Abstract
Post-pandemic health operations have become a near-term reality, discussions around wearables are on the rise. How do wearable health solutions effectively deploy and use this opportunity to fill the gap between wellness and healthcare? In this paper, we will talk about wearable healthcare diagnosis, with a particular focus on monitoring skin hydration using optical multi-wavelength sensor fusion. Continuous monitoring of human skin hydration is a task of paramount importance for maintaining water loss dynamics for fitness lovers as well as for skin beauty, integrity and the health of the entire body. Preserving the appropriate levels of hydration ensures consistency of weight, positively affects psychological state, and proven to result in a decrease in blood pressure as well as the levels of “bad” cholesterol while slowing down the aging processes. Traditional methods for determining the state of water content in the skin do not allow continuous and non-invasive monitoring, which is required for variety of consumer, clinical and cosmetic applications. We present novel sensing technology and a pipeline for capturing, modeling and analysis of the skin hydration phenomena and associated changes therein. By expanding sensing capabilities built into the SmartWatch sensor and combining them with advanced modeling and Machine Learning (ML) algorithms, we identified several important characteristics of photoplethysmography (PPG) signal and spectral sensitivity corresponding to dynamics of skin water content. In a hardware aspect, we newly propose the expansion of SmartWatch capabilities with InfraRed light sources equipped with wavelengths of 970 nm and 1450 nm. Evaluation of the accuracy and characteristics of PPG sensors has been performed with biomedical optics-based simulation framework using Monte Carlo simulations. We performed rigorous validation of the developed technology using experimental and clinical studies. The developed pipeline serves as a tool in the ongoing studies of the next generation of optical sensing technology.
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