Supercapacitive Sensors for Force/Strain Measurements in Biomedical Applications
2019-08
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Supercapacitive Sensors for Force/Strain Measurements in Biomedical Applications
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2019-08
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Thesis or Dissertation
Abstract
This dissertation develops a new class of flexible force and strain sensors based on the principle of supercapacitive sensing. The sensing mechanism consists of a change in capacitance in a double-layer supercapacitor in response to an applied force or strain by inducing a change in the contact area between an electrolyte and a pair of electrodes. The new sensors can provide a measurement sensitivity several orders of magnitude higher than traditional capacitive sensors, and have other advantages such as flexibility, soft material construction, ability to operate in liquid environments, tremendous ease of fabrication and unprecedented configurability. As a key component of the new sensors, a paper-based solid-state electrolyte with high deformability is developed. The paper substrate can be easily cut and shaped into complex three-dimensional geometries on which ionic gel can be coated. Paper dissolves in the ionic gel after determining the shape of the electrolyte, leaving behind transparent electrolyte structures with micro-structured fissures responsible for their high deformability. Exploiting this simple paper-based fabrication process, this dissertation develops diverse sensors of different configurations and demonstrates their operation and their advantages. First, force sensors in multiple configurations involving electrolytes that are arch-shaped, corrugated and dome-shaped are fabricated. They have sensitivity that is 1000 times larger than similarly sized capacitive sensors and have negligible parasitic capacitance when used in immersive liquid environments. The use of such force sensors on a urethral catheter which can be used to diagnose the cause of urinary incontinence in a Urology application is demonstrated. A urethral catheter with five distributed force sensors is fabricated that can be used to measure distributed urethral closure pressure in a human subject. Experimental results with the catheter, including cuff tests and ex vivo tests are presented. Next, their high sensitivity allows the use of multiple supercapacitive sensors together in a quad structure to enable a sensor in which normal and shear forces can be simultaneously measured. Such a sensor can have multiple applications in robotics and in wearable monitoring systems which can benefit from measurement of multi-axis forces. The performance of the multi-axis normal-shear force sensor is evaluated using extensive experimental data with a wide range of force combinations. Due to manufacturing imperfections, the sensor does not have uniform axisymmetric sensitivity. Hence, a learning algorithm which utilizes a deep neural network to model the sensor response to multi-axis forces is developed and implemented. The learning algorithm allows the sensor system to provide highly accurate normal and shear force estimates, no matter what the alignment of the forces applied on the sensor. Finally, the use of the supercapacitive sensors for strain measurement is evaluated. The paper-based electrolyte is strengthened with silicate nanoparticles to allow it to withstand over 110% stretch without failure. The strengthened electrolyte is used in a unique strain sensor design. The strain sensor is shown to have ultra-high sensitivity and its performance in a wearable home-monitoring application to measure the size of the leg and thus monitor leg-swelling is demonstrated. The contributions of this dissertation include the development of a new soft deformable electrolyte, the development of a paper-based supercapacitive sensor system, and the development of novel sensor configurations such as a simultaneous normal-shear force sensor, a distributed urethral catheter with multiple pressure sensors and a highly stretchable strain sensor. The developed class of new sensors provides extremely high sensitivity and other advantages in spite of easy fabrication with no requirement for clean room facilities.
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University of Minnesota Ph.D. dissertation. August 2019. Major: Mechanical Engineering. Advisor: Rajesh Rajamani. 1 computer file (PDF); xvi, 117 pages.
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Zhang, Ye. (2019). Supercapacitive Sensors for Force/Strain Measurements in Biomedical Applications. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/209035.
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