This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Description
With the extensive technological progress made in the areas of drives, sensors and processing, exoskeletons and other wearable devices have become more feasible. However, the stringent requirements in regards to size and weight continue to exert a strong influence on the system-wide design of these devices and present many obstacles

With the extensive technological progress made in the areas of drives, sensors and processing, exoskeletons and other wearable devices have become more feasible. However, the stringent requirements in regards to size and weight continue to exert a strong influence on the system-wide design of these devices and present many obstacles to a successful solution. On the other hand, while the area of controls has seen a significant amount of progress, there also remains a large potential for improvements. This dissertation approaches the design and control of wearable devices from a systems perspective and provides a framework to successfully overcome the often-encountered obstacles with optimal solutions. The electronics, drive and control system design for the HeSA hip exoskeleton project and APEx hip exoskeleton project are presented as examples of how this framework is used to design wearable devices. In the area of control algorithms, a real-time implementation of the Fast Fourier Transform (FFT) is presented as an alternative approach to extracting amplitude and frequency information of a time varying signal. In comparison to the peak search method (PSM), the FFT allows extracting basic gait signal information at a faster rate because time windows can be chosen to be less than the fundamental gait frequency. The FFT is implemented on a 16-bit processor and the results show the real-time detection of amplitude and frequency coefficients at an update rate of 50Hz. Finally, a novel neural networks based approach to detecting human gait activities is presented. Existing neural networks often require vast amounts of data along with significant computer resources. Using Neural Ordinary Differential Equations (Neural ODEs) it is possible to distinguish between seven different daily activities using a significantly smaller data set, lower system resources and a time window of only 0.1 seconds.
ContributorsBoehler, Alexander (Author) / Sugar, Thomas (Thesis advisor) / Redkar, Sangram (Committee member) / Hollander, Kevin (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Wearable assistive devices have been greatly improved thanks to advancements made in soft robotics, even creation soft extra arms for paralyzed patients. Grasping remains an active area of research of soft extra limbs. Soft robotics allow the creation of grippers that due to their inherit compliance making them lightweight, safer

Wearable assistive devices have been greatly improved thanks to advancements made in soft robotics, even creation soft extra arms for paralyzed patients. Grasping remains an active area of research of soft extra limbs. Soft robotics allow the creation of grippers that due to their inherit compliance making them lightweight, safer for human interactions, more robust in unknown environments and simpler to control than their rigid counterparts. A current problem in soft robotics is the lack of seamless integration of soft grippers into wearable devices, which is in part due to the use of elastomeric materials used for the creation of most of these grippers. This work introduces fabric-reinforced textile actuators (FRTA). The selection of materials, design logic of the fabric reinforcement layer and fabrication method are discussed. The relationship between the fabric reinforcement characteristics and the actuator deformation is studied and experimentally verified. The FRTA are made of a combination of a hyper-elastic fabric material with a stiffer fabric reinforcement on top. In this thesis, the design, fabrication, and evaluation of FRTAs are explored. It is shown that by varying the geometry of the reinforcement layer, a variety of motion can be achieve such as axial extension, radial expansion, bending, and twisting along its central axis. Multi-segmented actuators can be created by tailoring different sections of fabric-reinforcements together in order to generate a combination of motions to perform specific tasks. The applicability of this actuators for soft grippers is demonstrated by designing and providing preliminary evaluation of an anthropomorphic soft robotic hand capable of grasping daily living objects of various size and shapes.
ContributorsLopez Arellano, Francisco Javier (Author) / Santello, Marco (Thesis advisor) / Zhang, Wenlong (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2019