A spectral sensing device and associated methods for enhanced diagnostic capabilities across medical fields are disclosed. The device incorporates multispectral, hyperspectral, and photoplethysmography technologies to analyze biological features including tongue,
oral cavity,
saliva, teeth, and other tissues. The
system transforms any standard RGB camera into a multispectral imaging device by training
machine learning models to associate RGB values with spectral values inside and outside the
visible spectrum using measurements from a
single pixel detector spectroradiometer. A multimodal neural network with separate
processing branches analyzes spectral images, non-spectral images, and tabular data to predict
microbiome composition. The
system generates
health risk assessments by comparing predicted microbial abundances to thresholds associated with various medical conditions. Near-
infrared sensing enables
blood flow monitoring, subcutaneous imaging, and assessment of physiological parameters. Convolutional neural networks enable
spectral reconstruction without requiring the physical device, while supporting
continuous monitoring in various form factors.