overall result is that only a tiny portion of the global dermatology patient-base can be reached cost-effectively and efficiently. Telemedicine and telehealth network operations are rapidly developing ways to address patients broadly and at lower costs for them and their care providers. Yet, such tools neither deliver desmatoscope-like functionality nor improved it in way that it allows patients' skins to be examined and analysed during an online medical consultation with a general practitioner. In order to facilitate remote skin disease diagnosis, the use of software is required to acquire and share images in real-time and ideally, by the patients themselves. This software enables patients to take their medical sub-skin images with their mobile, tablet or laptop cameras, and securely share it with doctors. Crucially, dermatoscopy images can also be used with the technology to improve diagnostic accuracy. This technology is intended to position itself as a technology which when scaled-up, could allow for products that can enable optical biopsy and phototherapy.  The technology, Remote Diagnostic Imaging (RDI) is available in two modes: Real-Time (RT) and Store-and-Forward (SAF): RT provides remote real-time examination of the patient’s sub-skin by a clinician. SAF enables the patient to snap and forward the sub-skin images to the clinician for assessment. A non-clinician staff member at a clinic can also help the patient to take the images and forward them to a skin specialist. This remote imaging diagnostics is intended to facilitate time and cost savings for both doctors and patients.  The RDI service consists of proprietary software that works with any smart camera device such as mobile, tablet or laptop cameras. An individual at any remote location could take photographs of suspicious skin lesions, and then forward it to the doctor. While the functionality is similar to most image-sharing software, what sets the software apart from other algorithms is the presence of a sophisticated algorithm that acquires sub-skin features of the skin (in normal light) thereby noticing skin issues prior to manifestation on the skin surface. Cosmetic and Medical Dermatology - With 3rd party software, this skin imaging software platform has the potential to facilitate more accurate diagnosis and management of a range of skin diseases, such as psoriasis, acne, vitiligo and dermatitis, to more serious and potentially fatal conditions of melanoma. Optical Biopsy - Completing initial tissue analysis in a few minutes. Phototherapy - Producing the skin and tissue pectral data needed to deliver the correct type and dosage of opticat radiation. Podiatry (diabetes) – Diabetic patients can suffer from numbness in their feet, potentially leading to foot infections which if left untreated may necessitate amputation. The RDI and proposed multispectral imaging solutions can help podiatrists gain advance notice and clarity of potential issues. The key benefit being a better patient outcome.  X-ray (radiology) – X-ray radiation continues to be a major cause for health concern despite its significant benefit in patient diagnostics. It is also not known for being able to render soft tissue visual detail in the way that MRI and ultrasound does. Both RDI service and multispectral imaging embedded technology enable the use of pre-existing X-ray images to be used to acquire visualisation of more detail. The key benefit is reduced radiation dosage which results in less risk to the health of the patient.  In the near future, it is expected that an absorbed multispectral-based imaging app or device as well as the embeddable diagnostic platform will become an integral part of a smart diagnostics platform for remote clinical diagnosis. Dermatology clinics and hospitals can use these solutions for the remote diagnosis of any type of skin disease, track the progress of a patient condition after treatment, and better engage patients in the treatment process by empowering them to take proper preemptive care of their skin health. The technology is available as an embeddable algorithm, and as a secured cloud-based service that can be embedded to a website. The embeddable version of the technology is available in a licence or co-creation form. It can be embedded in OEM devices, equipment and machines. Some of the advantages of this innovative technology are as follows: Skincare consumers and patients can self-analyse and monitor their skin's health from the comfort and privacy of their home, while having their skin analysed visually. Information can be shared in real time with their skin specialist Provides an ability to visually 'see' the skin as light sees it and interacts with it on the surface and beneath opens up new diagnosis and treatment opportunities Synergenic tool for integration into the rapidly expanding telehealth platforms out in the market Potential to enable diagnosis of skin conditions as well as setup of pre-signal detection to alert potential skin conditions before they are visibly present. Enable storing of historical sub-skin imaging data through the SAF feature, this allows for image analysis overtime. melanoma, skin, imaging, diagnostic, analysis, microbe, microorganism, bacteria, virus, spectroscopy, smartphone, non-invasive, health, telemedicine, telehealth, dermatology, oncology, phototherapy, photoanalysis, radiology, biopsy, subskin, subsurface, embeddable, camera, microbiome, dermoscopy, cosmetic, optical Infocomm, Video/Image Analysis & Computer Vision, Personal Care, Cosmetics & Hair, Healthcare, Medical Devices, Healthcare ICT

There are 30,000 occupational drivers in Singapore, out of which 13,500 are 45 years old and above. The risk of acquiring cardiovascular disease increases with age and is potentially exacerbated by low physical activity and high emotional stress levels, which are two typical characteristics of occupational drivers arising from their work environment. Low level of physical activity and high stress levels have been shown to have significant relationship with heart rate variability, one of the indicators of cardiovascular disease. This technology is developed to help drivers to monitor their stress level, provide them with instantaneous feedback and the necessary alerts for a timely intervention. This technology offer presents a cross-platform AI system that estimates the stress levels continuously in real time, and can be easily integrated with commercially available photoplethysmography (PPG) wearables, e.g., a PPG wristwatch. In addition, this technology can be adapted for the monitoring of workplace stress with the aim of improving overall mental well-being. The current practice of using electrocardiogram (ECG) to measure the electrical activities of the heart is mainly found in the clinical settings and not easily accessible by the general population due to high costs. The need for an accurate placement of ECG electrodes does not allow the continuous monitoring of the heart condition in a non-clinical setting. It is not easy for individuals to continuously monitor their stress levels at the workplace in daily life, especially for drivers. This technology offer enables continuous, real-time monitoring and is not limited to clinical settings. It is cost-effective without the need to purchase medical grade ECG devices. The solution can be easily customised and adapted to existing and future PPG wearables. It is portable and feasible for all-day monitoring of stress levels and heart conditions in diverse workplace environments. Essentially, it is an algorithm that extracts proprietary features to predict stress levels, with an unique approach, from heart beat signals customised to a given context in the workplace. This facilitates the creation of contextualised stress profiles for specified workplace situations ranging from physical combat conditions to air-conditioned office sedentary conditions. The technology owner is interested to out-license this technology offer. Potential application areas are: Public or private hospitals, clinics, community care centers. Individual drivers and any workers who might be exposed to workplace related stress. Sports sectors including sports training, research and competition. Medical devices, equipment suppliers and manufacturers. Potential products: Existing or future wearables with PPG, e.g., wristwatch, headset, t-shirt, etc. Hardware and platform independent, easy to be incorporated into existing and future wearables. Portable and feasible for 24/7 stress monitoring. Affordable and cost-saving without the need to purchase medical grade ECG devices Real-time monitoring and timely feedback customised for users stress monitoring, ai algorithm, ai system, heart monitoring, workplace stress, wearable technology Infocomm, Artificial Intelligence, Internet of Things, Wireless Technology, Sustainability, Sustainable Living

One use of AI, including deep learning, is in prediction tasks, such as image scene understanding and medical image diagnosis. As deep learning models are complex, heatmaps are often used to help explain the AI’s prediction by highlighting pixels that were salient to the prediction. While existing heatmaps are effective on clean images, real-world images are frequently degraded or ‘biased’-such as camera blur or colour distortion under low light. Images may also be deliberately blurred for privacy reasons. As the level of image clarity decreases, the performance of the heatmaps decreases. These heatmap explanations of degraded images therefore deviate from both reality and user expectations.  This novel technology-Debiased-CAM-describes a method of training a convolutional neural network (CNN) to produce accurate and relatable heatmaps for degraded images. By pinpointing relevant targets on the images that align with user expectations, Debiased-CAMs increase transparency and user trust in the AI’s predictions. Debiased-CAMs are effective in helping users identify relevant targets even on images affected by different clarity levels and multiple issues such as camera blur, poor lighting conditions and colour distortion. The AI’s prediction also becomes more accurate. As the model is trained using self-supervised learning, no additional data is needed to train it.  The training for Debiased-CAM is generalisable, and thus applicable to other types of degraded or corrupted data and other prediction tasks such as image captioning and human activity recognition. Used to train a convolutional neural network (CNN) to produce accurate and relatable heatmaps for degraded images. By pinpointing relevant targets on the images that align with user expectations, Debiased-CAMs increase transparency and user trust in the AI’s predictions. It also increases the ability of meeting regulatory standards to deploy CNN models in the following applications, where explainable AI is required. Healthcare, eg. Radiology Autonomous Vehicles   Produces accurate, robust and interpretable heatmaps for degraded images Works on images with multiple degradation levels and types such as blurring and improper white balance Agnostic to degradation level, so that enhancement can be applied even when the level is unknown Perceived by users to be more truthful and helpful as compared to current heatmaps distorted due to image degradation Method of training can be applied to other degradation types and prediction tasks Explainable AI Infocomm, Video/Image Analysis & Computer Vision, Artificial Intelligence

Lists are an indispensable part of the online experience, often used to show many results, such as products, web pages, and food dishes. These items can be neatly sorted by a desired attribute like price, relevance, or healthiness. Listed items often have multiple attributes. However, instead of being able to sort multiple attributes simultaneously, consumers are currently limited to sorting only one attribute at a time. This makes searching for the desired item tedious and confusing. Imma Sort supports interpretable and multi-attribute sorting. Sorting for two or more attributes is possible. In contrast to existing search technology, Imma Sort trades off the smoothness of the sorted trend for the main attribute to increase ease of prediction for other attributes, by sorting them more approximately. Results for specific attributes can be made smoother by setting higher importance weights. Provides intuitively sorted results sorted by two or more attributes to improve decision-making and user experience Results can be customised by allocating higher weightage for selected attributes Enables users to perform multi-attribute sorting in any existing list interface without requiring sophisticated spreadsheets or data visualisations Can be integrated into search and recommendation systems across a wide range of applications Can also be incorporated into various search and recommendation systems for more effective search results. Examples of possible applications: Food dishes can be sorted by healthiness and tastiness Hotels can be sorted by price and distance Sorting by price and rating would generate results that generally trend in one direction for both attributes. This makes it easy for users to anticipate the values of multiple attributes as they move down the list, without having to construct a mental list for the secondary attribute. By decreasing users’ mental effort, this will improve decision-making and increase satisfaction. Multi-Attribute Sorting, e-commerce, algorithm Infocomm, eCommerce & ePayment, Enterprise & Productivity

Cadaveric bones are used to carry out medical training for surgeons and trainees. However, such bones are limited in supply, difficult to store, inconsistent in terms of quality and costly to use for repeated training. As such, it is necessary to create an alternative to cadaveric bones that is equally realistic while being more cost effective and easier to obtain. This technology can resolve the limitations of cadaveric bones by offering the formulation and processing method to produce a Fused Deposition Modelling (FDM) system-agnostic bone-like 3D printing filaments for surgical models printing. Printed anatomical bone models developed from this technology will have the look and feel of the real bone. The technology presents an affordable and readily available alternative that minimises the demand for cadaveric bones while still providing realistic training to medical professionals. The technology owner is seeking for collaborations with companies interested to scale-up the manufacture of the filaments and/or licensing of the technology.   The technology offers the formulation and processing method to produce bone-like filaments that allows users to 3D print realistic and relatively lower cost cadaver bone models for use in medical training of surgeons and trainees. These bone-like filaments have the following features: Compatible with all FDM 3D printers Achieves good mechanical properties  (~80% improvement in tensile strength) compared to the commercial bone-like filament. Printed bone models using this technology feel realistic to drill and cut and screws can be tightened nicely, just like real cadaveric bones. This technology is primarily targeted for use in the healthcare industry (hospitals, medical schools, and biomedical companies) to obtain realistic anatomical bone models for surgical training and workshops at a more affordable price compared to cadaveric bones. Surgeons can also create 3D printed bone structures to help them plan surgical procedures before operating on the patient to better understand the procedure. Significantly lowers the cost for realistic medical trainings and workshops as compared to using cadaveric bones Fabricated bone models are equal in quality with actual cadaveric bones cadeveric bones, cadever, cadevers, 3d printing, fdm, medical training, surgery, surgeon, medicine, bone models, additive manufacturing, fused deposition modelling, printed anatomical bone models, surgical models, printing, bone-like Materials, Composites, Manufacturing, Additive Manufacturing, Moulding, Sintering, Casting & Nanoimprinting, Life Sciences, Industrial Biotech Methods & Processes

EBV is a ubiquitous human herpes virus, which spreads through saliva. EBV infects over 90% of the human population and can establish life-long persistence in the host. Most people get EBV when they are young, but they will not experience any symptoms until they get older. There are about 200,000 EBV-associated cancer new cases per year. Nasopharyngeal cancer (NPC) is one of EBV associated cancers which is endemic in a few areas including Southern China, Southeast Asia, North Africa and the Arctic. The highest NPC incidence rate is found in Southern China including Hong Kong. The association of NPC and EBV is nearly 100% in endemic areas. Unfortunately, more than 80% of the new NPC cases are diagnosed in stage III or IV, while the survival rate of stage IV NPC is only 38%. Early detection and treatment would help to increase survival rate. This invention is a new EBV-specific targeted agent which selectively kills cancer cells without affecting any normal cells. The uptake of this drug can also be traced by the fluorescent signal that can be used for cancer cells imaging. Currently, there is no single agent that can both image and kill NPC cancer cells at the same time. Epstein–Barr nuclear antigen 1 (EBNA1) is the only viral protein expressed in all EBV-infected cells. This invention is an EBNA1 targeting bio-probe that can effectively target EBNA1 to disrupt its cancerous activities and inhibit cancer cell growth. In addition, it can also emit fluorescent signals to show the presence of EBV-infected cells, and this can be used for imaging the EBV-associated cancers. The invention is the first known agent with a dual function that can accurately trace and image for the EBV-associated cancers while being a pinpointed therapeutic intervention at the same time.  Other than providing a fast, simple and accurate detection for EBV-associated cancers, this invention shows a high efficacy at a low dose (less than 4mol/kg, ~92% cancer inhibition) toward cancer treatment. This invention shed light to develop a new generation medical reagent that has both imaging function and anti-cancer activity. The specificity of this technology provides a crucial means in the accurate detection of EBV-associated cancers. More importantly, its anti-tumour ability provides inhibition in the cancer cells and thus reduces potential metastasis. People in NPC-endemic areas could benefit from this world’s first agent with dual functions that can detect EBV-infected cells and inhibit cancer cells. It can be used to trace the presence of residual cancer cells after treatments. This invention could also replace or minimize the use of the radio- and chemo-therapies for NPC which could greatly improve the survival of patients with advanced diseases, as well as their quality of life. Nasopharyngeal cancer, Nasopharynx cancer, Epstein-Barr Virus, EBV, EBNA1, EBV-positive Healthcare, Diagnostics, Telehealth, Medical Software & Imaging, Pharmaceuticals & Therapeutics, Life Sciences, Biotech Research Reagents & Tools