Photonic monitoring of physiology

The Nanoengineering Group at CIC nanoGUNE aims to pioneer the development of advanced photonic systems for continuous, non-invasive monitoring of physiological parameters. Our research explores and exploits vibrational spectroscopy techniques as Raman, surface-enhanced Raman scattering (SERS), and Fourier-transform infrared (FTIR) spectroscopy to achieve high sensitivity and specificity in detecting subtle biochemical changes in biological samples.

Our investigation encompasses both in vitro and in vivo studies. In vitro experiments involve analyzing aqueous solutions, blood, blood plasma, and further bodily fluids to identify and monitor biomarkers and metabolic parameters. In vivo studies extend to animal and human subjects, aiming to translate our findings into real-world clinical applications. We take a holistic approach and focus on comprehensive biomarker profiling, classification of physiological states and disease detection, in addition to what is usually targeted, namely complementary specific biochemical or physiological parameters. This strategy enables us to capture a broad spectrum of physiological information, enhancing the potential for early disease detection and personalized diagnostics.

Data acquired from our spectroscopic analyses undergo rigorous preprocessing and are subjected to both linear and non-linear correlation analyses. We employ classic and advanced machine learning and apply also deep learning techniques, depending on the size and structure of the datasets, including regression and classification models to interpret spectroscopic, tabular, and categorical data. In cases where computer vision is involved, these models take into account a higher data dimension, which in some cases increases the potential for target detection and classification.

Our ultimate objective is to integrate these photonic systems with vital sign monitoring modules, creating a highly integrated, multimodal diagnostic platform. Such a system promises to revolutionize non-invasive continuous health monitoring in real-time and enable proactive healthcare interventions.

Publications

I. Olaetxea, H. Lafuente, E. Lopez, A. Izeta, I. Jaunarena, and A. Seifert, Photonic technology for in vivo monitoring of hypoxia-ischemia, Advanced Science, 10, 2204834, 2023. https://doi.org/10.1002/advs.202204834

H. Lafuente, I. Olaetxea, A. Valero, F. J. Alvarez, A. Izeta, I. Jaunarena, and A. Seifert, Identification of Hypoxia-Ischemia by chemometrics considering systemic changes of the physiology, IEEE Journal of Biomedical and Health Informatics, 26, 2814– 2821, 2022. https://doi.org/10.1109/JBHI.2022.3142190

I. Olaetxea, A. Valero, E. Lopez, H. Lafuente, A. Izeta, I. Jaunarena, and A. Seifert, Machine learning-assisted Raman spectroscopy for pH and lactate sensing in body fluids, Analytical Chemistry, 92, 13888–13895, 2020. https://doi.org/10.1021/acs.analchem.0c02625