Confocal Raman spectroscopy (CRS) has shown potential in non-invasive skin analysis. However, current CRS systems have various limitations including a narrow detection band, large size, non-flexibility, slowness, and complexity, which hinder their clinical applications. Herein, we developed a portable ultrawideband CRS system with a fiber-based handheld probe to acquire the Raman spectra in both fingerprint and high wavenumber regions in a fast and quasi-simultaneous way. Dual-wavelength excitation with a dualpassband laser cleaning filter and high-speed fiber array multiplexer was adopted instead of a specialized grating and detector to achieve instant switching between the detection regions and improve system robustness. Preliminary in vivo results demonstrated its depth profiling capability in an ultrawide detection range for stratum corneum thickness, natural moisturizing factor, and water content quantification, indicating its great potential in a wide range of clinical and cosmeceutical applications.

Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current commercial CRS systems suffer from limited detection regions (450−1750 cm −1 ), bulky sizes, nonflexibilities, slow acquisitions by consecutive excitations, and high costs if using a Fourier transform (FT) Raman spectroscopy with an InGaAs detector, which impede their adoption in clinics. In this study, we developed a portable CRS system with a simultaneous dual-wavelength source and a miniaturized handheld probe (120 mm × 60 mm × 50 mm) that can acquire spectra in both fingerprint (FP, 450−1750 cm −1 ) and high wavenumber (HW, 2800−3800 cm −1 ) regions simultaneously. An innovative design combining 671 and 785 nm lasers for simultaneous excitation through a compact and high-efficiency (>90%) wavelength combiner was implemented. Moreover, to decouple the fused FP and HW spectra, a first-of-its-kind precise Raman spectra separation algorithm (PRSSA) was developed based on the maximum a posteriori probability (MAP) estimate. The accuracy of spectra separation was greater than 99%, demonstrated in both phantom experiments and in vivo human skin measurements. The total data acquisition time was reduced by greater than 50% compared to other CRS systems. The results proved our proposed CRS system and PRSSA's superior capability in fast and ultrawideband spectra acquisition will significantly improve the integration of CRS in the clinical workflow.

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