Prescription glasses, sports footwear, and respirator masks are among the widely worn accessories and wearable products that require a good fit to perform with their intended function. However, inherent demographic design biases cause these products to fit poorly to certain demographics, with women and ethnic minorities twice as likely to experience poor fit in some cases. During the COVID-19 pandemic, up to 97% of healthcare professionals from ethnic minority backgrounds suffered from some form of skin damage due to poor fit of respirator masks. As a result, the performance of such products is undermined, leading to discomfort, the spread of disease and potential for injury.
PolyMetrix has developed a digital platform to rapidly and autonomously capture and process biometric data. The output from this process is a 3D biometric model with the complex topologies of an individual robustly mapped out, enabling digital fitting and design of bespoke wearables.
This is the first affordable, robust, and scalable solution for personalised wearable products and will be applicable to the e-commerce, healthcare, security, and industrial markets.
PolyMetrix will remove demographic bias from the wearable industry, enabling all to be equally served by devices designed to protect the wearer or enhance performance. To reach this goal, we will finish the development and stress testing of the web system and mobile data capture application. In 12 months, PolyMetrix will be applying the business teachings from the Fellowship programme and have a fully functioning and tested system licensed to first customers.
Associated Programme
