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Millions of individuals suffer from gait impairments due to stroke or other neurological disorders. A primary goal of patients is to walk independently, but most patients only achieve a poor functional outcome five years after injury. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor

Millions of individuals suffer from gait impairments due to stroke or other neurological disorders. A primary goal of patients is to walk independently, but most patients only achieve a poor functional outcome five years after injury. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor function, state-of-the-art robotic interventions in gait therapy have not resulted in improved outcomes when compared to traditional treadmill-based therapy. Because bipedal walking requires neural coupling and dynamic interactions between the legs, a fundamental understanding of the sensorimotor mechanisms of inter-leg coordination during walking is needed to inform robotic interventions in gait therapy. This dissertation presents a systematic exploration of sensorimotor mechanisms of inter-leg coordination by studying the effect of unilateral perturbations of the walking surface stiffness on contralateral muscle activation in healthy populations. An analysis of the contribution of several sensory modalities to the muscle activation of the opposite leg provides new insight into the sensorimotor control mechanisms utilized in human walking, including the role of supra-spinal neural circuits in inter-leg coordination. Based on these insights, a model is created which relates the unilateral deflection of the walking surface to the resulting neuromuscular activation in the opposite leg. Additionally, case studies with hemiplegic walkers indicate the existence of the observed mechanism in neurologically impaired walkers. The results of this dissertation suggest a novel approach to gait therapy for hemiplegic patients in which desired muscle activity is evoked in the impaired leg by only interacting with the healthy leg. One of the most significant advantages of this approach over current rehabilitation protocols is the safety of the patient since there is no direct manipulation of the impaired leg. Therefore, the methods and results presented in this dissertation represent a potential paradigm shift in robot-assisted gait therapy.
ContributorsSkidmore, Jeffrey Alan (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2017
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The advancements in the technology of MEMS fabrication has been phenomenal in recent years. In no mean measure this has been the result of continued demand from the consumer electronics market to make devices smaller and better. MEMS inertial measuring units (IMUs) have found revolutionary applications in a wide array

The advancements in the technology of MEMS fabrication has been phenomenal in recent years. In no mean measure this has been the result of continued demand from the consumer electronics market to make devices smaller and better. MEMS inertial measuring units (IMUs) have found revolutionary applications in a wide array of fields like medical instrumentation, navigation, attitude stabilization and virtual reality. It has to be noted though that for advanced applications of motion tracking, navigation and guidance the cost of the IMUs is still pretty high. This is mainly because the process of calibration and signal processing used to get highly stable results from MEMS IMU is an expensive and time-consuming process. Also to be noted is the inevitability of using external sensors like GPS or camera for aiding the IMU data due to the error propagation in IMU measurements adds to the complexity of the system.

First an efficient technique is proposed to acquire clean and stable data from unaided IMU measurements and then proceed to use that system for tracking human motion. First part of this report details the design and development of the low-cost inertial measuring system ‘yIMU’. This thesis intends to bring together seemingly independent techniques that were highly application specific into one monolithic algorithm that is computationally efficient for generating reliable orientation estimates. Second part, systematically deals with development of a tracking routine for human limb movements. The validity of the system has then been verified.

The central idea is that in most cases the use of expensive MEMS IMUs is not warranted if robust smart algorithms can be deployed to gather data at a fraction of the cost. A low-cost prototype has been developed comparable to tactical grade performance for under $15 hardware. In order to further the practicability of this device we have applied it to human motion tracking with excellent results. The commerciality of device has hence been thoroughly established.
ContributorsShetty, Yatiraj K (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2016
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Oscillatory perturbations with varying amplitudes and frequencies have been found to significantly affect human standing balance. However, previous studies have only applied perturbation in either the anterior-posterior (AP) or the medio-lateral (ML) directions. Little is currently known about the impacts of 2D oscillatory perturbations on postural stability, which are

Oscillatory perturbations with varying amplitudes and frequencies have been found to significantly affect human standing balance. However, previous studies have only applied perturbation in either the anterior-posterior (AP) or the medio-lateral (ML) directions. Little is currently known about the impacts of 2D oscillatory perturbations on postural stability, which are more commonly seen in daily life (i.e., while traveling on trains, ships, etc.). This study investigated the effects of applying 2D perturbations vs 1D perturbations on standing stability, and how increasing the frequency and amplitude of perturbation impacts postural stability. A dual-axis robotic platform was utilized to simulate various oscillatory perturbations and evaluate standing postural stability. Fifteen young healthy subjects were recruited to perform quiet stance on the platform. Impacts of perturbation direction (i.e., 1D versus 2D), amplitude, and frequency on postural stability were investigated by analyzing different stability measures, specifically AP/ML/2D Center-of-Pressure (COP) path length, AP/ML/2D Time-to-Boundary (TtB), and sway area. Standing postural stability was compromised more by 2D perturbations than 1D perturbations, evidenced by a significant increase in COP path length and sway area and decrease in TtB. Further, the stability decreased as 2D perturbation amplitude and frequency increased. A significant increase in COP path length and decrease in TtB were consistently observed as the 2D perturbation amplitude and frequency increased. However, sway area showed a considerable increase only with increasing perturbation amplitude but not with increasing frequency.

ContributorsBerrett, Lauren Ann (Author) / Lee, Hyunglae (Thesis director) / Peterson, Daniel (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant

This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging. The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition. These two studies provide new perspectives in human postural balance, which cannot be interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
ContributorsPhan, Vu Nguyen (Author) / Lee, Hyunglae (Thesis advisor) / Peterson, Daniel (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the

Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the development of robot controllers and system architectures that scale well with the number of robots and that are robust to robot errors and failures. To achieve this, one approach is to design decentralized robot control policies that require only local sensing and local, ad-hoc communication. In particular, stochastic control policies can be designed that are agnostic to individual robot identities and do not require a priori information about the environment or sophisticated computation, sensing, navigation, or communication capabilities. This dissertation presents novel swarm control strategies with these properties for detecting and mapping static targets, which represent features of interest, in an unknown, bounded, obstacle-free environment. The robots move on a finite spatial grid according to the time-homogeneous transition probabilities of a Discrete-Time Discrete-State (DTDS) Markov chain model, and they exchange information with other robots within their communication range using a consensus (agreement) protocol. This dissertation extend theoretical guarantees on multi-robot consensus over fixed and time-varying communication networks with known connectivity properties to consensus over the networks that have Markovian switching dynamics and no presumed connectivity. This dissertation develops such swarm consensus strategies for detecting a single feature in the environment, tracking multiple features, and reconstructing a discrete distribution of features modeled as an occupancy grid map. The proposed consensus approaches are validated in numerical simulations and in 3D physics-based simulations of quadrotors in Gazebo. The scalability of the proposed approaches is examined through extensive numerical simulation studies over different swarm populations and environment sizes.
ContributorsShirsat, Aniket (Author) / Berman, Spring (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Saripalli, Srikanth (Committee member) / Gharavi, Lance (Committee member) / Arizona State University (Publisher)
Created2022
Description

All civilization requires some sort of infrastructure to provide an essential service. Roads, bridges, pipelines, railroads, etc. are all critical in maintaining our society, but when they fail, they pose a serious threat to the economy, public safety, and environment. This is why it has become increasingly important to invest

All civilization requires some sort of infrastructure to provide an essential service. Roads, bridges, pipelines, railroads, etc. are all critical in maintaining our society, but when they fail, they pose a serious threat to the economy, public safety, and environment. This is why it has become increasingly important to invest in and research the field of Structural Health Monitoring (SHM) to ensure the safety and reliability of our infrastructure. This research paper delves into the optimization of a Lizard-inspired Tube Inspection (LTI) robot, with the primary focus on the inspection side of SHM through the use of Electro Magnetic Acoustic Transducer (EMAT), a Non-Destructive Testing (NDT) method. The robot is designed to inspect power plants piping for damage or defects, and its ability to detect issues early, results in improved plant efficiency, enhanced structural data collection, and increased safety. An iterative, reliable design was constructed by reducing the weight and addressing previous design flaws and then tested. Solidworks was used to calculate theoretical weight, applied stress, and displacements for the design modifications.. The overall reduction in weight was around 12.4% of the previous design. While this research successfully reduced the robot's weight and resolved issues in its design, further optimization is still necessary. Future studies should investigate the finger and friction pad design, robot control, and ways to reduce the reliance on commercial off-the-shelf parts. This will expand the robot’s inspection capabilities, making it applicable in other industries where NDT is critical to ensure structural integrity and safety, such as the pipes in oil and gas refineries, water treatment plants, and chemical processing plants, innovating the way infrastructure is monitored and maintained.

ContributorsMorris-Sjolund, Drake (Author) / Marvi, Hamidreza (Thesis director) / Lee, Hyunglae (Committee member) / Barrett, The Honors College (Contributor)
Created2023-05
Description

Falls are known to be a common occurrence and a costly one as well, as they are the second leading cause of unintentional deaths and millions of other injuries worldwide. Falls often occur due to an increase in trunk flexion angle, so this experiment aims to reduce the trunk flexion

Falls are known to be a common occurrence and a costly one as well, as they are the second leading cause of unintentional deaths and millions of other injuries worldwide. Falls often occur due to an increase in trunk flexion angle, so this experiment aims to reduce the trunk flexion received while stepping over an obstacle. To achieve this a soft actuator was attached to the trunk and pressure was sent as subjects walked and stepped over an obstacle presented on a treadmill. The pressure is meant to stiffen the back which should in theory reduce the trunk flexion angle and lower the chances of falling. In this experiment, two groups were tested: three participants from a control group (healthy young adults) and three participants from an experimental group (healthy elderly adults). Since elderly adults have the highest fall risk due to overall lack of stability, they are the experimental group and the focus for this experiment. The results from the study showed that elderly adults had a beneficial effect with the soft actuator as there was a noticeable difference in trunk flexion when the device was attached. The experiment also supported prior research that stated that trunk flexion was greater in elderly adults than younger adults. Despite the positive results, further studies should be done to prove that the soft devices influence lowering trunk flexion angle as well as to see if the device has any noticeable effect on younger adults.

ContributorsFisher, Caleb (Author) / Lee, Hyunglae (Thesis director) / Olivas, Alyssa (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05
ContributorsFisher, Caleb (Author) / Lee, Hyunglae (Thesis director) / Olivas, Alyssa (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05
ContributorsFisher, Caleb (Author) / Lee, Hyunglae (Thesis director) / Olivas, Alyssa (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05
ContributorsFisher, Caleb (Author) / Lee, Hyunglae (Thesis director) / Olivas, Alyssa (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05