Sensing by Seeing: In Vivo Detection and External Transmission of Blood Viscosity Through the Internet of Bio-Nano Things

This study introduces a novel “sensing-by-seeing” methodology for real-time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> detection and external transmission of whole blood viscosity (WBV) through the Internet of Bio-Nano Things (IoBNT). The motivation arises from the lack of real-time, noninvasive techniques to monitor dynamic tumor-induced physiological changes. Leveraging the computational nanobiosensing (CONA) framework, we model the tumor targeting process as a natural computation problem, where tumor-triggered biological gradient fields (BGFs) serve as the objective function to be optimized. Externally controlled nanoswarms (NSs) act as search agents, sensing BGF variations, and transmitting data to an external monitoring device. WBV, a key indicator of the tumor microenvironment (TME), modulates NS dynamics and reflects pathological progression. We employ the full-width-at-half-maximum (FWHM) of NS spatial distributions as a measurable parameter for WBV estimation, integrating convection-diffusion modeling with statistical mechanics. To address measurement noise, we propose a rotating magnetic field strategy to stabilize NS behavior. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In silico</i> simulations validate the spatiotemporal dynamics of WBV in capillary-scale TME models, achieving a relative detection error of 10%. Our method tracks sinusoidal, square, and triangular WBV waveforms with robust performance under thermal and flow variations. A strong correlation (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.9617) with Brookfield viscometer measurements confirms empirical consistency. The results demonstrate the feasibility of closed-loop nanoswarm-based sensing, advancing IoBNT applications in tumor detection and continuous health monitoring.