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DEVELOPMENT OF AN ARTIFICIAL ATRIUM FOR THE ADVANCEMENT OF CATHETERIZATION SURGERIES

ABSTRACT

Atrial fibrillation (AF) is a heart arrhythmia in which aberrant electrical signals are conducted through cardiac tissue, causing random contractions of the atria and improper heart rates. Catheter ablation, a corrective surgery for this arrhythmia, involves the transmission of electrical pulses by a special catheter to the conductive segments of the cardiac tissue, thus modifying the electrical properties of these areas and preventing improper electrical activity. Currently, the tracking methods of ablation surgeries require X-ray and CT-based monitoring, exposing the patient and surgeon to dangerous radiation. Additionally, the physician must manually manipulate the catheter tip throughout the long surgery, as opposed to an automated or digital-based method of catheter control. Dr. Grant H. Kruger of the SM Wu Manufacturing Center at the University of Michigan has developed a feed-forward robotic catheterization system that eliminates the need for high-radiation monitoring and allows the physician more fidelity with automation controls. Currently, the only test environment for Dr. Kruger’s robot has been a stationary box of fluid. However, the system must be further advanced before it can be deployed in clinical settings. Specifically, its feed-forward inverse kinematic model must be tested and developed in settings that mimic forces and disturbances normally present in arrhythmic heart environments. A dynamic environment that simulates flow patterns present in the human atrium – as well as the disturbances triggered by atrial fibrillation – was thereby developed by this team for purposes of advancing Dr. Kruger’s catheterization system.

1G. Bian, M. Lipowicz, and G. H. Kruger. “Self-Learning of Inverse Kinematics for Feedforward

BACKGROUND

A proper heart beat is initiated by an electrical signal originating in the sinoatrial (SA) node in the right atrium, depicted in Figure 1. This electrical signal forces a contraction of the right atrium. At the same time, the left atrium is stimulated, in addition to the atrioventricular (AV) node, which dampens the speed of the signal from the atria to the ventricles. In turn, the ventricles are given time to fill as the atria then contract. The ventricles then contract, delivering blood from the heart to the rest of the body.

Figure 1. Diagram of human heart with AF catheter positions.1 AF is caused by the generation of aberrant electrical signals from trigger sites originating in the atrial walls. These atypical signals force high-frequency, random cyclic contractions of the atria. In ablation surgeries, diagnostic catheters are inserted to identify the AF trigger sites, while an ablation catheter is deployed to transmit the corrective signal to these locations. In current settings, the positioning of these catheters are manually controlled through bending the distal end or rotating the handle. This causes exhaustive, non-ergonomic strain on the operator, while the use of

Control of Intracardiac Robotic Ablation Catheters,” pp. 1-6.

C. Coyne, A. Kurz, C. Munger, S. Shrago

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X-ray and CT monitoring systems expose patients and medical personnel to high amounts of radiation. Studies indicate that catheter ablation surgeries have higher efficacy than drug-based therapies. Dr. Kruger has developed a robotic system that controls the location of catheters using a feed-forward control algorithm, eliminating the need for high-radiation monitoring systems and relieving the operator of manually positioning the catheter for long, sustained periods of time. The results of using a feed-forward loop for catheter control are depicted in the below images generated from a magnetic tracking system. Figure 2. Catheter tip position data gathered by magnetic tracking system While the application of feed-forward control and magnetic-based validation have significant potential for advancing ablation surgeries, there are sources of error to be addressed. In feed-forward control, one difficulty is the presence of multiple disturbances within the system, which must be predicted a priori to ensure

accuracy and proper operation of the system. In the case of atrial fibrillation, forces resulting from cardiac contractions will certainly deform the distal shaft of the catheter and thus result in positioning error. In his paper Self-Learning of Inverse Kinematics for Feedforward Control of Intracardiac Robotic Ablation Catheters, Dr. Kruger holds that the three sources responsible for positioning error are 1) disturbances due to blood pressure and flow, 2) mechanical contact with the endocardium, and 3) friction and viscoelastic effects due to the catheter design. Other sources of positioning error are the contact between the catheter tip and the endocardium as well as material properties of the catheter’s elasticity responsible for causing some deflection. These sources of error in the positioning of catheters in Dr. Kruger’s system are far from negligible. To address them, the system’s inverse kinematic algorithm must be further developed by deploying a test environment that mimics the flow patterns, disturbances and other physical parameters present in a human heart with atrial fibrillation. While an artificial heart for the specific purpose of addressing surgery for AF hasn’t yet been pioneered, several products exist that provide suitable means of comparison and benchmarking. These products include an artificial ventricle employing soft robotics, the SynCardia Total Artificial Heart (TAH), and a hybrid biomechanical device developed by a team of engineers at a European defense and aerospace agency. Among all benchmark products, the artificial ventricle developed by Dr. Ellen T. Roche of Harvard University has proven the most useful in understanding various soft robotic technologies for replicating complicated motions. In addition, Dr. Roche’s work has undergone substantial validation and has proven to be a low-cost method for a product that is notoriously expensive. However, it was not developed for application with intracardiac catheters, and therefore is not suitable for this application. This team was tasked with developing a beating heart model to provide Dr. Kruger with a natural heart environment that would precisely simulate

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both the anatomy and physiology of the heart as well as the sources of disturbance present in a heart with atrial fibrillation. This model would then be used in conjunction with Dr. Kruger’s robotic system in an effort to advance the mathematical control model. METHODS

Stakeholder Needs and Specifications The primary user of the beating heart model will be Dr. Kruger'. The model must accurately simulate the environment of a human heart with AF so that the user’s robotic system can be operated and tested within our product. In a meeting with Dr. Kruger, it was confirmed that the following requirements form the basis of his needs. Material Requirements Compatibility with catheter (10/10): The device’s inlet at the right atrium must permit the insertion of a catheter. Inside the model, the septum must allow the penetration of the catheter to reach the left atrium. Conductive targets (8/10): In catheter ablation, conductive targets that transfer aberrant electrical signals within the heart must be detected by a catheter (and later, treated with an electrical signal to alter the tissue). This team’s product must contain conductive targets that will simulate these areas in a human heart. Transparency / translucency (5/10): Dr. Kruger has confirmed that the beating heart model should allow the audience to view activity inside of the heart. Thus, the user of this group’s product has made it clear that a transparent or translucent material would be preferable over an opaque one.

Compatibility with tracking (10/10): Tracking the position of the catheter in real time is a critical requirement for the user. The tracking device is a magnetic system, so the user requires this group to not include any metallic elements that may interfere with the tracking device.

Compatibility with ultrasound (5/10): The ability to monitor the system using ultrasound technology is preferred. The user requires this capability in the

event that his tracking system may not be used with any version of this group’s model. Dimensional Requirements Accurate inner dimensions (10/10): In order for the product to simulate the environment of a human heart, the physical dimensions of the atria and ventricles must lie within the normal range of a human heart.

Accurate motion (8/10): The product’s output motion due to the pumping mechanisms must accurately simulate the beating motion of a heart. Accurate flow properties (10/10): The blood-like fluid within our heart model must behave exactly like the blood in a human heart. If it doesn’t, the model will not accurately simulate the environment of a human heart and thus cannot be used as a proper environment for the user’s equipment. The specific fluid properties are discussed in the Engineering Specifications section. Blood-like viscosity (5/10): While viscosity might be addressed by the previous paragraph, the user has made a separate point for this team to use a fluid with a viscosity very similar to that of blood. If the model uses a fluid without this property, the catheters will be subject to unintended motion and forces.

Miscellaneous Requirements

Variable settings (9/10): The heart model’s ability to be switched through a variety of beat frequencies and amplitudes is important because these conditions differ among patients.

Easy replacement of atria (3/10): In the event that an atrium wall is punctured by a catheter, a method to rapidly reproduce and reinstall an atrium is preferred by the user.

Ease of operation (1/10): The user prefers a system that is simple and easy to use. Engineering Specifications The team formulated a range of engineering specifications to attribute quantifiable values to the user’s requirements. These specifications are divided into five categories: material,

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manufacturing, fluids, electrical, and budget. In a quality functional deployment (QFD) matrix, their values were weighted (and ultimately summated and analyzed) according to the user requirements. From this process, each engineering specification was designated an importance rating from 1-9. In the list below, a +, -, or N is indicated alongside every engineering specification to indicate a positive, negative, or N/A (not applicable) desirability attribute of that property as it relates to our design. Material Specifications Sensitivity to touch (+) (1/9): Since the material must react to various stimuli (i.e. physical contact, electrical impulses), the material’s strain is used to gauge its sensitivity.

Measurement unit: Strain: ε ()

Flexibility (+) (3/9): Since the material must be resilient to withstand probing and other forms of physical contact, the Young’s Modulus (stiffness) of the material is used to gauge flexibility.

Measurement unit: Young’s Modulus: E (Pa)

Porosity (-) (3/9): To maintain the proper blood flow characteristics, the heart model’s walls cannot become filled with blood. Therefore, a proper metric of the material is its porosity (ratio of volume of material’s voids to its actual volume).

Measurement unit: Percentage: % ()

Bonding ability (+) (9/9): In order for the heart model to be mounted to a surface (and to prevent against any fluid leakage), its material must be able to be sealed. For the seal to stay bonded, the material’s bonding property must be specified on a subjective scale.

Measurement unit: Subjective scale: 1-5 Durability (+) (4/9): As previously stated, the product must withstand various stimuli and probes. It must also survive long periods of use and catheterization. The material’s durability is an appropriate metric for this.

Measurement unit: Yield strength: σY (Pa)

Conductivity (+) (6/9): The heart model must contain conductive targets to simulate aberrant patches of conductive tissue in patients with AF. The material’s conductivity (or the conductivity of

any powders or additives in the product) is an appropriate unit.

Measurement unit: Conductivity (S/m)

Pressure, volume & flow detection (+) (8/9): Dr. Kruger has emphasized a comprehensively validated and simple model over an unsubstantiated yet complex model. The material selected must therefore allow for the incorporation of small measurement sensors to corroborate accurate pressure profiles, chamber dimensions, heartbeat waveforms, etc.

Measurement unit: Pressure (Pa), Volume (mL), Flow rate (mL/min)

Manufacturing Specifications Manufacturability (+) (9/9): In accordance with the user’s request for an easily replaceable atrium or part, this team believes the product’s manufacturability (its simplicity and ease of manufacturing) is an appropriate specification.

Measurement unit: Subjective scale: 1-5

Inner volume (-) (5/9): In accordance with the user’s request for exact dimensions of the human heart, this group looks to conserve as much inner volume as possible. The amount of volume conserved (as a difference in volume in comparison to that of a human heart) is the appropriate metric.

Measurement unit: Volume (m3)

Number of molds in composite (-) (9/9): In order to provide a system in which an atrium or part may be replaced, a system with variable parts (in this case, molds) is preferred. However, it is preferred that the number of molds is not excessively high, which would overcomplicate the design and manufacturing.

Measurement unit: Quantity: # Fluids Specifications Volumetric flow rate (N/A) (2/9): Keeping the fluid’s behavior in line with that of a human heart must be tracked by several fluid properties. One which stays constant throughout a system with equal mass transfer is the volumetric flow rate.

Measurement unit: m3/s Intracardiac pressure (N/A) (2/9): Intracardiac pressure is a measure of the pressure within a heart chamber (right/left atria, ventricles) at any point in

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the heartbeat cycle. The heartbeat cycle is complex, with many fluctuations valve openings/closures within a small interval of time. Thus, it is important to keep track of these pressures and design our pump system around them.

Measurement unit: mmHg

Viscosity (N/A) (3/9): In accordance with the user’s request for a fluidic viscosity equal (or extremely similar) to that of blood, the team found viscosity to be an appropriate specification for this aspect. Viscosity is also important, since it can give the team an idea of how the fluid will behave against the inner heart wall material.

Measurement unit: (m2/s) Deviation of flow speed from human system (-) (3/9): In order to determine the degree of accuracy of our system, the team could take blood flow speeds ascertained from a human system and compare values against those to produce a percentage deviation.

Measurement unit: Percentage: % () Electrical Specifications Number of circuits (-) (6/9): The amount of variable settings and degree to which the user can operate the system with ease is, in part, determined by the amount of circuitry in the system. This group quantifies this as the number of total circuits in the system.

Measurement unit: Quantity: # ()

Lines of code (+) (7/9): To achieve the same user requirement listed in the previous point, the computer code that drives the actuators and reads user inputs must be versatile and detailed. It is for this reason that a plus sign (+) is designated for this quality, but this team is mindful of the risks of an overcomplicated code.

Measurement unit: Quantity: # () Budget Specifications Total cost of materials (-) (8/9): The user has specified a target cost of 400 USD. For this reason, this group takes a conservative approach on spending and will make every effort to perform a cost/benefit analysis to determine whether a particular material is worth its price. To measure

our budget, a calculation of the total cost is employed.

Measurement unit: Price (USD) Discussion of User Requirements, Engineering Specifications After carefully gathering user requirements, assigning them engineering specifications and determining the importance level of each, our team had a solid preliminary concept of the beating heart model. According to Dr. Kruger, the most crucial elements of the model would be its compatibility with catheters (weight: 10/10), accurate inner dimensions (weight: 10/10), accurate flow properties (weight: 10/10) and variable settings (weight: 9/10). Indeed, the model would have to accommodate the insertion of catheters; otherwise, it could not be used in conjunction with the robotic system. The accurate simulation of flow patterns present in atrial fibrillation was also essential, since the feed-forward model could not be advanced otherwise. Concept Generation and Selection Paramount to the concept generation process of this project was the formulation of a functional decomposition. The many processes at hand were categorized and from the functional decomposition, the team found the three primary functions of the model to be: 1) beat heart, 2) pump fluid and 3) sense touch. Before discovering the research of Harvard University’s Whitesides Group, our team deliberated the use of very rudimentary objects to achieve the pulsations and contractions present in atrial fibrillation. Such objects included combinations of balloons, springs, fluid nozzles and motors. The work of Dr. Ellen T. Roche of Harvard University was discovered and studied extensively because it thoroughly investigated the use of affordable soft robotic actuators for purposes that were very similar to those in this project. Dr. Roche referred us to the Soft Robotics Toolkit, a small firm established by Harvard students that made available the CAD drawings and assembly instructions for various soft robotic actuators,

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including pneumatic air muscles (PAMs) and pneumatic networks (“PneuNets”). After careful consideration, the team decided to proceed with the use of pneumatic networks, since these actuators could be downsized, easily adhered to the silicone wall of a heart model, and rapidly reproduced, if need be. For methods used to pump fluid, our team sought to purchase a diaphragm-style or peristaltic fluid pump. Yet, the cost of such a pump was prohibitively high, so instead, a bilge pump was purchased, and proved to be a very economical alternative. Pump choice aside, the precise location of the pump(s) was a source of intense deliberation for this project. Before this team decided to pursue the development of only one atrium (due to budget and time constraints), it intended to construct a complete four-chamber heart, and thus questioned what the precise arrangement of pumps within the system would be. The two main arrangements in question were 1) a singular pump that begins in the right atrium and achieves fluid propulsion in a single loop throughout the heart, and 2) the use of two pumps with the right and left sides of the heart split into two independent loops for ease of construction and modeling. As stated previously, the team ultimately produced a singular left atrium instead of an entire heart, due to budget and time constraints. Dr. Kruger acknowledged that these restrictions would limit the ability to produce an entire heart. In the end, one bilge pump was used to drive the fluid through the atrium. The ability of the model to sense touch and allow the user to locate the catheter tip was essential. In comparison to the concepts generated for the previous two functions, the ones for this objective were straightforward. The use of transparent silicone, PVC or other plastic substances for the heart model was believed to be the simplest and most effective way of satisfying the user’s ability to view the position of the catheter tip. Dr. Roland Chen of the SM Wu Manufacturing Lab at the University of Michigan

further stressed the importance of transparent materials, and advised against using silicone since the material would attenuate ultrasound signals during the verification phase. Indeed, Dr. Chen urged the team to use PVC, but it was later discovered that the curing behavior of PVC presented unresolvable challenges in the manufacturing process. Thus, silicone was ultimately selected. One measure taken to prevent the formation of air bubbles (and consequent air pockets that would weaken the material, disturb the transmission of ultrasound signals, and reduce translucency) included the use of a vacuum chamber after mixing of silicone constituents. Before silicone was selected as the concept, another method under consideration was the use of conductive powder within the heart wall, which would provide the user with the capability to monitor the position of the catheter tip via transmission of electrical signals. This concept was quickly discarded and would only be considered if the use of transparent materials proved to be impossible or ineffective. Results of Concept Selection Ultimately, the above selected concepts were successfully incorporated into the final atrium model. The atrium was made of silicone, and was evacuated of air in a vacuum chamber to ensure minimal formation of air bubbles (which helped to achieve a clear color and mitigate attenuation of ultrasound signals). To accomplish the beating and randomized contractions of AF, the pneumatic networks were successfully downsized and modified for use on the atrium wall. Finally, the bilge pump also proved successful and error-free as a source of propulsion for fluid. Retrospective Changes In retrospect, very little should have been changed with respect to the components used in the atrium. Yet, difficulty was encountered in using an ultrasound phantom to analyze the fluid profiles within the atrium. This team believes a higher emphasis could have been placed on the use of proper blood-mimicking fluid to generate proper images in the ultrasound machine. While a blood-mimicking fluid was still concocted from water, glycerol and finely crushed glass beads, it did not

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allow the ultrasound to produce satisfactory images. Furthermore, in a meeting with University of Michigan cardiologist Dr. Hakan Oral, the team learned that a vital function of the AF simulation should involve the motion resulting from a patient’s respiratory system (respiratory gating). While this was brought to the attention of the team far too late in the semester, the simulation of this function is certainly an area for future work on the model. Engineering Analysis The four design drivers behind the atrium model were fluid dynamics, durability, anatomical accuracy, and intracardiac pressure. As stated, precise replication of fluid dynamics of an arrhythmic heart environment was perhaps the most important aspect of this model, as Dr. Kruger explained. As a means of theoretical modeling, ANSYS Fluent was used with the intention of identifying the flows of AF characterized by large vortex patterns. Below are ANSYS-generated flow profiles. In systole, there are proper flow dynamics, wherein flow initiates at each of the four pulmonary veins, forms small vortex-like patterns near each orifice, and leaves under laminar conditions through the mitral valve. In diastole, there is increased turbulence throughout. These conditions closely resemble the flow patterns in a heart with atrial fibrillation. Figure 3. ANSYS Fluent flow simulations of systole (left) and diastole (right) are consistent with flow patterns in AF conditions. To produce such accurate and detailed ANSYS simulations, a tetrahedral volume mesh used for computational fluid dynamics (CFD) was produced, pictured in Figure 4. 2Sil-Poxy Data Sheet, Smooth-On, Inc.

Figure 4. Tetrahedral volume mesh used for computational fluid dynamics (CFD) simulations. A durability analysis was conducted to analyze the deformation limits of our product. To better understand the deformation limits of the heart wall, a finite element simulation in SolidWorks was performed. An upper limit of deformation was set to the tear strain limit (19.60 mm) of the material based on literature values. 2 As anticipated, the deformation of the heart wall (0 mm to 8.30 mm) was well within the 19.60 mm limit, but the analysis can be used to preliminarily validate that the operating pressure is within the anatomical pressure inside the atrium. Below is a contour map from the deformation analysis. The model was deformed from its original shape in the simulation. The expanded model was used to visually check that the operating deformation is close to the simulated deformation for anatomical pressure. Figure 5. Deformation analysis reveals that the upper limit of deformation is safely within material deformation limits. The metrics under consideration for anatomical accuracy were wall thickness (which ranges from 1.5 mm to 6 mm), inner diameter (30-40 mm for men, 27-38 mm for women), and internal relaxed volume (18-58 mL for men, 22-52 mL for women).

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Anatomical accuracy was achieved by obtaining a CAD model of the heart based on MRI scans of human patients (and taking into account the above ranges), pictured below. Figure 6. The model used to generate the wax core has an inner diameter of 30.37 mm, which falls within the normal range of both male and female atria. To achieve proper replication of intracardiac pressure, the waveforms of an electrocardiogram (ECG) were studied. The P-wave of the WCG indicates the depolarization in the sinoatrial node, which in turn causes muscular contraction of both the left and right atria. This contraction is marked by an intracardiac pressure of 6-12 mm Hg in the left atrium during normal heart rhythm. Yet, the smooth P-wave is absent in patients with AF, and is instead replaced by a fibrillation wave (“F-wave”). Results from the ECG could then be mapped into a pressure profile via a Wigger diagram (pictured to the right). Drawing from the relationship between atrial pressure and electrocardiogram waveform for ordinary heart rhythm, a similar approach could be used to replicate intracardiac pressures found in AF settings. The final piece of this analysis is the incorporation of small pressure sensors into the atrium model wall. This approach (ECG to pressure profile) would allow the derivation of pulse patterns, and therefore internal pressures, directly from literature research and actual patient data.

3A. C. Guyton and J. E. Hall, 2006, Textbook of Medical Physiology, Elsevier Inc., Philadelphia, PA, Chap. 9.

Figure 7. The Wigger diagram visually illustrates the relationship between a variety of different variables throughout the cardiac cycle, including intracardiac pressures, ventricular volume, ECG signal, and heart sounds.3 RESULTS

Final Design and Prototype Pictured below and on the next page are an up-close photograph of the atrium model, two images (frontal view and rear view) of the atrium’s CAD model, and a photograph of the overall system.

Pneumatic networks (2 of 4)

Pulmonary inlets (2 of 4) Outlet to mitral valve

Figure 8. Photograph of final model with affixed pneumatic networks and fluid tubing.

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Validation

Pulmonary inlets Outlet to mitral valve Catheter insertion sleeve

Figure 10. Rear view of CAD-modelled left atriumFigure 9. Frontal view of CAD-modelled left atrium

Figure 11. Photograph of final system of heart model, tubing, fluid reservoir, solenoid valves and control board

Heart model Upstream flutter solenoid valve

Downstream mitral solenoid valve

Fluid reservoir containing pump

Arduino boards

Relay switches

Air solenoid manifold

LCD display

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While there were many functionalities of the system, the only ones worth validating were the fluid parameters. The validation experiment involving ultrasound imaging proved to be very difficult in the absence of a commercial-grade blood mimicking fluid and proper guidance in using clinical imaging software. Fortunately, these difficulties can be translated into future work for the system and are discussed in greater depth later on. A test was performed to validate that the volume of the left atrium was within the physiological range defined in literature. The atrium was removed from the system and simply filled with water to determine the volume, which was found to be 61.4 ml ± 5.5 ml. Literature values for the volume of a male’s left atrium range from 18 mL to 58 mL. Therefore, with error, our atrium is within the typical range of standard volume limits and is thereby valid. The next validation procedure for the fluid system was the determination of the relationship between pump voltage and flow rate. A linear relationship was found to exist (see Appendix). According to the calculated relationship, the proper output of 4.9 L/min was found to exist at a supplied voltage of 14.86 V. This voltage is unfortunately above the 13.6 V threshold of the pump, yet it is important to understand that AF cuts cardiac output by 20% (down to ~3.92 L/min), which occurs at approximately 13.2 V, within the voltage limit of the pump. Identification of flow patterns within the atrium was a central objective of the validation experiments, but it proved to be unfeasible. First, the cost of a commercial-grade blood-mimicking fluid (whose viscosity is precisely that of blood, and which contains microscopic particles to facilitate monitoring with an ultrasound phantom) was prohibitively high. A fluid comprising water, glycerol and crushed glass beads was concocted in the lab, but the mixture was not sufficient enough for the ultrasound to capture satisfactory images. Second, the ultrasound phantom was connected to a computer running clinical imaging software, which was foreign to the team. The graduate student familiar with the software had been away from the

laboratory, so there was no guidance in using this technology. DISCUSSION

Design Critique Overall, the design of this system was exceptional. In particular, it was durable and contained protective elements that preserved its functionalities. In retrospect, there are several areas that could have been slightly improved. In the fluid system, a direct-acting solenoid valve was used as the downstream mitral valve. A direct-acting valve was chosen because it requires no minimum pressure for operation (and the pressure downstream of the atrium is only 6-12 mm Hg). This team overlooked the high current draw of this valve. Indeed, during a presentation, the valve was left in the on position and fired continuously for about one hour, during which time the valve became very hot. Moreover, the high current draw of the valve generated a significant back EMF, which in turn severed the functionality of our button controls on the LCD screen. The design could have incorporated 1) a direct-acting solenoid valve rated at a higher voltage (and thus, one that draws less current) and 2) a snubbing diode to protect circuit elements from any back EMF generated across the valves. Another element that could have been protected more was the pneumatic network actuator placed on various sites on the atrium. In particular, closer attention could have been paid to the entrance of air pressure. An emergency shutoff or diversion valve could have proven useful in avoiding unintended air surges to the actuators. At several points, the Arduino boards were reset and the relay switches, in turn, were reset, causing the air valves to switch open for an extended period of time, delivering too much air to the actuators and causing material damage that later had to be resolved with a silicone epoxy. Future Work This system has deliver phenomenal results, but there are several improvements that should be made in the future.

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C. Coyne

Christopher Coyne is a fifth-year undergraduate with interests ranging from mechatronics and robotics to artificial heart technologies to advanced energy solutions. He’s been in the research lab since freshman year, and

has spent summers working in the semiconductor, surgical tool, insurance, and automotive industries.

health industries. He has been working as an intern at the Environmental Protection Agency: National Vehicle and Fuel Emissions Laboratory for the past three years.

A. Kurz

Alex Kurz is an undergraduate student of mechanical engineering at the University of Michigan, and has interest in the automotive and

C. Munger

Chance Munger is an undergraduate student in the mechanical engineering program at the University of Michigan. He has experience in the aerospace industry working for Northrop Grumman on the Lockheed Martin F-35 Lightning II.

S. Shrago

Samuel Shrago is a fifth-year undergraduate student of mechanical engineering with a minor in German at the University of Michigan. He is currently interested in the biomedical applications of mechanical engineering. He works a side job as a developer at the University of Michigan Medical School, where he works on prototyping low-cost medical sensors for use in clinical settings.

First, the addition of respiratory gating – the resultant cardiac motion of a patient’s respiratory motion during surgery – is an essential component of simulating a dynamic environment for Dr. Kruger’s system. It is advisable to include a system that synchronizes this function with the heartbeat, so that both the intracardiac properties (i.e. flow profiles) in addition to external motion (respiratory gating) can be simulated. Second, the use of commercial-grade blood mimicking fluid (instead of an in-lab concoction of water, glycerol and glass beads) is highly advised in order to obtain satisfactory results from the ultrasound trials. Moreover, the guidance of an ultrasound technician or qualified researcher is recommended when using the ultrasound phantom. Third, a method by which the atrium can be produced rapidly – say, in one or two steps – instead of a convoluted series of molding would be preferred. It came to the attention of this team that such a procedure could be possible. Specifically, 3D printing a thin “shell” of the atrium, which once filled with silicone and left time to cure, could then be broken and removed, leaving a wholesome model without any messy, time-consuming intermediate steps. In fact, the team developed said mold, but was unable to print it due to unavailability of resources and a strict budget. Fourth, the addition of snubbing diodes and other circuit elements to limit back EMF generated across the solenoid valves would be preferred, as the effects of back EMF have presented challenges in using the LCD display’s button controls. Moreover, the direct-acting solenoid valve deployed downstream of the atrium draws high amounts of current (up to 1A), so a valve of a higher voltage rating (which would in turn draw less current) is preferable, in addition to a heat transfer solution to dissipate heat from the valve. ACKNOWLEDGEMENTS

We would like to acknowledge our sponsor, Dr. Grant H. Kruger of the SM Wu Manufacturing Center at the University of Michigan. In addition, we would like to thank Professor Jun Ni, Ph.D.,

Dr. Xioning Jin, Barry Belmont, Robert Chisena, Alex Price and Dr. Hakan Oral for their guidance. AUTHORS

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REFERENCES 1. G. Bian, M. Lipowicz, and G. H. Kruger.

“Self-Learning of Inverse Kinematics for Feedforward Control of Intracardiac Robotic Ablation Catheters,” pp. 1-6.

2. Sil-Poxy Data Sheet, Smooth-On, Inc. 3. A. C. Guyton and J. E. Hall, 2006, Textbook

of Medical Physiology, Elsevier Inc., Philadelphia, PA, Chap. 9.

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APPENDIX Linear relationship between flow rate and bilge pump voltage:

Voltage (V)

Volume (mL)

Time (sec)

Flow Rate (L/min)

9.0 418 15 1.672 405 15 1.62 461 15 1.844

AVG 428 15 1.712 10.0 552 15 2.208

536 15 2.144 553 15 2.212

AVG 547 15 2.188 11.0 679 15 2.716

661 15 2.644 670 15 2.68

AVG 670 15 2.68 12.0 862 15 3.448

841 15 3.364 838 15 3.352

AVG 847 15 3.388

4.9 L/min occurs at: 14.86 V*

*with water as the working fluid