IntroductionThis study evaluated the hypothesis that vascular aging (VA) reduces ventricular contractile function and mechanical efficiency (ME) using the left ventricular pressure-volume (PV) construct.MethodsA previously published in-silico computational model (CM) was modified to evaluate the hypothesis in two phases. In phase I, the CM included five settings of aortic compliance (CA) from normal to stiff, studied at a heart rate of 80 bpm, and phase II included the normal to stiff CA settings evaluated at 60, 100, and 140 bpm. The PV construct provided steady-state and transient data through a simulated vena caval occlusion (VCO). The steady-state data included left ventricular volumes (EDV and ESV), stroke work (SW), and VCO provided the PV area (PVA) data in addition to the three measures of contractile state (CS): end-systolic pressure-volume relationship (ESPVR), dP/dtmax-EDV and preload recruitable stroke work (PRSW). Finally, ME was calculated with the SW/PVA parameter.ResultsIn phase I, EDV and ESV increased, as did SW and PVA. The impact on the CS parameters demonstrated a small decrease in ESPVR, no change in dP/dtmax-EDV, and a large increase in PRSW. ME decreased from 71.5 to 60.8%, respectively. In phase II, at the normal and stiff CA settings, across the heart rates studied, EDV and ESV decreased, ESPVR and dP/dtmax-EDV increased and PRSW decreased. ME decreased from 76.4 to 62.6% at the normal CA and 65.8 to 53.2% at the stiff CA.DiscussionThe CM generated new insights regarding how the VA process impacts the contractile state of the myocardium and ME.

Mean arterial pressure and cardiac output provide insufficient guidance for the management of intraoperative hypotension (IOH). In silico models offer additional insights into acute changes in hemodynamic parameters that may be encountered during IOH. A computational model (CM) generated parameters quantifying ventricular-vascular coupling, and pressure-volume construct across levels of aortic compliance (CA ). We studied how a loss from normal-to-stiff CA impacts critical care metrics of hemodynamics during vascular occlusion. Pulse pressure (PP), end-systolic pressure (Pes ), arterial compliance (Art-ca), arterial elastance (Art-ea), and dynamic arterial elastance (Eadyn), along mechanical efficiency (ME) were measured at five levels of CA . A loss in CA impacted all variables. During steady-state conditions, PP, Pes , and stroke work increased significantly as CA decreased. Art-ca decreased and Art-ea increased similarly; Eadyn increased and ME decreased. During a decrease in preload across all CA levels, arterial dynamics measures remained linear. The CM demonstrated that a loss in CA impacts measures of arterial dynamics during steady-state and transient conditions and the model demonstrates that critical care metrics are sensitive to changes in CA . While Art-ca and Art-ea were sensitive to changes in preload, Eadyn did not change.

The Partial Element Equivalent Circuit (PEEC) method is an efficient technique to model the propagation of an electromagnetic field using an equivalent circuit. This work is a methods paper on computing the equivalent PEEC model of a parallel plate capacitor. Results are validated.

Radio frequency (RF) biosensors are an expanding field of interest because of the ability to design noninvasive, label-free, low-production-cost sensing devices. Previous works identified the need for smaller experimental devices, requiring nanoliter to milliliter sampling volumes and increased capability of repeatable and sensitive measurement capability. The following work aims to verify a millimeter-sized, microstrip transmission line biosensor design with a microliter well operating on a broadband radio frequency range of 1.0–17.0 GHz. Three successive experiments were performed to provide evidence for (1) repeatability of measurements after loading/unloading the well, (2) sensitivity of measurement sets, and (3) methodology verification. Materials under test (MUTs) loaded into the well included deionized water, Tris-EDTA buffer, and lambda DNA. S-parameters were measured to determine interaction levels between the radio frequencies and MUTs during the broadband sweep. MUTs increasing in concentration were repeatably detected and demonstrated high measurement sensitivity, with the highest error value observed being 0.36%. Comparing Tris-EDTA buffer versus lambda DNA suspended in Tris-EDTA buffer suggests that introducing lambda DNA into the Tris-EDTA buffer repeatably alters S-parameters. The innovative aspect of this biosensor is that it can measure interactions of electromagnetic energy and MUTs in microliter quantities with high repeatability and sensitivity.

The impact of the aging process on the cardiovascular system has been well documented. The Framingham studies have shown that a loss in aortic compliance (Ca) from the 3rd to 7th decade is associated with a rise in pulse-wave velocity (PWV). It is anticipated that precise measurements of cardiac function across this time frame would also demonstrate a loss in cardiac work. However, these changes are likely due to the combination of age and CVD. We sought to determine how a loss in Ca alone impacts cardiac function and we employed a computational model (CM) developed by Ursino (Cheng, 2016), modified for assessment of pressure-volume loop data during simulated vena-caval occlusions at five levels of Ca: baseline (Native-N), 90%, 80%, 60% of native and Stiff, as defined by Kelly et al (1992). In agreement with their animal data, we observed step increases in pressures, EDV and ESV, stroke work and dP/dtmax and effective arterial elastance (Ea) (Table 1). The CM approach permitted gradual losses between Native and Stiff options compared with the animal model. Three methods of assessing cardiac function (Ees, dPdtmax-EDV (d-EDV) and preload recruitable stroke work (PRSW)) were impacted differently from Native to Stiff. Ees decreased 8.8% across the spectrum with little change at 90% and 80%, d-EDV changed less than 2.5% across the entire spectrum and PRSW increased 20.7 and 29.7% at 60% and during the stiff simulation, respectively. Pulse pressure (PP) increased across the spectrum with a large increase (65%) being observed at 60% Ca and a near four-fold increase (215%) at S. The change in Ea was aligned with the PP changes with an increase of 14% at 60% and 41% at S. These findings extend the work by Kelly et al and demonstrate that smaller changes in Ca (90 and 80%) impact cardiac volumes, PP and SW more than contractile state. Finally, PP, shown to be a sensitive parameter of vascular aging, along with PWV, increases out of proportion to Ea, possibly highlighting the lack of sensitivity of Ea to shed light on VVC. The impact of the aging process on the cardiovascular system has been well documented. The Framingham studies have shown that a loss in aortic compliance (Ca) from the 3rd to 7th decade is associated with a rise in pulse-wave velocity (PWV). It is anticipated that precise measurements of cardiac function across this time frame would also demonstrate a loss in cardiac work. However, these changes are likely due to the combination of age and CVD. We sought to determine how a loss in Ca alone impacts cardiac function and we employed a computational model (CM) developed by Ursino (Cheng, 2016), modified for assessment of pressure-volume loop data during simulated vena-caval occlusions at five levels of Ca: baseline (Native-N), 90%, 80%, 60% of native and Stiff, as defined by Kelly et al (1992). In agreement with their animal data, we observed step increases in pressures, EDV and ESV, stroke work and dP/dtmax and effective arterial elastance (Ea) (Table 1). The CM approach permitted gradual losses between Native and Stiff options compared with the animal model. Three methods of assessing cardiac function (Ees, dPdtmax-EDV (d-EDV) and preload recruitable stroke work (PRSW)) were impacted differently from Native to Stiff. Ees decreased 8.8% across the spectrum with little change at 90% and 80%, d-EDV changed less than 2.5% across the entire spectrum and PRSW increased 20.7 and 29.7% at 60% and during the stiff simulation, respectively. Pulse pressure (PP) increased across the spectrum with a large increase (65%) being observed at 60% Ca and a near four-fold increase (215%) at S. The change in Ea was aligned with the PP changes with an increase of 14% at 60% and 41% at S. These findings extend the work by Kelly et al and demonstrate that smaller changes in Ca (90 and 80%) impact cardiac volumes, PP and SW more than contractile state. Finally, PP, shown to be a sensitive parameter of vascular aging, along with PWV, increases out of proportion to Ea, possibly highlighting the lack of sensitivity of Ea to shed light on VVC.

As more educational data becomes available, learning analytics and educational data mining are allowing instructors to make data-driven decisions like never before. Much of the work in learning analytics and educational data mining has been done in traditional subjects like math and reading, but these tools also have the potential to shape our understanding of the complexity of engineering design and innovation. This work uses learning analytics and educational data mining to analyze and interpret student data collected in a course where students work on innovation projects. Specifically, this work improves previous classification models developed for innovation in classroom settings by implementing the Innovation-Based Learning (IBL) Framework – a qualitative model that sorts student actions into seven categories. The models developed include 1) a text classifier that automatically groups student text into the categories of the IBL framework with higher reliability than a team of human raters ( $\kappa =0.760$ versus $\kappa =0.627$ ), 2) a text classifier that uses the IBL framework to predict student performance on new cohorts better than previously developed models (ROC AUC =0.710 versus ROC AUC =0.640), and 3) a quantitative classifier that uses the IBL framework to differentiate between lower and higher performing students better than previously developed models (ROC AUC =0.782 versus ROC AUC =0.491). Not only does this work detail the development and testing of these models, but it also uses the results to suggest best practices of teaching innovation in educational settings.

In many areas of electronics design, it is necessary to understand the different aspects of capacitance associated with various conducting surfaces in a particular layout. This is because as operating frequencies increase and dimensions decrease, capacitive coupling can become the dominant means in which noise is induced in a design. Therefore, having the ability to extract an equivalent circuit for modeling capacitive coupling and understanding the coupling can be very important, and challenging. This paper presents insight on capacitive coupling by evaluating the capacitance between two parallel plates, with particular attention paid to the self-capacitance (with a reference at infinity) of each of the individual plates. More specifically, the Partial Element Equivalent Circuit (PEEC) method is used to compute the self-capacitance of each individual plate in the parallel plate capacitor problem, and results are verified by comparison to values from James C. Maxwell’s original works and the electrostatic solver ANSYS Maxwell 3D. Overall, it is shown how the self-capacitance of each individual plate changes as a function of distance between the parallel plates.

Understanding neuronal structure and function is essential to studying the human brain. The goal of this project was to create a model of human brain neurons that accurately reflects neuronal function, energy consumption, and oxygen consumption. Extensive work has been performed on the Hodgkin-Huxley model of neurons to accurately model neuronal firing. This study focuses on the creation of a model of the Hodgkin-Huxley neuron in MATLAB with the assistance of the DynaSim toolbox. This model was used to compute values and using another model the energy efficiency of the neuron was calculated and related to oxygen consumption, which then corresponds to Blood Oxygenation Level Dependent (BOLD) imaging in fMRI. The results of this study provide detailed visual and technical information about how the brain neurons function, which is crucial to the further development in brain imaging techniques and to further our understanding of why and how our complex brains function.

Accurate noninvasive blood pressure (BP) measurements are vital in preventing and treating many cardiovascular diseases. The “gold standard” for noninvasive procedures is the auscultatory method, which is based on detecting Korotkoff sounds while deflating an arm cuff. Using this method as a “gold standard” requires highly trained technicians and has an intrinsic uncertainty in its BP predictions. In this article, we analyze and characterize the origins of this uncertainty. This article defines an uncertainty model for two consecutive BP measurements. Our research group developed a computer-based simulation of auscultatory BP measurement uncertainty, and these results were compared to a human-subject experiment with a group of 20 diverse-conditioned individuals. Uncertainties were categorized and quantified. The total computer-simulated uncertainty ranged between −8.4 and 8.4 mmHg in systolic BP (SBP) and −8.4 and 8.3 mmHg in diastolic BP (DBP) at a 95% confidence interval (CI), while the limits in the human-based study ranged from −8.3 to 8.3 mmHg in SBP and −16.7 to 4.2 mmHg in DBP.

Human cognitive processes remain an area of strong interest and ongoing research. One tool to gain greater insight into this process is neuronal modeling. The following features are desirable in a neuronal modeling tool: a library of known parameters for different neurons and species, the ability to select the neuron and species of interest, the ability to quickly simulate neuronal behavior, and the ability to calculate metabolic requirements and efficiencies for various neuronal activity. Many of these can be found in software today, but not all elements can be found in one entity. The goal of this work is to develop a neuronal modeling tool that incorporates these features.

This study describes a non-invasive medical device capable of measuring arterial blood pressure (BP) with a combination of inflationary and deflationary procedures. The device uses the pressure cuff pressure signal, arterial skin-surface acoustics, and photoplethysmography (PPG) to make a sensor-fusion estimation of blood pressure readings. We developed an apparatus composed of 1) a modified off-the-shelf oscillometric blood pressure system, 2) a contact microphone with an amplifier, 3) and high-sensitivity pulse oximeter, and its control electronics.

The advancing field of biosensor design continues pushing for smaller, inexpensive, yet accurate sensor designs. A subset of biosensors operating in the radio frequency (RF) range of electromagnetic (EM) waves, called RF biosensors, offer appeal as a non-destructive, non-invasive form of sensing. A novel RF biosensor is proposed which detects changes in scattering parameter measurements of a microliter, aqueous material under test (MUT) held within a well adjacent to a microstrip transmission line. This sensing design measures scattering parameter data and changes in these measurements offer insight into the effects of RF wave exposure on dielectric materials within the well. The following paper describes design considerations and the sensing technique of the proposed RF biosensor. Simulations were run in incremental steps to first, establish the simulation design of a 50-ohm microstrip transmission line using two software packages ADS and Ansys HFSS. Next, experimental measurements were collected by milling the RF biosensor, first using air and then distilled water as the MUT, and finally comparing to simulations to establish validity of the novel sensing device. Next, experimental S-parameter measurements were obtained and compared between the two test cases to determine if a difference could be detected. Both simulated and experimentally obtained measurements suggest the designed RF biosensor can detect changes in the MUT loaded inside its etched well and therefore can be used as a sensing device.

In this work-in-progress (innovative practices) paper, we introduced a biomedical engineering research project to students in our primarily undergraduate institute (PUI) where sources and research activities are limited. Here, we present the motivation, background, best practices, initial assessment, and future work. Through virtual collaboration with a research institute, the project helped engage students in research activity, broaden the current scope of our project-based pedagogy, and address the typical challenges in online learning. In this semester-long project, a group of seven students from two schools developed a highly coupled Simulink model that captured the behaviors of the human cardiovascular system. The model aimed to study the aging effect of the aorta on cardiac power and blood pressure. Regarding the project design, we introduced the concept from the software engineering, i.e., “Agile Principle” and “Minimal Viable Product”. Students started to develop a working model of one component (i.e., O2 and CO2 exchange model in the tissue) from the entire system. Through multiple iterations, the model was debugged, expanded, and polished. We recognized the critical role of communication in the virtual space. Besides routine team meetings on Zoom, we also mentored students with model debugging time through the Slack platform. Students developed their professional skills through weekly learning journals where ideas, reflection, confusion can be shared with faculty. The preliminary assessment indicates positive impacts, such as growth mindset, time management, and more career options.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract It is also vital to acknowledge the enthusiastic and effective participation by the Microventure students: Matthew Lanoue, sophomore in Manufacturing Engineering; Joshua Brantner, senior in Industrial Engineering and Management; Mayank Verma, graduate student in Manufacturing Engineering; Casey Radtke, junior in University Studies; Stephen Wurm, senior in Business Administration. New recruits are … Caitlyn Aho and Laura Axvig, sophomores in Microbiology; Jared Graetz, junior in Manufacturing Engineering; Michael Hedlund, senior in Industrial Engineering and Management, and David Stenseth, senior in Manufacturing Engineering. These folks have been dedicated, creative and effective in establishing a project focus from a very broad topical area, researching and analyzing the technologies involved and creating a vision for the Team -- and not so incidentally, teaching their mentors. References: 1. “78 Ideas Enrolled in 2nd InnovateND Program”; www.innovatend.com; 19th December 2007 2. Daniel Ewert; “Bison Ventures: Engines of Innovation”; NDSU White Paper; April 2007 3. David L. Wells; “Micromanufacturing in the Classroom and Laboratory”; Annual Conference, American Society for Engineering Education; Honolulu; June 2006 4. David L.Wells, Sreenath Seetharamu and Arun Shankaran; “A Novel Microelectronics Packaging Taxonomy”; Automation and Assembly Summit, Society of Manufacturing Engineers; St. Louis; April 2005

A radio frequency (RF)-based medical device implanted deep inside a human body can be wirelessly powered using RF energy. However, this method experiences loss in the form of attenuation and absorption, which is caused by the lossy human body. The need for a path loss (PL) model is, therefore, necessary to characterise these losses. This study presents a novel PL method, which is based on the measurements, obtained from a series of experiments on two different Dorset breed ovine models. Also, the uncertainty analysis of the equipment has been performed and the available RF power inside the body at a proposed implant location has been computed. The results are then used to develop and propose an equivalent model for PL in an anechoic chamber. Overall, an approximate PL of 3.5 dB/cm in the ovine body was measured at 1.2 GHz. Moreover, it was concluded that with the inevitable errors in the equipment, the total PL for 6 cm deep implant location was ∼21 dB with an uncertainty of 2.034 dB. The PL model presented is novel and has a great potential for applications in the design and development of RF-based implantable devices, especially leadless pacemakers.

Recently, interest in the effects of radio frequency (RF) on biological systems has increased and is partially due to the advancements and increased implementations of RF into technology. As research in this area has progressed, the reliability and reproducibility of the experiments has not crossed multidisciplinary boundaries. Therefore, as researchers, it is imperative to understand the various exposure systems available as well as the aspects, both electromagnetic and biological, needed to produce a sound exposure experiment. This systematic review examines common RF exposure methods for both in vitro and in vivo studies. For in vitro studies, possible biological limitations are emphasized. The validity of the examined methods, for both in vitro and in vivo, are analyzed by considering the advantages and disadvantages of each. This review offers guidance for researchers to assist in the development of an RF exposure experiment that crosses current multidisciplinary boundaries.

Radio-frequency (RF)-based wireless power transfer method is highly desirable to power deep-body medical implants, such as cardiac pacemakers. The antenna is one of the essential components of such system; however, it poses significant design challenges for deep-body applications and must be modeled and characterized correctly to achieve the required performance. In this paper, design and validation of a novel wideband numerical model (WBNM) are proposed for deeply implantable antennas and to enable RF-powered leadless pacing. In particular, we acquired a wideband tissue simulating liquid (TSL) and fully characterized it using a dielectric probe. Based on the measured properties of the TSL, the design and numerical characterization of the WBNM were performed using a hybrid simulation method, i.e., by employing the finite-element method and method of moment. The proposed WBNM was validated experimentally as well as analytically using a reference microstrip antenna. Good agreement between the simulated, measured, and analytical results validated the proposed model. Furthermore, the application of this model and the TSL was demonstrated by the design, development, manufacture, and measurement of a novel metamaterial-based conformal antenna at 2.4 GHz. Moreover, good agreement was found between the simulated and measured results of the proposed conformal antenna. It is evident from the results that the proposed numerical model can be used to design deeply implantable antennas for any frequency, ranging from 800 to 5800 MHz. Finally, the proposed miniature conformal antenna and its successful integration with a leadless pacemaker model present a great potential for future RF-powered leadless pacemakers and other deep-body medical implants.

The management of heart failure patients via the implantation of cardiac pacemakers has become a well-known therapy. However, the complications associated with traditional cardiac pacemakers are usually related to finite-battery life, transvenous pacing leads, and subcutaneous device pocket. In this paper, we propose a wearable RF-powered leadless pacing system, which can be implanted directly inside the heart and powered via RF energy, without any batteries or pacing leads. More specifically, we have realized a prototype rectenna-based leadless pacemaker (LP), the implant, which consists of an implantable rectenna, charging and pacing circuits, as well as the pacing electrodes. In addition, a wearable transmit-antenna array was designed, developed, and fabricated for RF energy transmission into the body. In an acute animal study, using ovine models, the proposed LP was implanted at the left ventricular apex by thoracotomy. Using the prototype wearable transmit-antenna array, the prototype LP was powered wirelessly and as a result, leadless pacing was successfully demonstrated in the in vivo ECG results. Besides measuring the efficiency of the rectenna, the computations of specific absorption rate (SAR) are presented and found to be under the IEEE recommended limits. We conclude that a wearable RF-powered leadless pacing system is realizable with the SAR under the safe levels. Thus, the proposed leadless pacing method has the potential to be significantly safer as it completely eliminates the battery, leads, and device pocket and all the associated complications.

Specific absorption rate (SAR) is a measure of safety and a requirement for portable radio frequency devices which are regulated mainly by the standards recommended by the Institute of Electrical and Electronics Engineers (IEEE) and International Commission on Non-Ionizing Radiation Protection (ICNIRP). Accurate approximation of SAR is therefore important for safety as well as for compliance purposes. This article presents the analytical representation and derivation of the SAR from the basics of electromagnetic theory, Maxwell Equations, and law of conservation of energy in electromagnetic theory. It is shown, analytically, that for a time harmonic electromagnetic wave propagating in a homogeneous lossy medium having permittivity E, permeability mu, and conductivity sigma, the time rate change of electric and magnetic energy densities at steady state inside a given volume is zero. It is also shown that at the steady state, the net power flowing through a volume, bounded by a surface is equal to the power dissipated in that volume. Furthermore, this work demonstrates that at the steady state, SAR can be represented in terms of power density or in terms of power dissipated in the given volume. Moreover, calculation of SAR for a 1 mm x 1 mm x 0.01 m box having the dielectric properties of human skin was performed using the derived formulas and then compared with the numerical results, obtained using a full wave 3D simulation tool, HFSS. A good agreement was found between the analytical and numerical results.

Mechanical circulatory support devices (MCSDs) have gained widespread clinical acceptance as an effective heart failure (HF) therapy. The concept of harnessing the kinetic energy (KE) available in the forward aortic flow (AOF) is proposed as a novel control strategy to further increase the cardiac output (CO) provided by MCSDs. A complete mathematical development of the proposed theory and its application to an example MCSDs (two-segment extra-aortic cuff) are presented. To achieve improved device performance and physiologic benefit, the example MCSD timing is regulated to maximize the forward AOF KE and minimize retrograde flow. The proof-of-concept was tested to provide support with and without KE control in a computational HF model over a wide range of HF test conditions. The simulation predicted increased stroke volume (SV) by 20% (9 mL), CO by 23% (0.50 L/min), left ventricle ejection fraction (LVEF) by 23%, and diastolic coronary artery flow (CAF) by 55% (3 mL) in severe HF at a heart rate (HR) of 60 beats per minute (BPM) during counterpulsation (CP) support with KE control. The proposed KE control concept may improve performance of other MCSDs to further enhance their potential clinical benefits, which warrants further investigation. The next step is to investigate various assist technologies and determine where this concept is best applied. Then bench-test the combination of kinetic energy optimization and its associated technology choice and finally test the combination in animals.