Digital Health

Arm and hand impairment is the major problem usually found in stroke patients, which extremely affects their quality of life. Moreover, motor rehabilitation using conventional physical therapy is ineffective in stroke patients who have severe to moderate arm and hand impairment due to inability to perform voluntary movement. In order to help these patients regain arm and hand function, we have researched and developed brain-computer interface system for motor rehabilitation in stroke patients. This system can help stroke patients learn how to do voluntary arm and hand movement by using only their thoughts or brain signals; additionally, it can also enhance neural plasticity that is the key concept in stroke recovery. Finally, we aim to distribute this technology to the department of rehabilitation in hospitals, rehabilitation clinics, and home use.

This cutting-edge technology is setting new benchmarks in global healthcare with its focus on precision and personalized surgical devices and porous-based implants, particularly within the domain of oral and maxillofacial procedures. One of the primary challenges in contemporary surgical treatments has been the pervasive reliance on standardized devices. Such generic solutions often lead to prolonged surgical durations and extended recovery periods. In contrast, this innovative technology offers a resounding solution by providing 3D-printed surgical devices meticulously tailored to fit individual bone anatomies. The hallmark of these devices lies in their enhanced porous design, which significantly accelerates bone ingrowth and thus curtails healing times. Drawing from extensive clinical evidence, these devices have consistently demonstrated marked improvements in surgical outcomes. The underlying prowess of this technology hinges on advanced design principles and state-of-the-art manufacturing processes. By implementing a two-scale porous-based topology optimization approach, these medical devices are engineered to ensure anatomical conformity, robust mechanical stability, and optimal biological compatibility. As a result, they not only promote accelerated bone ingrowth but also ensure the mechanical integrity and longevity of the device. Poised at the crossroads of design excellence and medical proficiency, this technology is on track to redefine global healthcare standards.

Biomarkers are biomolecules and/or physical characteristics found in the body that give a clear picture of a person’s health and fitness. Currently, the golden standard of biomarker testing is through blood tests. However, this method is invasive as it involves drawing blood with a needle. Additionally, blood tests are neither real-time nor continuous which means there is significant delay between testing and receiving results. Such problems can be solved through this invention as this method involves sensing biomarkers within sweat through a skin patch, eschewing the need for needles. Furthermore, the biomarker data can be instantly transmitted to a smartphone application which allows users to continuously monitor their data in a convenient manner.  This technology would be relevant in numerous industries such as sports fitness, beauty, and medical diagnostics; thus, attracting sizable demand for it where there is an unmet need for convenient, accurate and real time detection of accurate biomarkers.

Histopathology is a cornerstone of modern medicine, providing crucial information that enables doctors to formulate optimal treatment strategies before, during, and after surgeries. However, current methods for obtaining histological images grapple with a compromise between speed and accuracy and suffer from organ-dependent inconsistencies. Addressing these challenges, our technology was developed as a versatile solution to cater to a wide array of clinical scenarios. It sets a new benchmark for medical standards with its rapid, precise, and label-free on-the-spot imaging capability. Computation High-throughput Autofluorescence Microscopy by Pattern Illumination is a one-of-a-kind patented solution n that can detect and provide instant information about cancer status before, during, and after surgeries. This technology lets surgeons place fresh tissue samples taken directly from the patient into the microscope and receive high-resolution and virtually stained histological images in just three minutes. The primary adopters of this technology are expected to be healthcare organizations, hospitals, and research institutions, or any entity involved in histopathology, cancer diagnosis, and surgery. This technology fills a crucial void in the market by providing swift, high-resolution, label-free imaging of thick tissue samples, an achievement previously unattainable. Consequently, this technology not only accelerates the diagnostic process but also enhances its precision, revolutionizing the field of histopathology

Along with the global aging population, the number of people with dementia is also increasing. Moreover, digitalization of society is isolating elderly people. Enjoyable learning using digital devices can be the solution. The product is in the form of a table with a touch screen on the surface. The embedded software is connected to the contents server, which provides various programs such as visual perception and cognitive tests, videos, trainings, and analysis results. They prevent brain aging by stimulating both the left and right brains. The product is beneficial to children as well. The rich educational contents are designed to develop the problem solving ability and the metacognitive ability. The training course includes solid figures, basic Korean, mathematics, and adages etc. Analysis results are also provided to compensate for a vulnerable subject. In addition, safety education and news from local education offices are provided in conjunction with the government.

Neurological diseases are the second leading cause of death. CT scans have been used as the primary modality to diagnose brain abnormalities such as Intracranial Haemorrhage (ICH) and neurodegeneration. Radiologists usually have to deal with an overwhelming scan backlog and writing radiology reports is a time consuming process. Manual segmentation of lesions is tedious and existing heuristics have been shown to overestimate lesion volumes. Clinicians are also wary of the ‘black box’ nature of deep learning models. Hence, an automated tool in the workflow could substantially improve clinical productivity and interpretability is crucial to build trust with clinical stakeholders. Our proposed technology is an AI solution that automates ICH detection and brain tissue segmentation on CT scans, producing accurate volumetric information to assist triaging. Our technology also comes with a set of tools to interact with the AI models and generate reports easily. Moreover, we strengthen our AI transparency with interpretable models. Our platform also focuses on model robustness tests to assure AI safety.  

Osteoporosis is a significant global public health concern affecting approximately 500 million people. The condition is associated with high mortality and disability rates due to osteoporotic fractures. The management of osteoporotic fractures comes at a considerable cost of SGD 11K per patient in Singapore, placing a growing burden on healthcare budgets as the aging population increases. Currently, osteoporosis is assessed by measuring bone mineral density (BMD) using dual energy X-ray absorptiometry (DXA). However, the availability of DXA machines, particularly in developing countries, is limited. Consequently, DXA examinations are not routinely ordered, resulting in orthopaedists often lacking DXA results during examinations. Therefore, an alternative method for estimating and screening osteoporosis is necessary. To address this, an automated AI system that can predict a patient's osteoporotic score by evaluating the CTI (cortical thickness index) from a plain femur X-ray scan is designed and developed. This system would provide a preliminary assessment and enable mass screening for osteoporosis.

Diabetes is associated with macrovascular and microvascular complications, including Diabetic Foot Ulcers (DFU). To identify and manage DFU risk, diabetic patients are recommended to go for a regular foot assessment. Patients who are at‐risk diabetic foot should undergo regular podiatry evaluation, however specialised diabetes centers are currently facing high rates of ulcer recurrence. Frequent visits to these centers can strain an already overwhelmed healthcare system. The technology developer has invented an Artificial Intelligence (AI) model that is able to detect pre-ulceration. By detecting feet at risk of developing DFU, the model is able to refer patients for timely intervention before it becomes a DFU. Users only need to submit photos of their feet from different angles and an anomaly score will be calculated.

This invention is a portable electromyography (EMG) sensor for muscle activity detection.  Unlike conventional EMG devices, which are bulky and confined to clinic settings, the sensor is built to be compact and wearable. It enables real-time, reliable biofeedback regardless of user’s location, bridging the accessibility gap in EMG analysis outside the traditional medical environments. This portability is achieved by integrating reusable micro-structured electrodes and highly integrated sensing system onto a soft and flexible substrate. The design ensures accurate EMG detection while offering a comfortable experience for extended use. The technology consists of three main components: Use of nanofabrication to build the electrodes followed by electric signal detection, replacing conventional gel electrodes. A processing unit for amplification to digital signals. Software to visualize EMG signals. The EMG sensor performance and analysis capabilities allows for collection of signals at high frequency to monitor muscle fatigue conditions. The technology owner is seeking for collaborations in the sports and fitness industry in providing accurate muscle activity signals, enhancing tracking of individual’s physical health actively and for athletes to make optimal adjustments to their training and tailor their approach towards fitness goals. However, its applications extend beyond fitness, with potential uses in elderly health care, virtual reality, gaming, and human-robot interaction. This technology taps into the growing demand for advanced, portable health monitoring systems, offering a solution that bridges the gap between medical-grade equipment and consumer fitness products. The sensor is also currently being trial to aid in rehabilitation in the hospitals.