SBIR-STTR Award

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to equip consumers with a scientific tool to measure and control their exposure to ultraviolet (UV) radiation, thereby mitigating their risk of getting skin cancer while enjoying the benefits of sunlight such as Vitamin D and outdoors activities. In the United States, skin cancer has become a major public health issue with an estimated 3.5M people being treated each year for a cost of over $8B. The rate of Vitamin D deficiency in the US has been estimated to be over 40% leading to increased risk for depression, cardiovascular disease, and cancer. Up until now, accurate measurement of ultraviolet exposure remains confined to research laboratories. This project aims at carrying a scientific breakthrough in UV dosimetry and bring a laboratory-grade technology to consumers.The proposed project aims to achieve a scientific breakthrough in UV dosimetry by combining several detectors, machine learning algorithms, and customized calibration. We anticipate that this breakthrough will lead to a drastic improvement in accuracy to closer match that of laboratory-grade equipment, while keeping the size and cost of our instrument in line with consumers? expectations. The scientific challenge is to have the UV sensor be accurate when it measures most solar spectra, and there is an infinity of these based on location, weather, and time of the year. Our strategy is to stay away from incremental improvements (e.g. filter optimization) or expensive developments (e.g. a full-blown spectrometer). Instead, we are testing the hypothesis that the combination of machine learning algorithms and a small set of carefully chosen detectors will enable us to build a small low-cost instrument able to identify the local solar spectrum and provide correctly calibrated real-time measurements. To achieve this, we propose to apply clustering techniques to find representative spectra of solar UV and train several detectors to recognize them and correct the measurement. The execution of this project requires top-level R&D among diverse collaborators, whom we have gathered for this project.

The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to provide a new tool promoting healthy sun behavior, a major public health issue in the US as melanoma incidences have increased steadily over the past 60 years. This technology is already used in clinical studies on sun behavior across a variety of populations (children, adults, melanoma survivors, people suffering from lupus) and can significantly improve the quality of life for patients with disorders requiring particularly sensitive UV detectors to prevent exposure to potentially carcinogenic levels of sun. This proposed project will positively impact broader health with a device that can be incorporated in personal electronic wearable devices. The proposed project will support the advanced development of low-cost UV measurement. Sunlight is a complex electromagnetic source generating spectra that vary strongly with the position of the sun, location on earth, weather conditions from the ground to the stratosphere, and local shadows. Previous detectors were based on simple linear, single wavelength calibrations inappropriate for a signal with a varying spectral shape. The proposed project will extend the development of a new system with a detection limit of 0.005 UVI (UV Index, the health-relevant measure of intensity), compared with the state of practice of 0.1 UVI; this extends traditional detection limits by integrating machine learning. The Phase II research objectives are to engineer a prototype system, reduce the package size, extend the machine learning capabilities, and optimize system performance in real-world environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.