Arterial waveforms can provide valuable insights into a patient’s health. Hematocrit (HCT) level, the blood volume concentration of red blood cells, makes up 40 to 50% of the total blood concentration. Dielectric spectroscopy studies focusing on blood have shown that relative permittivity and conductivity vary with HCT levels. This paper presents a novel method to detect the hematocrit levels in the blood and sense the arterial waveform. A finite-difference time-domain (FDTD)-based 2D electromagnetic (EM) simulation with an artery and tissue model was used to detect different HCT levels at 915 MHz. Based on published literature, dielectric parameters for a normal range of HCT levels were assumed from animal blood studies. Additionally, a 2D wrist simulation model was developed at 915 MHz and 2.45 GHz with a multiple-port system. Based on numerical simulations, EM signals were sensitive to different HCT levels and changes in arterial blood volume. The simulation results indicate a great potential for microwave-based non-invasive sensing of HCT levels and arterial waveforms.

Applications of microwave imaging in the biomedical fields have gained momentum in recent years due to low cost, non-ionizing nature, and non-invasive capabilities. For such imaging applications, the dielectric properties of the specific tissues need to be accurately known where such accuracies are often dependent on the physical attributes such as shapes and sizes of biological samples under test. In this work, the effects of the variable insertion depth of a generic coaxial probe in a biological tissue on the measured permittivity is investigated. Using return loss, the dielectric properties of the material are estimated and compared with the Debye model. The results are in good agreement from 500 MHz to 8 GHz.

Digital representation of tissues allows the examination of tissue morphology in new ways enabling patient stratification for effective treatments. Current slide-scanning techniques capture the visible details of the tissue as whole-slide images and digitally record them in the form of spatial and color relationships. Specialized experimental techniques like dielectric spectroscopy can also be used to investigate a tissue's response to an applied electric field. This study used the dielectric spectroscopy method to collect the complex permittivity of healthy and abnormal biopsy tissues excised during Gastroenterology procedures. A single pole Cole-Cole model is fitted to the measurements dataset to extract the Cole-Cole parameters which are used as features in the machine learning binary classification model. The model's performance demonstrates the feasibility of using microwave-based spectroscopy measurements to create a digital dielectric fingerprint for tissues under investigation.

Digitization of tissues allows examination of tissue morphologies in new ways enabling patient stratification for effective treatments. Current slide-scanning techniques capture the visible details of the tissue as whole-slide images and digitally record them in the form of spatial and color relationships. Specialized experimental techniques like Dielectric spectroscopy can also be used to investigate a tissue’s response to an applied electric field. This study used the dielectric spectroscopy method to collect the complex permittivity of healthy and abnormal biopsy tissues excised during gastroenterology procedures. A single pole Cole-Cole model is fitted to the measurements dataset to extract the parameters which are used as features in machine learning binary classification models. The models achieved high accuracy, demonstrating the feasibility of using microwave-based spectroscopy measurements to create a digital dielectric fingerprint for tissues under investigation.