Wearable computational optical sensing for inflammatory skin diseases

Summary: Abstract Body: Inflammatory dermatoses, such as atopic dermatitis, psoriasis, and allergic contact dermatitis (ACD), are prevalent and often chronic disorders that can severely impact patients’ quality of life. ACD, affecting approximately 1 in 5 individuals, serves as an ideal model for our study of inflammatory skin diseases. The purpose of this study is to develop a wearable optical sensor for real-time, non-invasive monitoring of skin inflammation, using ACD as a model. Despite the prevalence of ACD, the diagnostic gold standard, patch testing, has been fundamentally unchanged since its introduction in 1895, remaining a time-consuming and clinic-dependent method. This study aims to address these limitations by designing and fabricating a low-cost optical sensor capable of detecting changes in skin optical properties, such as scattering and absorption, which are indicative of early inflammatory responses. To support the sensor's development, custom skin phantoms were created to replicate the optical characteristics of human tissue across the full spectrum of Fitzpatrick skin tones. These phantoms provide a controlled testing environment for calibration and validation of the device, ensuring inclusivity and accuracy across diverse skin types. A prototype sensor was engineered to perform time-lapse optical measurements and was validated on these phantoms under simulated inflammatory conditions. This study represents a critical step toward the development of non-invasive diagnostic tools for ACD. By combining custom skin phantoms with advanced sensor technology, this project lays the groundwork for future clinical studies and broader applications to other inflammatory skin diseases, ultimately improving diagnostic accessibility and addressing healthcare disparities. Shannon Wongvibulsin¹, Paloma Casteleiro Costa², Yuzhu Li², Georgios Spanodimos², Zhuoran (Leo) Zhao², Gyeo-Re Han², Aydogan Ozcan² 1. Medicine, Division of Dermatology, University of California Los Angeles, Los Angeles, CA, United States. 2. Electrical & Computer Engineering, University of California Los Angeles, Los Angeles, CA, United States. Bioinformatics, Computational Biology, and Imaging