Still medical sampling has a snapshot approach lacking the dynamical behaviour of a person’s physiology. Sensor technologies are able to provide metrics by means of active (prompted) or passive (unnoticed) measurements, offering considerable flexibility in approach. Those high-frequency longitudinal data sets can then be used for prevention or characterization of a disease . We address those time dependent features using monitoring of vital signs pre-, peri- and post- intervention. In various studies together with the department of integrative natural medicine (Charité) , German Institut of Nutrition (DIfE), Max Delbrück Centre for Biomedical Research (MDC, BIH) and Luxembourg Center for Systems Biomedicine we approach to better understand human phenotypes.
 Kourtis LC, Regele OB, Wright JM, Jones GB. Digital biomarkers for Alzheimer’s disease: the mobile/wearable devices opportunity [In- ternet]. Vol. 2, npj Digital Medicine. 2019. Available from: http://dx.doi.org/https://doi. org/10.1038/s41746-019-0084-2
 Steckhan, Nico; Arnrich B. Quantified Complementary and Alternative Medicine : Convergence of Digital Health Technologies and Complementary and Alternative Medicine. Complement Med Res. 2020;8–10.