Highly accurate multimodal monitoring of lactate and urea in sweat by soft epidermal optofluidics with single-band Raman scattering

The shifting paradigm in clinical practice to remote healthcare underscores the need to develop novel biosensing modalities to rapidly and continuously assess digital and metabolic biomarkers. Sweat is a rich, heterogeneous biofluid that provides broad insights from the underlying dynamic metabolic activity of human physiology and enables new unobtrusive ways to monitor health status continuously. However, eccrine sweat is a relatively unexplored body fluid and has scant use in clinical practices. Here, we introduce a novel, easy-to-fabricate skin-interfaced sweat collection epidermal microfluidics, which enables multimodal analysis coupled with sponta-neous Raman scattering. The introduced wearable optofluidic patch is soft, fully flexible, can robustly interface with the skin without inducing chemical or physical irritation, and has minimal optical interfaces to the spectra of the analytes. The proposed detection approach by Raman scattering provides label-free chemical fingerprint information, enabling quantitative optical biosensing with high sensitivity and selectivity. As a great advantage, the proposed epidermal optofluidics and optical biosensing technique require neither plasmonic surface fabri-cation for surface Raman enhancement nor bulky ultrashort-pulsed lasers for coherent Raman enhancement, which are typically acquired for increasing Raman signal intensity and sensitivity of quantitative Raman analysis. Moreover, the developed system enables simultaneous sweat glucose, lactate, and urea concentration moni-toring. Furthermore, we show that biomolecule concentration monitoring with only one Raman shift simplifies spectroscopies instrumentation complexities and eliminates the requirement of advanced data processing methods to analyze the entire Raman spectra. Therefore, the proposed "single-band Raman analysis" coupled with developed epidermal optofluidics (epioptofluidics) shows accurate, repeatable, and stable sweat biomole-cule analysis and proposes instrument down-scale and miniaturization possibilities.