BioMed Theses

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    Using machine learning to predict f-actin morphology of endothelial cells: An application for mechanobiology models
    (Wichita State University, 2023-05) Hafenstine, Rex W.; Long, David S.
    The expansive monolayer of cells in direct contact with blood is called the endothelium. The endothelium is fundamentally involved with almost every human disease. The endothelium is composed of endothelial cells (EC)s that exhibit structural and phenotypical heterogeneity that vary in time and space. These cells exhibit emergent properties that allow communication with neighboring cells. Since experimental observation of ECs at a single cell level will not provide complete details on these behaviors, other techniques are needed. One method for observing these emergent properties is through 3D dynamic response of cell shape and morphology. Live-cell imaging is limited, such as the number of structures or events that can be imaged. Therefore, incorporating a complementary method such as machine learning (ML) could be a feasible option. To validate if ML could predict 3D f-actin fibers from only the cell membrane, human dermal microvascular endothelial cells were grown to confluence, the cell membrane, nucleus, and f-actin were fluorescently labeled, and imaged with confocal microscopy. The images were processed via normalization techniques, segmented, augmented, and filtered before being introduced into a conditional generative adversarial network (cGAN). The f-actin predictions from the cGAN did not perform at a level previously seen when predicting 3D nucleus and focal adhesion (FA) structures. However, these results do not necessarily mean that the f-actin fibers cannot be predicted but may require different methods, such as tuning the cGAN parameters (batch size and additional learning rates), obtaining more raw images, or testing different deep learning (DL) algorithms. Future work should also include testing a primary cell line of human dermal blood endothelial cells to minimize cell overgrowth, transfecting the cell with a K-Ras CAAX motif to improve cell membrane labeling, and developing new image similarity metrics to compare the predicted f-actin images with their corresponding ground truth images.
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    A bluetooth-enabled, light weight, flexible epidermal electronic system for ECG monitoring
    (Wichita State University, 2022-12) Chowdhury, Rakhi; Lee, Yongkuk
    With 17.9 million deaths annually, cardiovascular diseases (CVDs) have become the leading cause of mortality worldwide. This increased death rate creates a significant need for long-term ambulatory ECG monitoring for early diagnosis and treatment. Commercially existing ECG monitors use rigid materials, aggressive adhesives, and lack mechanical compliance with skin. Here, a wireless, Bluetooth-enabled, flexible, low-profile epidermal ECG monitoring device is presented with high-quality ECG signals. Electrode placements with different distances are investigated to find the optimal placement position of the electrode on the chest for identical readings with traditional ECG lead I and II. Afterward, the dry electrode and circuit are microfabricated using 2 $\mu{m}$-thick copper foil. The functionality of the electrode is demonstrated with stretchability, contact impedance, and EMG SNR measurement. The device's functionality is presented with a flexibility test, antenna performance test, RSSI measurement, and ECG signal collection. Contact impedance values for gel and dry electrodes are comparable, which are 3.94 and 3.96, respectively. Also, EMG SNR values are comparable for gel and dry electrodes, with 18.12 dB and 17.84 dB, respectively. Mechanical and electrical experiments suggest a 2 mm radius of curvature at 180° bending as the maximum flexibility of the device and a 30m long working distance for constant wireless communication between the device and a portable device. The morphology and quality of ECG signals acquired from human subjects during different activities demonstrate the device's potential for ambulatory monitoring. Overall, our findings prove the device is flexible, Bluetooth enabled, and can provide conformal contact with skin to achieve ECG monitoring in real-time effortlessly. Future work should include validating the device's functionality with data collection during different activities of the human subject.
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    Characterization of an RF resonator to measure fluid volume for biomedical applications
    (Wichita State University, 2022-12) Arafah, Suhaib Amjad; Cluff, Kim
    Wearable technologies have gained a huge interest in recent years due its advantages in the early diagnosis of medical conditions such as heart attack and monitoring intercranial pressure. Additionally, wearable technologies are an attractive solution in the medical field due to wearable form factor and minimal required training for uses. As such, in this study we are investigating a wearable RF skin patch resonator for the measurement of fluid volume changes. Specifically, this study aims to characterize the sensitivity, dynamic range, and repeatability of the sensor response to changes in fluid volume. The wearable skin patch sensor is an open circuit resonator that is energized wirelessly via an external antenna placed within closed proximity. Once the resonator is energized via the external antenna, it develops its own electromagnetic field and measure the changes in fluid volume nearby. For this study, we used a vector network analyzer for the purpose of energizing the wearable sensor and collecting the $S_{11}$ return loss. From the VNA, we measure the resonance frequency shift in terms of frequency in MHz and amplitude in dB. In this study, the characterizations of the skin patch sensitivity and dynamic range were performed by dynamically increasing the fluid $(H_{2}0)$ volume inside a chamber and collecting the sensor response. The result of this study illustrates that the larger square planner resonators has higher dynamic range than the others sensor designs such as triangle, circle, and pentagon while measuring fluid volume changes up to 540 mL. Furthermore, the sensitivity of large square skin patch resonator was greater than 0.75 mL. In this study, we are able to characterize the sensitivity and dynamic range of the wearable skin patch sensor which will lead into future advancement and development.
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    Inkjet printing techniques for wearable/stretchable electronics in healthcare
    (Wichita State University, 2022-12) Al Wahid, Ali Mohammed; Lee, Yongkuk
    Inkjet printing techniques, a good alternative of the traditional MEMS techniques, can be utilized to fabricate flexible and stretchable electronics, which can be used for healthcare applications. Therefore, the objectives of this study are 1) Providing proof of concept for the inkjet printing parameters for silver (Ag) and polyimide (PI) inks, 2) understanding the relationship between the dynamics of inkjet-printed patterns and surface energies of the substrate, and 3) demonstrating printing a flexible circuit on a PI coated substrate. During experiments, the effects of the printing parameters including jetting voltages, cartridge temperatures, and drop spacings of both the Ag and PI inks via the drop size and line width measurements were explored. The surface energies were manipulated by applying $O_2$ and $CF_4$ plasma for different durations using Reactive Ion Etching (RIE) that were measured by the means of contact angle measurements and ink drop size and line width measurements. Our results indicated that 1) the drop sizes increase as jetting voltages and cartridge temperatures increase, respectively, 2) the line widths decrease with increasing drop spacings, and 3) the $CF_4$ plasma increases the hydrophobicity of the surface while $O_2$ increases the hydrophilicity of the surface. Collectively, we successfully demonstrated accurate printing of multi-layered ECG circuit with a drop size of 40 $\mu{m}$ for the Ag ink and PI ink. The next goal will be to demonstrate wireless continuous monitoring of reliable ECG signals using the printed ECG circuit.
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    Design and analysis of a soft robotic glove for rehabilitation therapy
    (Wichita State University, 2022-07) Rieger, Claire Monet; Desai, Jaydip M.
    Strokes often lead to hemiparesis of the hand. This renders individuals unable to actively flex or extend the affected hand’s fingers. Currently the only option for improvement is therapy to improve the neuromuscular connection and maintain ROM (Range of Motion). Conventional therapy is costly and time consuming. It involves in person visits and at home exercises. Soft robotics has a significant potential in rehabilitative and assistive exoskeletons. The flexible materials deliver a gentle, accessible therapy, minimizing possible injury and increasing the possibility of recovery. This research aimed to design and evaluate an optimized pneumatically actuated soft robotic glove for rehabilitative tasks which will execute the motion of the hand. While there are existing soft robotic gloves, this unique design will allow users to self-actuate their therapy through re-extending the hand using a layer of flexible steel. The resistive layer causes the fingers to return to a straightened position after the pneumatic actuator has released the air pressure which causes it to curl. This design underwent prototyping, evaluation, and human subject testing. This glove, tested by 10 unimpaired subjects, assisted in extension while minimally impairing the glove’s flexion performance. The actuations consistently achieved an average peak of 75° or greater during passive assisted motion. An addition of the steel layer lowered the blocked tip force by an average of 18.13% for all five fingers. The maximum blocked tip force with the steel ranged from 12.7-14.1 N. During passive assisted testing, participants accomplished 80.75% of their normal active flexion ROM when neglecting outliers with the steel lined glove. This data shows strong evidence that this glove would be appropriate to advance to human subject testing on those who do have post stroke hand impairments.