TECH OFFERS

Recently, the rising adoption of Internet of Things (IoT) devices and portable electronics has made electronic waste (e-waste) pollution worse, especially when small and low-power IoT devices are single-use only. As such, low-cost and environmentally friendly power sources are in high demand. The technology owner has developed an eco-friendly liquid-activated primary battery for single-use and disposable electronic devices. The battery can be activated by any aqueous liquid and is highly customisable to specific requirements (i.e., shape, size, voltage, power) of each application. This thin and flexible battery can be easily integrated into IoT devices, smart sensors, and medical devices, providing a sustainable energy solution for low-power and single-use applications. The technology owner is keen to do R&D collaboration and IP licensing to industrial partners who intend to use liquid-activated batteries to power the devices. The technology is a single-use and non-rechargeable battery that can be instantly activated by any aqueous liquid (e.g., water, fruit juice, soft drink, etc.) as well as all types of body fluids (e.g., blood, saliva, urine, sweat, bile, etc.). The features of this technology are: Customisable shape, size, and power (1.5 to 6.0 V at 4 to 50 mW) Ultra-thin and flexible (<1 mm in thickness) Lightweight (when dry) High energy density (less than 5 mm2 for low-power application: 1.5 V, 2 mAh) Indefinite pre-activation shelf-life (no self-discharge) Non-toxic and biocompatible (safe for human beings) Environmentally friendly (no disposal pollution) This inherently safe and non-toxic battery can be widely applied in MedTech applications, disposable IoT, smart sensors, and low-power electronics. The potential applications include but are not limited to: Medical devices: digital pills, ingestible sensors, smart bandages, wearable biosensors, in-vitro diagnostics (IVDs), body fluid testing, etc. Disposable IoT: Bluetooth Low Energy (BLE) chips, microprocessors, wireless sensors (pH, temperature, humidity), micromotors, LEDs, heaters, etc. Other low-power electronics: smart labels, electronic skin patches, cold chain monitoring, smart packaging, etc. The technology offers the following unique features: Highly customisable for different applications Thin and flexible (adaptable to various designs) Long shelf-life (can be sealed for a very long time) Biocompatible (can be safely consumed) Environmentally friendly and non-toxic The technology owner is keen to do R&D collaboration and IP licensing to industrial partners who intend to use liquid-activated batteries to power the devices.  Primary Battery, Environmentally Friendly, Non-Toxic, MedTech, Disposable IoT Energy, Battery & SuperCapacitor, Healthcare, Medical Devices, Infocomm, Internet of Things

Despite the increasing prevalence of obesity, all FDA-approved medications, which act indirectly on the central nervous system to suppress appetite or on the gastrointestinal tract to inhibit fat absorption, suffer from poor effectiveness and side effects. Most of these medications have been withdrawn from the market. Although liposuction performed in clinics can effectively remove targeted subcutaneous fat, it suffers from invasiveness, high costs, associated risks, induction of compensatory increase of visceral fat. Although thermal lipolysis induced by high-power laser energy is a non-invasive way to reduce subcutaneous fat, its effectiveness is limited and it often causes skin burning. Both liposuction and laser lipolysis cannot improve whole-body metabolism. The technology owner has developed a transdermal mild photothermal therapy directly acting on the root of evil, i.e. subcutaneous fat, to induce its ameliorating remodelling (browning, lipolysis, angiogenesis, and apoptosis), based on the injectable hydrogel encapsulated with photothermal agent. Browning refers to the conversion of energy-storage white fats into energy-burning brown fats. Further, combining with pharmaceutical therapy by codelivery of pharmacological agent leads to a strong therapeutic synergy. This method not only ensures high effectiveness and low side effects due to localized and targeted application but also remotely creates significant improvements in whole-body metabolism (e.g., reduction of visceral fat, relief of diabetic symptoms). In addition, this technology is applicable for cosmetic purposes, e.g., body contouring and reduction of double chin. The technology owner is seeking potential biotechnology companies, clinicians, and other partners to clinically translate and commercialize this technology. Possible modes of collaboration include R&D, process, and product development. Photothermal agents and pharmacological agents are encapsulated in biocompatible and biodegradable hydrogel which retains the therapeutics to ensure sustained effects. After being injected into subcutaneous fat depots (e.g., belly fat) using an insulin needle or an automated injection device with minimal pain, NIR irradiation at each injection site will be applied for only five minutes using a portable laser source, one to three times a day for several days without the need of another injection. This described procedure (injection + laser treatment) can be applied once or several times. Obvious mass reduction of the treated fat and other beneficial effects on the whole-body should be resulted. In contrast to laser lipolysis, this procedure shall be much more effective, pain free without causing skin burning, and profoundly beneficial. It can be conducted in clinics by professionals or be self-administered at home for long-term care. The primary application area of our technology is for treating obesity and associated metabolic diseases (e.g., type 2 diabetes). This technology can also be used for non-therapeutic or cosmetic purposes, including contouring, sculpting, or slimming one or more regions of the subject’s body for a desirable appearance. To be specific, this technology can locally remove stubborn fat below the chin, or in thigh, abdomen, thorax, flank, upper limb, upper body, lower limb, back, etc.   As highlighted by Mordor Intelligence, the anti-obesity drugs market was valued at about US$ 1,690 million in 2020, and it is expected to reach US$ 4,250 million in 2026, registering a CAGR (compound annual growth rate) of 15% over the forecast period, 2021-2026. And according to IMARC Group, the global body contouring market reached a value of US$ 7.3 billion in 2021, and is expected to reach US$ 11.1 billion by 2027, exhibiting at a CAGR of 6.9% during 2022-2027. This technology provides an unprecedented solution with high effectiveness and low risks. Non-invasive targeted treatment on subcutaneous fat Drastic reduction of subcutaneous fat and visceral fat Relief of obesity-associated metabolic diseases (e.g., diabetes) Low risks and low side-effects High effectiveness Self-administrable Obesity, Diabetes, Metabolic Diseases, Transdermal Therapy, Personal Care, Slimming Healthcare, Medical Devices, Pharmaceuticals & Therapeutics

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

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

This Technology Offer allows automation of the process of monitoring stock levels in the warehouse, and when they drop below a certain threshold, trigger a certain event.  This technology can be used to address the following challenges: What items are on the shelf? What is the current inventory level? What items need to be restocked? How many items need to be restocked? This technology can automatically trigger material top-up quantity from a cloud platform to suppliers, based on visual signals using webcams. Two types of technology concepts are used: 1) Webcam scans AR code to detect stock to be replenished or 2) Webcam compares area occupied vs empty (ROI image area mapping), and calculates stock to be replenished Thus, stock management can optimized and no longer require storage in warehouse; they can be directly sent to Centralized Packaging, hence saving staging space & inventory. This technology would be useful for companies that are interested in automating the warehouse processes. This in turn could reduce the time and manpower required to do inventory checks. The technology can also be applied in places with high turnover stock rates or unpredictable selling rates, e.g., pharmacy or supermarket. This technology allows for automatic monitoring and top up triggering of inventory levels, thus reducing time and manpower required to do inventory checks. Inventory Management, Logistics, Warehouse Management Logistics, Inventory Management