Development and Analysis of a Multi-Wavelength Near-Infrared Sensor for Monitoring Skin Hydration and Validation Using Monte Carlo Simulation

Abstract

Abstract The monitoring of an individual’s hydration levels is a vital measurement required for the maintenance of a healthy skin barrier function as well as the avoidance of dehydration. The current commercial devices for this measure are typically based on electrical methodologies, such as capacitance, which allows for the extraction of skin hydration using the ionic balance deviations in the stratum corneum. The use of optical-based methods such as near-infrared spectroscopy (NIRS) has been recently explored for the measurement of skin hydration. Optical approaches have the ability to penetrate deeper into the skin layers and provide detailed information on the optical properties of present water bands. This paper presents the development of a multi-wavelength optical sensor and its capability of assessing skin hydration in an in vitro experiment utilizing porcine skin. Regression analysis of the results showed to be in line with standard reference measurements (R 2 CV=0.952257), validating the accuracy of the developed sensor in measuring dermal water content. A Monte Carlo model of the human skin was also developed and simulated to predict the optical sensor’s performance at variable water concentrations. This model serves as a tool for validating the sensor measurement accuracy. The output from this model gave a standard expectation of the device, which agreed with trends seen in the in vitro work. This research strongly suggests that non-invasive (wearable) NIR based sensors could be used for the comprehensive assessment of skin hydration.

Keywords

• Skin hydration
• NIRS
• optical sensor
• biosensors
• wearables
• Monte Carlo simulation