Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

Flexible Sensors and Smart Patches for Multimodal Sensing

Rohit, Akanksha
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou162887329354353

Abstract Details

2021, Doctor of Philosophy (PhD), Ohio University, Electrical Engineering & Computer Science (Engineering and Technology).
Emerging wearable technologies are creating a major impact in the area of health monitoring, aerospace, prosthetics and robotics to monitor crucial information in real time which could not be achieved using conventional electronics only. The demand for multifunctional wearable systems is set to grow exponentially in the next decade and low cost multimodal sensor patches that can be closely coupled to the skin define the success of this new era of digital health and robotics. Accordingly, this dissertation focuses on developing a wireless multi-modal sensor patch that can be directly placed on the skin or integrated into clothing to monitor multiple biophysical and structural signals simultaneously. Serving both as a multimodal sensor as well as a compact integration platform for smart textile development, the proposed patch is ideally suited for complex body performance monitoring, realistic worker training and for high-risk patients. The foundation of this research is based on parallel plate capacitive sensors with elastomeric dielectrics (Ecoflex/PDMS) and conductive textile electrodes. The patches are highly stretchable (100%) with a gauge factor of 0.64 with pure silicone (Ecoflex) as the dielectric layer. The gauge factor of the capacitive strain sensor is enhanced two-fold with the inclusion of high-k (or relative dielectric constant) barium titanate (BTO) nanoparticles dispersed in the silicone dielectric layer without sacrificing its linearity and durability easily exceeding 2000 cycles. To further improve the capacitive performance and capabilities for multi-modal sensing, the elastomer dielectric layer is modified with highly flexible polyurethane (PU) foam. With a foam-based dielectric, the change in capacitance is not only due to the change in the thickness of the dielectric but also due to the change in the permittivity of the micropores due its porous structure. In addition to bending and stretching, the foam-based dielectric had a high-pressure sensitivity (0.0198 kPa-1) in the range of 0-4.5 kPa making it capable to monitor phonation, pulsatile flow and respiration. The piezoelectric properties of films, including the nanoparticles of barium titanate (BTO), lead zirconate titanate (PZT) and polyvinylidene fluoride-trifluoroethylene (PVDF-TrFE) was systematically studied at different weight ratios by bending and motor vibrational tests. On corona poling the nanocomposite films at high field (6 kV/cm), the voltage output of all the piezoelectric sensors increased by two-fold. Therefore, with a few modifications in the dielectric layer, the patches are sufficiently sensitive to detect multiple stimuli such as strain, pressure, temperature, bending, vibration, and acoustic feedback. Due to limitations with high poling voltages that can cause arcing, triboelectric sensing was also explored in this work. While charge generation in piezoelectric materials is due to deformation and shift of ions in the crystal structure, triboelectricity is the charge generated due to friction between the two materials. Amongst all the material studied, polyurethane foam was used as the positive frictional layer and PDMS mixed with expandable microspheres was used as the negative frictional layer. The high sensitivity of the triboelectric sensors were capable of sensing small movements such as blinking and chewing, breathing rate and pulsatile flow which could not be detected with the piezoelectric sensors. Three different designs of multimodal patches were developed by combining the different dielectrics into a single patch. The patch is designed with a focus towards multi-purpose usage, both as a sensor in itself to capture motion as well as an integration platform for additional compact sensors that can be modified depending on the target application and measurement parameters. Deployed in appropriate locations and geometries, the patches can capture critical information on the type, intensity and duration between episodic movements and environmental factors, as demonstrated via a shoe-insert and respiratory health monitors. The information from these hybrid multimodal patches can be combined with machine learning/artificial intelligence algorithms for potential applications in the future to detect complex activities or early onset of symptoms by monitoring overall physiological health.
Savas Kaya (Advisor)
Wojciech Jadwisienczak (Committee Member)
Karanth Avinash (Committee Member)
Monica Burdick (Committee Member)
David Tees (Committee Member)
Chris Bartone (Committee Member)
220 p.
Electrical Engineering
Wearable Sensing; E-textile; Smart Patches; Multimodal Sensing

Recommended Citations

Citations

  • Rohit, A. (2021). Flexible Sensors and Smart Patches for Multimodal Sensing [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou162887329354353

    APA Style (7th edition)

  • Rohit, Akanksha. Flexible Sensors and Smart Patches for Multimodal Sensing. 2021. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou162887329354353.

    MLA Style (8th edition)

  • Rohit, Akanksha. "Flexible Sensors and Smart Patches for Multimodal Sensing." Doctoral dissertation, Ohio University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou162887329354353

    Chicago Manual of Style (17th edition)

ohiou162887329354353
528
© 2021, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.