Non-invasive detection of haemoglobin, platelets, and total bilirubin using hyperspectral cameras

Hyperspectral imaging has emerged as a promising high-resolution and real-time imaging technology with potential applications in medical diagnostics and surgical guidance. In this study, we developed a high-speed hyperspectral camera by integrating a Fabry-Perot cavity filter on each CMOS pixel. We used it to non-invasively detect three blood components (haemoglobin, platelet, and total bilirubin). Specifically, we acquired transmission images of the subject's fingers, extracted spectral signals at each wavelength, and used dynamic spectroscopy to obtain non-invasive blood absorption spectra. The prediction models were established using the PLSR method and were modelled and validated based on the standard clinical-biochemical test values. The experimental results demonstrated excellent performance. The best predictions were obtained for haemoglobin, with a high related coefficient (R) of 0.85 or more in both the calibration and prediction sets and a mean absolute percentage error (MAPE) of only 5.7%. The results for total bilirubin were also ideal, with R values exceeding 0.8 in both sets and a MAPE of 10.6%. Although the prediction results for platelets were slightly less satisfactory, the error was still less than 15%, indicating that the results were also acceptable. Overall, our study highlights the potential of hyperspectral imaging technology for the development of portable and affordable devices for blood analysis, which can be used in various settings.