Matching Items (4)
Description
This paper introduces a wireless reconfigurable “button-type” pressure sensor system, via machine learning, for gait analysis application. The pressure sensor system consists of an array of independent button-type pressure sensing units interfaced with a remote computer. The pressure sensing unit contains pressure-sensitive resistors, readout electronics, and a wireless Bluetooth module, which are assembled within footprint of 40 × 25 × 6mm3. The small-footprint, low-profile sensors are populated onto a shoe insole, like buttons, to collect temporal pressure data. The pressure sensing unit measures pressures up to 2,000 kPa while maintaining an error under 10%. The reconfigurable pressure sensor array reduces the total power consumption of the system by 50%, allowing extended period of operation, up to 82.5 hrs. A robust machine learning program identifies the optimal pressure sensing units in any given configuration at an accuracy of up to 98%.
ContributorsBooth, Jayden Charles (Author) / Chae, Junseok (Thesis director) / Chen, Ang (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
With more people falling every year it is more important to continue to track everyday activity as well as follow the progress that someone is making over time. As well as at risk subjects, athletes are also wanting to track their activity as well as improve in finer control of their motions and abilities. To improve someone’s balance, strength, flexibility, and more someone can now start to use different biological sensors to help live a healthier and better lifestyle. To build different sensors requires materials that are comfortable to wear and accurate in collecting data. Graphene has been considered a wonder material that is used in many different applications which allow circuits and devices to use the flexible and durable material to conduct electricity. This paper shows multiple different tests and 36 trials of using graphene as a device which measures pressure that can be used to analyze gait patterns. These tests involve walking on a dual force plate treadmill for 90 continuous seconds with the graphene strip in the heel of the shoe wirelessly transmitting data to be recorded. The initial tests show that graphene will pick up noise and that graphene can start to deteriorate without proper protection. When looking at subject 1 there is less than .01 seconds of error between the graphene circuit and the ground truth. The ground truth was collected simultaneously, and the t-tests and ANOVA tests showed that there is no statistical difference between the graphene system and the ground truth. These tests also showed a 96.7% reproducibility score. There are limitations as seen in the later subjects, but these limitations can be overcome by further protecting the graphene and replacing the strip when it starts to show signs of deterioration which will allow graphene to be used in everyday bio wearable devices.
ContributorsSweeten, William (Author) / Lockhart, Thurmon (Thesis advisor) / Arquiza, Jose Apollo (Committee member) / Soangra, Rahul (Committee member) / Arizona State University (Publisher)
Created2022
Description
The human ankle is a critical joint required for mobility and stability of the body during static and dynamic activity. The absence of necessary torque output by the ankle due to neurological disorder or near-fatal injury can severely restrict locomotion and cause an inability to perform daily tasks. Physical Human-Robot Interaction (pHRI) has explored the potential of controlled actuators to positively impact human joints and partly restoring the required torque and stability at the joint to perform a task. However, a trade-off between agility and stability of the control technique of these devices can reduce the complete utilization of the performance to create a desirable impact on human joints. This research focuses on two control techniques of an Active Ankle Foot Orthosis (AFO) namely, Variable Stiffness (VS) and Variable Damping (VD) controllers to modulate ankle during walking. The VS controller is active during the stance phase and is used to restore the ankle trajectory of healthy participants that has been altered by adding a dead-weight of 2 Kgs. The VD controller is active during the terminal stance and early-swing phase and provides augmentative force during push-off that results in increased propulsion and stabilizes the ankle based on user-intuitions. Both controllers have a positive impact on Medial Gastrocnemius (GAS) muscle and Soleus (SOL) muscle which are powerful plantar - flexors critical to propulsion and kinematic properties during walking. The VS controller has recorded an 8.18% decrease in GAS and an 9.63 % decrease in SOL muscle activity during the stance phase amongst participants while decreasing mean ankle position error by 22.28 % and peak ankle position error by 17.43%. The VD controller demonstrated a 7.59 % decrease in GAS muscle and a 10.15 % decrease in SOL muscle activity during push-off amongst the participants while increasing the range-of-motion (ROM) by 7.84 %. Comprehensively, the study has shown a positive impact on ankle trajectory and the corresponding muscle effort at respective stages of the controller activity.
ContributorsSave, Omik Milind (Author) / Lee, Hyunglae (Thesis advisor) / Marvi, Hamidreza (Committee member) / Yong, Sze (Committee member) / Arizona State University (Publisher)
Created2020
Description
Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper gait cycle might be attributed to the lack of force produced at the toe-off stage. This project addresses if it is possible to create an OpenSim model to find the ideal time and force magnitude needed of an assistive force ankle device to improve gait patterns in individuals with NMD.
ContributorsRivera, Jose Luis (Author) / Zhang, Wenlong (Thesis director) / Lockhart, Thurmon (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05