A new Swinburne-led startup, SensFit Technologies, has developed a smart shoe with inbuilt sensors, aiming to improve the quality of life of older people through the early detection of dementia, diabetic ulcers and other physical activity issues.
The unique technology is based on 87 smart sensors bonded with an innovative graphene ink that is embedded in the soles of a shoe. It was developed by startup co-founders Professor Franz Konstantin Fuss, a medical technologies researcher, and Dr. Nishar Hameed, whose research focuses on developing innovative technologies from advanced composite materials.
"SensFit Technologies will be the first company to use cutting edge graphene sensors in a smart shoe, providing a first-to-market innovation" the researchers stated.
The innovative sensor technology picks up the pattern of movement imprinted in the shoe. Proprietary AI algorithms analyze the data. In doing so, the shoe conducts a neurological assessment, helping users to understand and respond to the onset of health problems such as dementia, diabetic ulcers or the likelihood of a fall. This can lead to early treatment for conditions that may not have been detected otherwise.
SensFit Technologies is now looking for $125,000 in funding to support technology development and clinical trials.
Professor Fuss and Dr. Hameed were inspired by the medical use of pressure sensor arrays in Professor Fuss’ previous project to prevent head injuries and saw the potential to commercialize the technology.
While the researchers developed the technology, they recruited students Minh My Hanh Le, Syed Anwar, Ali Omran, Zoe Halligan and Ashley Walsh to find the right market fit for SensFit Technologies.
SensFit Technologies was initially focused on fall prevention within aged care facilities. After the conducting data analysis, developing a market strategy and pitching to one of the top 10 residential aged care providers in Australia, they recommended expanding SensFit Technologies to assist with a range of health issues affecting older people.