Theses and Dissertations
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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- All Subjects: Exoskeleton
Description
There has been a decrease in the fertility rate over the years due to today’s younger generation facing more pressure in the workplace and their personal lives. With an aging population, more and more older people with limited mobility will require nursing care for their daily activities. There are several applications for wearable sensor networks presented in this paper. The study will also present a motion capture system using inertial measurement units (IMUs) and a pressure-sensing insole with a control system for gait assistance using wearable sensors. This presentation will provide details on the implementation and calibration of the pressure-sensitive insole, the IMU-based motion capture system, as well as the hip exoskeleton robot. Furthermore, the estimation of the Ground Reaction Force (GRF) from the insole design and implementation of the motion tracking using quaternion will be discussed in this document.
ContributorsLi, Xunguang (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Subramanian, Susheelkumar (Committee member) / Arizona State University (Publisher)
Created2022
Description
The human shoulder plays an integral role in upper limb motor function. As the basis of arm motion, its performance is vital to the accomplishment of daily tasks. Impaired motor control, as a result of stroke or other disease, can cause errors in shoulder position to accumulate and propagate to the entire arm. This is why it is a highlight of concern for clinicians and why it is an important point of study. One of the primary causes of impaired shoulder motor control is abnormal mechanical joint impedance, which can be modeled as a 2nd order system consisting of mass, spring and damper. Quantifying shoulder stiffness and damping between healthy and impaired subjects could help improve our collective understanding of how many different neuromuscular diseases impact arm performance. This improved understanding could even lead to better rehabilitation protocols for conditions such as stroke through better identification and targeting of damping dependent spasticity and stiffness dependent hypertonicity. Despite its importance, there is a fundamental knowledge gap in the understanding of shoulder impedance, mainly due to a lack of appropriate characterization tools. Therefore, in order to better quantify shoulder stiffness and damping, a novel low-inertia shoulder exoskeleton is introduced in this work. The device was developed using a newly pioneered parallel actuated robot architecture specifically designed to interface with complex biological joints like the shoulder, hip, wrist and ankle. In addition to presenting the kinematics and dynamics of the shoulder exoskeleton, a series of validation experiments are performed on a human shoulder mock-up to quantify its ability to estimate known impedance properties. Finally, some preliminary data from human experiments is provided to demonstrate the device’s ability to collect the measurements needed to estimate shoulder stiffness and damping while worn by a subject.
ContributorsHunt, Justin (Author) / Lee, Hyunglae (Thesis advisor) / Artemiadis, Panagiotis (Committee member) / Sugar, Thomas (Committee member) / Yong, Sze Zheng (Committee member) / Marvi, Hamid (Committee member) / Arizona State University (Publisher)
Created2020
Description
This research seeks to present the design and testing of exoskeletons capable of assisting with walking gait, squatting, and fall prevention activities. The dissertation introduces wearable
robotics and exoskeletons and then progresses into specific applications and developments in the
targeted field. Following the introduction, chapters present and discuss different wearable
exoskeletons built to address known issues with workers and individuals with increased risk of fall.
The presentation is concluded by an overall analysis of the resulting developments and identifying
future work in the field.
ContributorsOlson, Jason Stewart (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2021
Description
Robotic assisted devices in gait rehabilitation have not seen penetration into clinical settings proportionate to the developments in this field. A possible reason for this is due to the development and evaluation of these devices from a predominantly engineering perspective. One way to mitigate this effect is to further include the principles of neurophysiology into the development of these systems. To further include these principles, this research proposes a method for grounded evaluation of three machine learning algorithms to gain insight on what modeling approaches are able to both replicate therapist assistance and emulate therapist strategies. The algorithms evaluated in this paper include ordinary least squares regression (OLS), gaussian process regression (GPR) and inverse reinforcement learning (IRL). The results show that grounded evaluation is able to provide evidence to support the algorithms at a higher resolution. Also, it was observed that GPR is likely the most accurate algorithm to replicate therapist assistance and to emulate therapist adaptation strategies.
ContributorsSmith, Mason Owen (Author) / Zhang, Wenlong (Thesis advisor) / Ben Amor, Hani (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2021
Description
The mean age of the world’s population is rapidly increasing and with that growth in an aging population a large number of elderly people are in need of walking assistance. In addition, a number of medical conditions contribute to gait disorders that require gait rehabilitation. Wearable robotics can be used to improve functional outcomes in the gait rehabilitation process. The ankle push-off phase of an individual’s gait is vital to their ability to walk and propel themselves forward. During the ankle push-off phase of walking, plantar flexors are required to providing a large amount of force to power the heel off the ground.
The purpose of this project is to improve upon the passive ankle foot orthosis originally designed in the ASU’s Robotics and Intelligent Systems Laboratory (RISE Lab). This device utilizes springs positioned parallel to the user’s Achilles tendon which store energy to be released during the push off phase of the user’s gait cycle. Goals of the project are to improve the speed and reliability of the ratchet and pawl mechanism, design the device to fit a wider range of shoe sizes, and reduce the overall mass and size of the device. The resulting system is semi-passive and only utilizes a single solenoid to unlock the ratcheting mechanism when the spring’s potential force is required. The device created also utilizes constant force springs rather than traditional linear springs which allows for a more predictable level of force. A healthy user tested the device on a treadmill and surface electromyography (sEMG) sensors were placed on the user’s plantar flexor muscles to monitor potential reductions in muscular activity resulting from the assistance provided by the AFO device. The data demonstrates the robotic shoe was able to assist during the heel-off stage and reduced activation in the plantar flexor muscles was evident from the EMG data collected. As this is an ongoing research project, this thesis will also recommend possible design upgrades and changes to be made to the device in the future. These upgrades include utilizing a carbon fiber or lightweight plastic frame such as many of the traditional ankle foot-orthosis sold today and introducing a system to regulate the amount of spring force applied as a function of the force required at specific times of the heel off gait phase.
The purpose of this project is to improve upon the passive ankle foot orthosis originally designed in the ASU’s Robotics and Intelligent Systems Laboratory (RISE Lab). This device utilizes springs positioned parallel to the user’s Achilles tendon which store energy to be released during the push off phase of the user’s gait cycle. Goals of the project are to improve the speed and reliability of the ratchet and pawl mechanism, design the device to fit a wider range of shoe sizes, and reduce the overall mass and size of the device. The resulting system is semi-passive and only utilizes a single solenoid to unlock the ratcheting mechanism when the spring’s potential force is required. The device created also utilizes constant force springs rather than traditional linear springs which allows for a more predictable level of force. A healthy user tested the device on a treadmill and surface electromyography (sEMG) sensors were placed on the user’s plantar flexor muscles to monitor potential reductions in muscular activity resulting from the assistance provided by the AFO device. The data demonstrates the robotic shoe was able to assist during the heel-off stage and reduced activation in the plantar flexor muscles was evident from the EMG data collected. As this is an ongoing research project, this thesis will also recommend possible design upgrades and changes to be made to the device in the future. These upgrades include utilizing a carbon fiber or lightweight plastic frame such as many of the traditional ankle foot-orthosis sold today and introducing a system to regulate the amount of spring force applied as a function of the force required at specific times of the heel off gait phase.
ContributorsSchaller, Marcus Frank (Author) / Zhang, Wenlong (Thesis director) / Sugar, Thomas (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12