EIT of the Human Body with Optimal Current Patterns and Skin-Electrode Impedance Compensation

Following the lead of the EIT research group at Rensselaer Polytechnic Institute, we have designed and implemented a system comprising 32 independent current sources, in which it is possible to apply current patterns optimizing distinguishability. One potential technical problem is that we are measuring voltages on current-carrying electrodes, giving some sensitivity to time varying skinelectrode impedances. We demonstrate here an algorithm to estimate simultaneously changes in the medium and timevarying skin-electrode impedances

Multi-channel EIT for layer-based hydration monitoring

Accurate monitoring of hydration level in patients remains a major challenge for hemodialysis therapy. Using a prototype EIT system with simultaneous multi-channel current excitation, we demonstrated the capability to detect a difference of 35ml daily fluid change in human subjects who wear compression sock only on one leg. The prototype system has the potential to be used in clinical settings with hydration monitoring needs

A High Precision Parallel Current Drive Experimental EIT System

Our parallel current drive EIT architecture can simultaneously drive 32 independent high impedance current sources and measure 32 independent precision voltage channels. Coherent modulation and demodulation is digitally implemented using field programmable gate arrays. High accuracy and precision is achieved using custom analog circuits containing modified Howland current sources coupled to negative impedance converters

Feature-Enhancing Inverse Methods for Limited-View Tomographic Imaging Problems

In this paper we overview current efforts in the development of inverse methods which directly extract target-relevant features from a limited data set. Such tomographic imaging problems arise in a wide range of fields making use of a number of different sensing modalities. Drawing these problem areas together is the similarity in the underlying physics governing the relationship between that which is sought and the data collected by the sensors. After presenting this physical model, we explore its use in two classes of feature-based inverse methods. Microlocal techniques are shown to provide a natural mathematical framework for processing synthetic aperture radar data in a manner that recovers the edges in the resulting image. For problems of diffusive imaging, we describe our recent efforts in parametric, shape-based techniques for directly estimating the geometric structure of an anomalous region located against a perhaps partially-known background

A Retrospective Cohort Study of Clinical Factors Associated with Transitions of Care among COVID-19 Patients

Coronavirus Disease 2019 (COVID-19) is an international health crisis. In this article, we report on patient characteristics associated with care transitions of: 1) hospital admission from the emergency department (ED) and 2) escalation to the intensive care unit (ICU). Analysis of data from the electronic medical record (EMR) was performed for patients with COVID-19 seen in the ED of a large Western U.S. Health System from April to August of 2020, totaling 10,079 encounters. Of these, 5172 resulted in admission as an inpatient within 72 h. Inpatient encounters (n = 6079) were also considered for patients with positive COVID-19 test results, of which 970 resulted in a transfer to the ICU or in-hospital mortality. Laboratory results, vital signs, symptoms, and comorbidities were investigated for each of these care transitions. Different top risk factors were found, but two factors common to hospital admission and ICU transfer were respiratory rate and the need for oxygen support. Comorbidities common to both settings were cerebrovascular disease and congestive heart failure. Regarding laboratory results, the neutrophil-to-lymphocyte ratio was associated with transitions to higher levels of care, along with the ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT)