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A semi-dynamic heart model for UWB microwave transmission simulations and hardware

evaluation

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2015 Biomed. Phys. Eng. Express 1 045005

(http://iopscience.iop.org/2057-1976/1/4/045005)

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Biomed. Phys. Eng. Express 1 (2015) 045005 doi:10.1088/2057-1976/1/4/045005

PAPER

A semi-dynamic heart model for UWBmicrowave transmissionsimulations and hardware evaluation

Marcel Seguin, Jeremie Bourqui, Elise Fear andMichalOkoniewskiDepartment of Electrical andComputer Engineering, University of Calgary, Calgary, Canada

E-mail:msseguin@ucalgary.ca

Keywords: hemodynamics, heartmodel,microwave sensing, heart simulation, heart dynamics,microwavemonitors

AbstractIn this paper, we present a simplified semi-dynamic heartmodel for investigation ofmicrowavetransmission heartmonitoring systems between 1.5 and 4 GHz in both simulation andmeasurement.We aim to validate that our proposed heartmodel is able to represent the heart structure atmicrowavefrequencies by comparing ourmodel to an accurate numerical heartmodel (anHM) from the ITISfoundation virtual population. Our simple numerical heartmodel (snHM) (simulation) and physicalheartmodel (pHM) (measurement) are evaluated in a simplified human chestmodel using anUWBbiomedical sensor. In simulation, the transmission parameter shows agreement with the time domainpeak of−94.5 dB for the snHMand−96.4 dB in the anHM.The anHMand pHM transmission signalcharacteristics were then compared showing good agreement. Our heartmodel is able to represent theheart between 1.5 and 4.0 GHz and represents a step toward a real time dynamic heartmodel forhardware evaluation.

1. Introduction

Microwave heart monitoring has been explored for arange of hemodynamic parameters. Vital signs, heartpressure wave, wall motion, and volume change havebeen sensed usingmicrowave systems [1–6].

Human testing is commonly used for evaluation ofmicrowave heart monitors [1, 3–5]. This subjects thesystem to the complex structure and motion of thehuman chest. However, in human tests it is difficult tocontrol specific variables or perform repeated studiesto optimize system parameters. Conversely, modelsallow for specific parameters to be manipulated asdesired and give a consistent test environment formultiple evaluations of a system. We are thereforeinterested in producing a dynamic heart model formicrowave hardware evaluation. Simulation-basedstatic and dynamic heart models have been developedfor EM and othermodalities [2, 4, 7–11]. Manymicro-wave specific heartmodels are for dosimetric purposesand do not mimic the heart motion. To the author’sknowledge, there are no constructible microwaveheart models that mimic the motion and volumechange of a four chamber human heart. Here, weintroduce a semi-dynamic heart model with this

functionality that can be implemented for both simu-lation and hardware evaluation.

In developing our HM, a set of requirements wasdetermined: the model must approximate heartmotion, be reconfigurable, be volumetrically accurate,and be manufacturable. The ability of the model tomimic the motion and volumetric change of the heartwas prioritized as these parameters are known to haveeffects on a transmitted microwave signal [5, 6]. TheHM needs to be constructible in a standard laboratoryenvironment. Anatomical detail was not considered tobe important in the frequency range of interest(1.5–4 GHz).

In this project, we aimed to adapt a heart modelfrom literature for other modalities to use with micro-wave transmission systems. Three general categoriesof dynamic heartmodels were identified: voxelmodels[10, 11], spline approximations (hybrid)models [7, 8],and geometric models [9]. Spline approximation are

models that approximate the complex surfaces of theheart chambers with smoothed splines. Geometricmodels represent the heart with simple geometricshapes (e.g. spheres). Resolution, structural accuracy,and complexity differ between themodels as summar-ized in table 1.

RECEIVED

6 July 2015

REVISED

28August 2015

ACCEPTED FOR PUBLICATION

28 September 2015

PUBLISHED

6November 2015

© 2015 IOPPublishing Ltd

The geometric dynamic heart model presented in[9] was found to be a suitable template for our HM.The model gives a simplified representation of theheart chambers, changes in volume, andmotion of theheart. The model is constructible using a techniquedescribed in [12]. Note that we generate our heartmodel as stages of the cardiac cycle, with no real timevolume change. Therefore as implemented, it does notallow for real time hardware evaluation. However, itprovides a step towards a real time dynamic heartmodel for microwave transmission heart monitorevaluation.

The objective of this paper is to implement a phy-sically constructible heart model that has sufficientaccuracy at microwave frequencies. We being by out-lining the HM implementations in both simulationand measurement in section 2. Next, we discuss eva-luation methods and test equipment in section 2.1.The results and analysis of both the simulation andexperimental heartmodel are given in section 3.

2. Proposedmethods

The HM structure, as described in [9], is based onellipsoids with each heart chamber represented by twohalf ellipsoids; one defining the blood pool (innerchamber) and one defining heart muscle (outer shell).The cardiac cycle is then mimicked by changing thedimension and relative centers of each half ellipsoid.The atria of the heart grow as the ventricles contractduring ventricle ejection and the opposite occurswhenthe ventricles fill. To model the ‘wringing’ motion ofthe heart, a 14° rotation is applied, centered aroundthe mid-point of the left ventricle (LV) [9]. Thestructure and dimensions of the HM are shown infigure 1.

Total volume change in the heart during the car-diac cycle is considerably smaller than the bloodvolume ejected from the ventricles [9, 12–16]. Theheart can be approximated as a volume invariantpump [14]. This is a major detraction for microwavetransmission technologies. Bulk dielectric propertiesare determinable from microwave transmission sig-nals [17, 18] but without a significant change in bloodvolume, total signal variation may be very low or notmeasurable. For this reason, the HM was imple-mented to be total volume invariant over the cardiaccycle. However, the HM can be implemented to haveany desired volumetric change.

To implement our simple numerical heart model(snHM) for simulation, a MATLAB script was used to

generate the ED and ES stages of the heart cycle. Thisscript defines a blood pool and a muscle wall for eachof the four chambers of the heart. These entities arevoxelized as as 0.5 mm x 0.5 mm x 1mm cubes to beused in simulation.

We then fabricated the HM using tissue mimick-ing material and construction method from [18]. Theurethane rubber material tissue mimicking material islossy, dispersive and has 25.r ¢ » The mixture usedfor physical heart model (pHM) consisted of 4% car-bon black, 30% graphite, and 66% urethane rubber byweight andwill be referenced asCB-TMM.

We build the outer shape of ED and ES stages, withapproximate wall thickness of 5 mm, and then fill theinner volume with a liquid tissue mimicking material.We take this approach as the urethane rubber tissuemimicking material does not have the dielectric prop-erties of heart materials, having lower conductivityand much lower r ¢. We therefore limit the amount ofCB-TMM in the heart model in order to ensure thatinner volume of the pHM stages will have a largereffect on the average dielectric properties. We thenchoose an inner material to achieve average dielectricproperties close to that of the heart. The outline of thisshell is shown infigure 1.

The pHM stages were formed with CB-TMMusing compression molds designed in Solidworks(Dassault Systemes, France) and 3D printed using aMakerbot Replicator 2 (MakerBot Industries, USA).For each heart stage, the atria and the ventricleswere molded separately and then fastened togetherusing CB-TMM. The two pHM stages are shown infigure 2.

2.1. Experimental design andmethodologyWe chose to evaluate our HM in a simplifiedrepresentation of the adult male chest, based on themodel presented in [4]. We represent the thorax bythree layers; two outer layers representing the skin andan inner liquid to approximate the interior composi-tion of the chest (primarily lung). This simplisticmodel is chosen as it allows for comparisons betweensimulation andmeasurement, as we can construct thissimple model. We use planar layers of CB-TMM torepresent the skin and water to fill the center volumeof the test environment. Water was chosen due tosimplicity, loss characteristics, and contrast to CB-TMM. The test environment, with dimensions isshown in figure 3. The simulation and measurementtest environments are shown figure 4.

To validate that our HM is able to represent thestructure of the heart at microwave frequencies withreasonable accuracy, we compare the transmissionsignal characteristics of ourHM to an accurate numer-ical heartmodel (anHM). The anHM is taken from theadult male in the IT’IS foundation virtual population[10], which are a set of anatomically detailed humanbody models generated from voxelized MRI data. TheanHM is shown in figure 5. We test the anHM in the

Table 1.A comparison of dynamic heartmodels.

Model type Accuracy Complexity Construction

Imaging data High High Very difficult

Spline Medium Medium Difficult

Geometric Low Low Easier

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three layer approximation of the chest previouslydescribed, giving a common test environmentbetween all three models (anHM, snHM, and pHM).The anHM is voxelized in 2 mmx 2mmx 2mm cubes

at the same orientation as the snHM. This positionsthe apex of the RV and LV downward (see figure 4).Note that the stage of the cardiac cycle that the anHMrepresents is unknown.

Figure 1.HMdimensions at ED and ES fromboth side view ((a) and (c), respectively) and valve plane (VP) of the ventricles ((b) and(d), respectively) (dashed line in side view). The blood pool (light red) and heartmuscle (both dark red and black) is shown for eachchamber. The constructed structures are outlined in black. The left atrium (LA), right atrium (RA), left ventricle (LV), right ventricle(RV), and septum (S) are labeled in the side view.

Figure 2.The 3Dprinted ventriclemoulds (a) and the two pHMstages (b)with the ES on the left and EDon the right. The 1/4 PVCpipes, in combinationwith thewood supports, suspend the stage in the tank and allow for the inner chambers to be filled.

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All three heart models are positioned in the centerof the test environment for all dimensions as shown infigure 5. Two of the UWB sensors described in [23]were used to evaluate the HM both in simulation andin measurement. These sensors are designed for con-tact transmission biomedical applications and aretherefore well suited for interrogating the heartmodels.

The snHM voxels, anHM, voxels and the CADmodel of the test environment were imported intoSEMCADXV14.8 (SPEAG, Switzerland). UWB simu-lations were run from 1 to 4 GHz with absorbingboundary conditions in an finite difference time

domain solver. To allow creeping waves around thetank to be simulated, 8l free space padding wasadded along the sides of the tank.

For all simulations, one pole Debye models wereused to model the dispersive dielectric properties ofthe materials [22]. First, we determined the dielectricproperties of each material used in this study over ourfrequency range. CB-TMM and water dielectric prop-erties were determined using the open ended coaxialprobemethod [19, 20]. Blood and heartmuscle dielec-tric properties were taken from the ITIS tissue data-base [21]. We then fit the dielectric properties of all ofthe materials to single pole Debye models using a

Figure 3.Test tank front view (a) and cross sectional view (b)with dimensions (inmm). The test tank structure (gray)was 3Dprinted.The sidewalls are sealedwith theCB-TMM. layers of CB-TMM (black). The planar layer on the front and back of the tank is held inplace with a plexiglassmount (light gray). The tank isfilledwith a liquid TMM (blue). Note that the outline shows the top and bottomwidths of the 3Dprinted structure.

Figure 4. Simulation (a) andmeasurement (b) test environment withUWB antennas in contact.

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Matlab script [20]. The Debye parameters are given intable 2.

The pHM transmission parameters were mea-sured with two UWB sensors in custom holders and avector network analyzer (PNA-X, Keysight Technolo-gies Inc., USA). Measurements were taken from 1 to5 GHz (linear sweep, 201 points, IF bandwidth: 1 kHz,averaging: off, source power:+8 dBm, dynamic range:110 dB).

All data collected in simulations and measure-ments were down sampled to baseband and convertedto time domain using the chirp Z transform algorithmas described in [24]. The time domain signals areformed from a uniform excitation voltage that pro-duces a + 10 dBm transmission power at all fre-quencies (Z0 = 50 W). A Tukey window that equalsunity from 1.5 to 18.5 ns was applied to the simulationdata to limit frequency domain sidelobes caused by thefinite simulation length (20 ns). The frequencydomain data was not pulse shaped as the spectra natu-rally tapers, due to the cutoff frequency of the anten-nas (low frequency) and path loss (high frequency).

3. Results and analysis

The transmission signals of both snHM stages areshown in figure 6. All simulation signals have twodominant peaks in time domain: a primary peak atapproximately 8.9 ns and the secondary peaks atapproximately 11.1 ns.

The 11.1 ns peaks were suspected to be scatteredpaths. To confirm this, simulations were run with a15 mmplanar layers placed along the sidewall with the

r ¢ of tap water but with conductivity increased by20%. Such layers will attenuate paths with compo-nents along the sidewall of the simulation environ-ment. The 11.1 ns path was attenuated by 0.77 dBwhile the 8.9 ns path remained unchanged, confirm-ing that the 11.1 ns signal component is dependent onthe sidewalls. We therefore we examine the 8.9 ns pathprimarily.

The snHM showed small variations between theED and ES stages (see figure 6). The time of arrival(TOA) was unchanged between stages which wasexpected as heart muscle and blood have very similar

r ¢. Contraction of the inner chamber should thereforehave small effect on the average r ¢ sensed. The con-ductivity of blood is higher than that of heart muscle,resulting in a small increase in signal strength from theED stage to ES stage (0.44 dB) which is in agreementwith literature [5]. Note that snHM is examined in asimplistic test environment with the specific antennaalignment used in this evaluation. The signal strengthvariation achieved over the cardiac cycle could begreater with a more realistic thorax model and withoptimal antenna placement.

Figure 5.The anHM (a) from the ITIS foundation virtual population [10]. The anHM is positioned in the test environment (b) at thesame orientation as the snHM (c).

Table 2.One poleDebye parameters for allmaterials [20, 22]. Thedielectric properties ofHeartmuscle and blood are from [21]. Allothermaterial dielectric properties were found using the coaxialprobemethod [19, 20].

Material r, ¥ rD S ms1( )s - ps( )t

CB-TMM 19.73 11.96 0.97 61.81

Water 7.6 70.5 0.102 9.00

2.5% sucrose 6.86 59.7 0.104 9.48

Heartmuscle 32.5 26.0 1.08 24.7

Blood 28.9 32.0 1.39 18.5

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Figure 6 shows the transmission signal character-istics between the snHM and the anHM are in goodagreement for both material compositions. The TOAof all peaks, the magnitudes of the peaks, and multi-path behavior were consistent between our model andthe anHM. The TOAs of the main peaks are identicaland the secondary peaks are also closely aligned atapproximately 11.1 ns. The maximummagnitude dif-ference between the signals for the snHM and theanHM was 1.90 dB which is small relative to theapproximately 95 dB of attenuation of the timedomain peak.

We then compared the pHM to the anHM. Toperform this comparison, we first evaluated how closethe behaviour of the simulation andmeasurement testenvironment were for a transmission signal whenthere is no heart model present. The TOA was 9.10 nsin simulation and 8.82 ns in measurement, which willresult in a 280 ps offset between all measurement andsimulation data. We correct for this TOA offset in our

comparisons between the pHM and anHM. The mag-nitudes were similar, within 1.27 dB between simula-tion and measurement (375 μV and 434 μVrespectively). Possible sources of error include mate-rial dielectric properties estimation error, antennasimulation model error, sensor alignment error, themeasurement antenna holders, and CB-TMM thick-ness variability.

Good agreement was achieved with our referencemodel (anHM)when the correct inner chambermate-rial is chosen for each stage of the pHM (see figure 7).This demonstrates that the inner dielectric of the pHMcan be used to achieve the desired average dielectricproperties. When the pHM ED stage inner chamberwas filled with water, we achieved good agreementwith the anHM (see figure 7). The signal magnitudewas within 2.67 dB of the anHM and the TOA waswithin 190 ps. The ES stage of the pHM was in closeagreement when the inner chamber was filled with a2.5% BW sucrose in water mixture (see figure 7). The

Figure 6.The results from the two stages of the snHM (EDsnHM andESsnHM) compared to the accurate numerical heartmodel (anHM)in frequency domain (a) and time domain (b) for ED and ES stages. The time domain graphs are zoomed to display the twomajorpeaks found in the time domain signals.

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dielectric properties of 2.5% BW sugar in water mix-ture are given in table 2. The pHM signal magnitudewas within 0.34 dB of the anHM and the ΔTOA was120 ps.

The secondary peak do not show close agreementbetween simulation andmeasurement, with the simu-lated secondary peaks having much higher signalstrength. As this secondary peaks were shown to bedependent on scattered paths off of the sidewalls ofour simplified thoraxmodel, the difference is expectedto be due in part to errors in antenna alignment inmeasurement, errors in material dielectric propertyestimation in simulations, and highly variable thick-ness of the CB-TMM wall coating in the physical testenvironment (±3 mm).

4. Conclusion

A semi-dynamic heart model for UWB microwavetransmission simulation and experimentation is

introduced. The heart model mimics the structure,motion, and volume change of the human heart. Thismodel allows for repeatable, controlled parameteranalysis in both simulation and hardware for micro-wave transmission basedmonitoring systems.

To validate our heart model, we compare thetransmission signal characteristics to those of a non-dynamic, anHM from the ITIS virtual population [10].Results show that the simplified structure of ourHM isable to approximate the heart from 1.5 to 4 GHz inboth simulation and in measurement. Comparing ourheartmodel to previous work, it is the only four cham-ber heartmodel that can bothmimic the heart dynam-ics and can be constructed for microwave hardwareevaluation. Other models can accurately represent thestructure of the heart [7, 8, 10] and certain modelsallow for simulation of the heart cycle [7, 8]. Nomodelfound in literature was able to accomplish this formicrowave hardware however.

Only as small signal difference is shown over thecardiac cycle of our HM. However, this difference

Figure 7.The results from the two stages of the pHM (EDpHM and ESpHM) compared to the anHM in frequency domain (a) and timedomain (b). The ESpHM stage isfilledwith 2.5%BWsucrose in tapwater while the EDpHM isfilledwith tapwater.

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could more substantial with proper antenna align-ment, heart volume variation over the cardiac cycle,and amore complex thoraxmodel.

The HM could be improved by better representa-tion of the structure of atria and base of the heart.Improvements to the construction process and use ofmore flexible TMMcould allow for theHM to providereal time modeling of the cardiac cycle. Modeling oflung motion and other lung effects would formanother innovative addition to the model. Currently,we utilize the HM for testing a microwave transmis-sion based cardiac outputmonitor we have designed.

Acknowledgments

The authors would like to thank AITF, NSERC, andthe Alvin Libin foundation for their financial support.

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