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Keywords = bionic test-bed

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18 pages, 2277 KiB  
Article
A Bionic Testbed for Cardiac Ablation Tools
by Wei-Han Lin, Zhijie Zhu, Vasanth Ravikumar, Vinod Sharma, Elena G. Tolkacheva, Michael C. McAlpine and Brenda M. Ogle
Int. J. Mol. Sci. 2022, 23(22), 14444; https://doi.org/10.3390/ijms232214444 - 21 Nov 2022
Cited by 1 | Viewed by 2584
Abstract
Bionic-engineered tissues have been proposed for testing the performance of cardiovascular medical devices and predicting clinical outcomes ex vivo. Progress has been made in the development of compliant electronics that are capable of monitoring treatment parameters and being coupled to engineered tissues; however, [...] Read more.
Bionic-engineered tissues have been proposed for testing the performance of cardiovascular medical devices and predicting clinical outcomes ex vivo. Progress has been made in the development of compliant electronics that are capable of monitoring treatment parameters and being coupled to engineered tissues; however, the scale of most engineered tissues is too small to accommodate the size of clinical-grade medical devices. Here, we show substantial progress toward bionic tissues for evaluating cardiac ablation tools by generating a centimeter-scale human cardiac disk and coupling it to a hydrogel-based soft-pressure sensor. The cardiac tissue with contiguous electromechanical function was made possible by our recently established method to 3D bioprint human pluripotent stem cells in an extracellular matrix-based bioink that allows for in situ cell expansion prior to cardiac differentiation. The pressure sensor described here utilized electrical impedance tomography to enable the real-time spatiotemporal mapping of pressure distribution. A cryoablation tip catheter was applied to the composite bionic tissues with varied pressure. We found a close correlation between the cell response to ablation and the applied pressure. Under some conditions, cardiomyocytes could survive in the ablated region with more rounded morphology compared to the unablated controls, and connectivity was disrupted. This is the first known functional characterization of living human cardiomyocytes following an ablation procedure that suggests several mechanisms by which arrhythmia might redevelop following an ablation. Thus, bionic-engineered testbeds of this type can be indicators of tissue health and function and provide unique insight into human cell responses to ablative interventions. Full article
(This article belongs to the Special Issue Stem Cell Biology & Regenerative Medicine)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Schematic image showing the process of pulmonary vein ablation (two of four veins shown). (<b>B</b>) Schematic image showing the bionic myocardial testbed with pressure-sensing capability.</p>
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<p>(<b>A</b>) Schematic image showing the layered design of the hydrogel-based pressure sensor with the inset image showing an infinitesimal region within the hydrogel layer. (<b>B</b>) Photograph of the fabricated hydrogel-based pressure sensor. (<b>C</b>) Plot showing the curves to predict the applied pressure based on inputs from a hydrogel sensor. The linear curves are fitted from the calibration dataset consisting of applied pressure (measured with the force gauge) and the variation in conductance (measured with the hydrogel sensor) in a 34 °C water bath and under room temperature (<span class="html-italic">n</span> = 15 readings from at least 3 different hydrogel sensors). G denotes conductance under pressure, G<sub>0</sub> denotes initial conductance without pressure. (<b>D</b>) Plot showing the detected and intended positions of point-wise compression at multiple locations on the sensor in 34 °C water bath (<span class="html-italic">n</span> = 20). (<b>E</b>) Images showing the map of variation in conductance defined by (G − G<sub>0</sub>)/G<sub>0</sub> (left), and the estimated pressing region (in black) and catheter location (blue circle) within the circular sensing region.</p>
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<p>Cardiac disk preparation and characterization. (<b>A</b>) Cardiac disks were bioprinted with the bioink composed of human-induced pluripotent cells (hiPSCs) and extracellular proteins. The inset in subfigure iv represents a differentiated cellular disk with a scalpel-made marker for structure orientation. CM indicates cardiomyocyte; ColMA, collagen methacrylate; FN, fibronectin; GelMA, gelatin methacrylate; and LN, laminin-111. (<b>B</b>,<b>C</b>) Calcium traces generated from differentiated CMs in 3 different patches and the corresponding calcium upstroke and downstroke velocities. (<b>D</b>) Spatiotemporal calcium activity of a disk with 1 Hz pacing including isochronal maps of calcium response duration at 80% of repolarization (CaD80) and the activation time at 50% of depolarization (AT); red asterisks represent the site of pacing.</p>
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<p>Calcium intensities after cryoablation and recorded pressure profiles along the radius of disks are presented in the same figure to show the correspondence. (<b>A</b>–<b>C</b>) represent the conditions of normal pressure with cryoablation, minimum pressure with cryoablation, and normal pressure without cryoablation, respectively. The red dots and the black dots indicate the recorded pressures and the calcium intensities of cardiomyocytes from the same radius of each disk, respectively. (<b>D</b>–<b>F</b>) are reconstructed conductance maps showing three pressing locations under normal pressure with cryoablation, minimum pressure with cryoablation, and normal pressure without cryoablation, respectively. The gray-dotted lines indicate the pressure profiles in figure (<b>A</b>–<b>C</b>). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 for comparison between the pre-ablation group and the post-ablation group (<span class="html-italic">n</span> = 3), two-tailed Student’s <span class="html-italic">t</span>-test. # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 for comparing to the group nearest to the disk center (0.2 mm) (<span class="html-italic">n</span> = 3), 1-way ANOVA with Tukey post hoc test.</p>
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<p>Cell and tissue responses to the cryoablation. (<b>A</b>) From left to right, the non-ablated disk under brightfield, staining for cardiac muscle layer via cTnT (cardiac troponin T) and DAPI on the surface of the non-ablated disk, and a high-magnification image of cell structures of the non-ablated disk stained via cTnT, DAPI and CX43 (connexin 43). (<b>B</b>) From left to right, the ablated disk under brightfield, staining for cardiac muscle layer via cTnT (cardiac troponin T) and DAPI on the surface of the ablated disk, and a high-magnification image of cell structures of the ablated disk stained via cTnT, DAPI and CX43.</p>
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26 pages, 14241 KiB  
Article
A Wearable Body Controlling Device for Application of Functional Electrical Stimulation
by Nazita Taghavi, Greg R. Luecke and Nicholas D. Jeffery
Sensors 2018, 18(4), 1251; https://doi.org/10.3390/s18041251 - 18 Apr 2018
Cited by 8 | Viewed by 5668
Abstract
In this research, we describe a new balancing device used to stabilize the rear quarters of a patient dog with spinal cord injuries. Our approach uses inertial measurement sensing and direct leg actuation to lay a foundation for eventual muscle control by means [...] Read more.
In this research, we describe a new balancing device used to stabilize the rear quarters of a patient dog with spinal cord injuries. Our approach uses inertial measurement sensing and direct leg actuation to lay a foundation for eventual muscle control by means of direct functional electrical stimulation (FES). During this phase of development, we designed and built a mechanical test-bed to develop the control and stimulation algorithms before we use the device on our animal subjects. We designed the bionic test-bed to mimic the typical walking gait of a dog and use it to develop and test the functionality of the balancing device for stabilization of patient dogs with hindquarter paralysis. We present analysis for various muscle stimulation and balancing strategies, and our device can be used by veterinarians to tailor the stimulation strength and temporal distribution for any individual patient dog. We develop stabilizing muscle stimulation strategies using the robotic test-bed to enhance walking stability. We present experimental results using the bionic test-bed to demonstrate that the balancing device can provide an effective sensing strategy and deliver the required motion control commands for stabilizing an actual dog with a spinal cord injury. Full article
(This article belongs to the Special Issue Wearable Smart Devices)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Injured dog at balance, (<b>b</b>) Dog at the critical timing before falling, (<b>c</b>) Dog has fallen.</p>
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<p>3D model of replica.</p>
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<p>Small scale muscle stimulator used for preliminary tests.</p>
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<p>(<b>a</b>) The replica, (<b>b</b>) Arduino boards, IMU, and electronic connections.</p>
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<p>Hip joint angle as a function of time (<b>a1</b>) One term of Fourier series approximation (<b>a2</b>) One term approximation error (<b>b1</b>) Two terms of Fourier series approximation (<b>b2</b>) Two terms approximation error (<b>c1</b>) Three terms of Fourier series approximation (<b>c2</b>) Three terms approximation error (<b>d1</b>) Four terms of Fourier series approximation (<b>d2</b>) Four terms approximation error (<b>e1</b>) Five terms of Fourier series approximation (<b>e2</b>) Five terms approximation error (<b>f1</b>) Six terms of Fourier series approximation (<b>f2</b>) Six terms approximation error.</p>
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<p>Knee joint angle as a function of time. (<b>a1</b>) One term of Fourier series approximation (<b>a2</b>) One term approximation error (<b>b1</b>) Two terms of Fourier series approximation (<b>b2</b>) Two terms approximation error (<b>c1</b>) Three terms of Fourier series approximation (<b>c2</b>) Three terms approximation error (<b>d1</b>) Four terms of Fourier series approximation (<b>d2</b>) Four terms approximation error (<b>e1</b>) Five terms of Fourier series approximation (<b>e2</b>) Five terms approximation error (<b>f1</b>) Six terms of Fourier series approximation (<b>f2</b>) Six terms approximation error.</p>
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<p>Hock joint angle as a function of time. (<b>a1</b>) One term of Fourier series approximation (<b>a2</b>) One term approximation error (<b>b1</b>) Two terms of Fourier series approximation (<b>b2</b>) Two terms approximation error (<b>c1</b>) Three terms of Fourier series approximation (<b>c2</b>) Three terms approximation error (<b>d1</b>) Four terms of Fourier series approximation (<b>d2</b>) Four terms approximation error (<b>e1</b>) Five terms of Fourier series approximation (<b>e2</b>) Five terms approximation error (<b>f1</b>) Six terms of Fourier series approximation (<b>f2</b>) Six terms approximation error.</p>
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<p>(<b>a</b>) RMS for hip joint angle, (<b>b</b>) RMS for knee joint angles, (<b>c</b>) RMS for hock joint angles based on the number of Fourier series, (<b>d</b>) Magnitude of Fourier series for hip joint, (<b>e</b>) Magnitude of Fourier series for Knee joint, (<b>f</b>) Magnitude of Fourier series for hock joint.</p>
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<p>Three-link manipulator model. (<b>a</b>) Robot model, (<b>b</b>) Manipulator model</p>
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<p>Bionic dog gait.</p>
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<p>Bionic dog modified gait.</p>
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<p>(<b>a</b>) Modified hip joint angle, (<b>b</b>) Modified hock joint angle.</p>
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<p>3D model of two legs. α is the hip angle with the ground.</p>
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<p>Hip position change during stimulation using strategy number 1.</p>
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<p>Strategy 1, raise or lower the contact leg to level the pelvis.</p>
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<p>Hip position change during stimulation using strategy number 2.</p>
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<p>Strategy 2, move the body only in the vertical direction.</p>
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<p>Required motion for monotonically (<b>a</b>) increasing the hip angle and (<b>b</b>) decreasing the hock angle.</p>
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<p>System output for hip joint angle. (<b>a1</b>) One term of Fourier series system output (<b>a2</b>) One term output error (<b>b1</b>) Two terms of Fourier series system output (<b>b2</b>) Two terms output error (<b>c1</b>) Three terms of Fourier series system output (<b>c2</b>) Three terms output error (<b>d1</b>) Four terms of Fourier series system output (<b>d2</b>) Four terms output error (<b>e1</b>) Five terms of Fourier series system output (<b>e2</b>) Five terms output error (<b>f1</b>) Six terms of Fourier series system output (<b>f2</b>) Six terms output error.</p>
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<p>System output for hock joint angle. (<b>a1</b>) One term of Fourier series system output (<b>a2</b>) One term output error (<b>b1</b>) Two terms of Fourier series system output (<b>b2</b>) Two terms output error (<b>c1</b>) Three terms of Fourier series system output (<b>c2</b>) Three terms output error (<b>d1</b>) Four terms of Fourier series system output (<b>d2</b>) Four terms output error (<b>e1</b>) Five terms of Fourier series system output (<b>e2</b>) Five terms output error (<b>f1</b>) Six terms of Fourier series system output (<b>f2</b>) Six terms output error.</p>
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<p>RMS error between system output and approximated function for (<b>a</b>) hip joint angles and (<b>b</b>) hock joint angles based on the number of Fourier series.</p>
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<p>Hip balancing experiment, (<b>a</b>) IMU installed on hip, (<b>b</b>) balanced hip, (<b>c</b>) unbalanced hip.</p>
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<p>Hip balancing test results for hip joint angle changes.</p>
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<p>Hip balancing test results for hock joint angle changes.</p>
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<p>Hip balancing test results for hip joint angle changes.</p>
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<p>Hip balancing test results for hock joint angle changes.</p>
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