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- Creators: Harrington Bioengineering Program
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Description
The global population over the age of 60 is estimated to rise to 23% by 2050 only increase the prevalence of functional neurological disorders and stroke. Increase in cases of functional neurological disorders and strokes will place a greater burden on the healthcare industry, specifically physical therapy. Physical therapy is vital for a patient’s recovery of motor function which is time demanding and taxing on the physical therapist. Wearable robotics have been proven to improve functional outcomes in gait rehabilitation by providing controlled high dosage and high-intensity training. Accurate control strategies for assistive robotic exoskeletons are vital for repetitive high precisions assistance for cerebral plasticity to occur.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
ContributorsGaytan-Jenkins, Daniel Rinaldo (Author) / Zhang, Wenlong (Thesis director) / Tyler, Jamie (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The effect of conflicting sensorimotor memories on optimal force strategies was explored. Subjects operated a virtual object controlled by a physical handle to complete a simple straight-line task. Perturbations applied to the handle induced a period of increased error in subject accuracy. After two blocks of 33 trials, perturbations switched direction, inducing increased error from the previous trials. Subjects returned after a 24-hour period to complete a similar protocol, but beginning with the second context and ending with the first. Interference from the first context on each day caused an increase in initial error for the second (P < 0.05). Following the rest period, subjects showed retention of the sensorimotor memory from the previous day through significantly decreased initial error (P = 3x10-6). However, subjects showed an increase in forces for each new context resulting from a sub-optimal motor strategy. Higher levels of total effort (P < 0.05) and a lack of separation between force values for opposing and non-opposing digits (P > 0.05) indicated a strategy that used more energy to complete the task, even when rates of learning appeared identical or improved. Two possible mechanisms for this lack of energy conservation have been proposed.
ContributorsSmith, Michael David (Author) / Santello, Marco (Thesis director) / Kleim, Jeffrey (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Medial compartment knee osteoarthritis (OA) is a disease whose severity has been associated with the peak adduction moment during walking (pKAM). Unfortunately, measuring patients' pKAM to track their therapy progress involves the use of a gait laboratory which is expensive and time intensive. This study aimed to develop and assess a regression method to predict the pKAM using only plantar pressure measurements. This approach could greatly reduce the burden of evaluating pKAM.
ContributorsThomas, Kevin Andrew (Author) / Hinrichs, Richard (Thesis director) / Harper, Erin (Committee member) / Favre, Julien (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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
Description
Over the past 30 years the use of graphene has been increasing at a rapid rate. The reason why graphene has become more popular is because it is starting to be understood better, and researchers are starting to recognize graphene’s unique properties. Graphene is a single atomic layer of graphite, and graphite is a three-dimensional cube base structure of carbon. Graphite has a high conductivity rate, and graphene has an even higher conductivity, meaning that graphene makes for an excellent resistor in any hardware system. Graphene is flexible, has high durability, and can vary in resistance based on its shape (Sharon 2015). With graphene being able to change its resistivity, it can act as different types of sensors. These sensors include measuring pressure, resistance, force, strain, and angle. One problem across the globe is that patients have arthritis, decaying bone density, and injuries which can easily go mistreated or not treated at all. It can be hard to determine the severity of injuries in joints by observation of the patient. There are tools and equipment that will allow a doctor to track the force and degrees of motion of certain joints, but they are mostly limited to hospitals. With graphene acting as a sensor it can be embedded into casts, braces, and even clothing. With a mobile sensor that relays accurate and continuous data to a doctor they can more precisely determine a therapy or recovery time that will better suit the patients’ needs. In this project the graphene was used to measure the angle of a patient’s wrist while they were wearing a wrist brace. From the data collected, the graphene was able to track the user’s movement of their wrist as they moved it in a single direction. The data showed the angle of the wrist ranging from zero degrees to 90 degrees. This proves that graphene can shape the way biosensing is accomplished. Biodynamics is a growing field, and with more injuries everyday it is important to study graphene and how it can be used to diagnose and prevent injuries related to joints. Graphene can be used as a biosensor which can then be implemented into a brace to allow for accurate biodynamic tracking.
ContributorsSweeten, William (Author) / Lockhart, Thurmon (Thesis director) / Helms Tillery, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05