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- All Subjects: Control
- All Subjects: Wearable Robotics
- Creators: Lee, Hyunglae
Description
Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity.
This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU.
This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.
This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU.
This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.
ContributorsChinimilli, Prudhvi Tej (Author) / Redkar, Sangram (Thesis advisor) / Zhang, Wenlong (Thesis advisor) / Sugar, Thomas G. (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2018
Description
Walking ability is a complex process that is essential to humans, critical for performing a range of everyday tasks and enables a healthy, independent lifestyle. Human gait has evolved to be robust, adapting to a wide range of external stimuli, including variable walking surface compliance. Unfortunately, many people suffer from impaired gait as a result of conditions such as stroke. For these individuals, recovering their gait is a priority and a challenge. The ASU Variable Stiffness Treadmill (VST) is a device that is able to the change its surface compliance through its unique variable stiffness mechanism. By doing this, the VST can be used to investigate gait and has potential as a rehabilitation tool. The objective of this research is to design a variable damping mechanism for the VST, which addresses the need to control effective surface damping, the only form of mechanical impedance that the VST does not currently control. Thus, this project will contribute toward the development of the Variable Impedance Treadmill (VIT), which will encompass a wider range of variable surface compliance and enable all forms of impedance to be con- trolled for the first time. To achieve this, the final design of the mechanism will employ eddy current damping using several permanent magnets mounted to the treadmill and a large copper plate stationed on the ground. Variable damping is obtained by using lead screw mechanisms to remove magnets from acting on the copper plate, which effectively eliminates their effect on damping and changes the overall treadmill surface damping. Results from experimentation validate the mechanism's ability to provide variable damping to the VST. A model for effective surface damping is generated based on open-loop characterization experiments and is generalized for future experimental setups. Overall, this project progresses to the development of the VIT and has potential applications in walking surface simulation, gait investigation, and robot-assisted rehabilitation technology.
ContributorsFou, Linda Guo (Author) / Artemiadis, Panagiotis (Thesis director) / Lee, Hyunglae (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Human walking has been a highly studied topic in research communities because of its extreme importance to human functionality and mobility. A complex system of interconnected gait mechanisms in humans is responsible for generating robust and consistent walking motion over unpredictable ground and through challenging obstacles. One interesting aspect of human gait is the ability to adjust in order to accommodate varying surface grades. Typical approaches to investigating this gait function focus on incline and decline surface angles, but most experiments fail to address the effects of surface grades that cause ankle inversion and eversion. There have been several studies of ankle angle perturbation over wider ranges of grade orientations in static conditions; however, these studies do not account for effects during the gait cycle. Furthermore, contemporary studies on this topic neglect critical sources of unnatural stimulus in the design of investigative technology. It is hypothesized that the investigation of ankle angle perturbations in the frontal plane, particularly in the context of inter-leg coordination mechanisms, results in a more complete characterization of the effects of surface grade on human gait mechanisms. This greater understanding could potentially lead to significant applications in gait rehabilitation, especially for individuals who suffer from impairment as a result of stroke. A wearable pneumatic device was designed to impose inversion and eversion perturbations on the ankle through simulated surface grade changes. This prototype device was fabricated, characterized, and tested in order to assess its effectiveness. After testing and characterizing this device, it was used in a series of experiments on human subjects while data was gathered on muscular activation and gait kinematics. The results of the characterization show success in imposing inversion and eversion angle perturbations of approximately 9° with a response time of 0.5 s. Preliminary experiments focusing on inter-leg coordination with healthy human subjects show that one-sided inversion and eversion perturbations have virtually no effect on gait kinematics. However, changes in muscular activation from one-sided perturbations show statistical significance in key lower limb muscles. Thus, the prototype device demonstrates novelty in the context of human gait research for potential applications in rehabilitation.
ContributorsBarkan, Andrew (Author) / Artemiadis, Panagiotis (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2016
Description
August Krogh, a 20th century Nobel Prize winner in Physiology and Medicine, once stated, "for such a large number of problems there will be some animal of choice, or a few such animals, on which it can be most conveniently studied." What developed to be known as the Krogh Principle, has become the cornerstone of bioinspired robotics. This is the realization that solutions to various multifaceted engineering problems lie in nature. With the integration of biology, physics and engineering, the classical approach in solving engineering problems has transformed. Through such an integration, the presented research will address the following engineering solution: maneuverability on and through complex granular and aquatic environments. The basilisk lizard and the octopus are the key sources of inspiration for the anticipated solution. The basilisk lizard is a highly agile reptile with the ability to easily traverse on vast, alternating, unstructured, and complex terrains (i.e. sand, mud, water). This makes them a great medium for pursuing potential solutions for robotic locomotion on such terrains. The octopus, with a nearly soft, yet muscular hydrostat body and arms, is proficient in locomotion and its complex motor functions are vast. Their versatility, "infinite" degrees of freedom, and dexterity have made them an ideal candidate for inspiration in the fields such as soft robotics. Through conducting animal experiments on the basilisk lizard and octopus, insight can be obtained on the question: how does the animal interact with complex granular and aquatic environments so effectively? Following it through by conducting systematic robotic experiments, the capabilities and limitations of the animal can be understood. Integrating the hierarchical concepts observed and learnt through animal and robotic experiments, it can be used towards designing, modeling, and developing robotic systems that will assist humanity and society on a diversified set of applications: home service, health care, public safety, transportation, logistics, structural examinations, aquatic and extraterrestrial exploration, search-and-rescue, environmental monitoring, forestry, and agriculture, just to name a few. By learning and being inspired by nature, there exist the potential to go beyond nature for the greater good of society and humanity.
ContributorsBagheri, Hosain (Author) / Marvi, Hamidreza (Thesis advisor) / Berman, Spring M (Committee member) / DeNardo, Dale F (Committee member) / Emady, Heather N (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2020
Description
This work presents the design, modeling, analysis, and experimental characterization and testing of soft wearable robotics for lower limb rehabilitation for the ankle and hip. The Soft Robotic Ankle-Foot Orthosis (SR-AFO) is a wearable soft robot designed using multiple pneumatically-powered soft actuators to assist the ankle in multiple degrees-of-freedom during standing and walking tasks. The flat fabric pneumatic artificial muscle (ff-PAM) contracts upon pressurization and assists ankle plantarflexion in the sagittal plane. The Multi-material Actuator for Variable Stiffness (MAVS) aids in supporting ankle inversion/eversion in the frontal plane. Analytical models of the ff-PAM and MAVS were created to understand how the changing of the design parameters affects tensile force generation and stiffness support, respectively. The models were validated by both finite element analysis and experimental characterization using a universal testing machine. A set of human experiments were performed with healthy participants: 1) to measure lateral ankle support during quiet standing, 2) to determine lateral ankle support during walking over compliant surfaces, and 3) to evaluate plantarflexion assistance at push-off during treadmill walking, and 4) determine if the SR-AFO could be used for gait entrainment. Group results revealed increased ankle stiffness during quiet standing with the MAVS active, reduced ankle deflection while walking over compliant surfaces with the MAVS active, and reduced muscle effort from the SOL and GAS during 40 - 60% of the gait cycle with the dual ff-PAM active. The SR-AFO shows promising results in providing lateral ankle support and plantarflexion assistance with healthy participants, and a drastically increased basin of entrainment, which suggests a capability to help restore the gait of impaired users in future trials. The ff-PAM actuators were used in an X-orientation to assist the hip in flexion and extension. The Soft Robotic Hip Exosuit (SR-HExo) was evaluated using the same set of actuators and trials with healthy participants showed reduction in muscle effort during hip flexion and extension to further enhance the study of soft fabric actuators on human gait assistance.
ContributorsThalman, Carly Megan (Author) / Lee, Hyunglae (Thesis advisor) / Artemiadis, Panagiotis (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
In the development of autonomous ground vehicles (AGVs), how to guarantee vehicle lateral stability is one of the most critical aspects. Based on nonlinear vehicle lateral and tire dynamics, new driving requirements of AGVs demand further studies and analyses of vehicle lateral stability control strategies. To achieve comprehensive analyses and stability-guaranteed vehicle lateral driving control, this dissertation presents three main contributions.First, a new method is proposed to estimate and analyze vehicle lateral driving stability regions, which provide a direct and intuitive demonstration for stability control of AGVs. Based on a four-wheel vehicle model and a nonlinear 2D analytical LuGre tire model, a local linearization method is applied to estimate vehicle lateral driving stability regions by analyzing vehicle local stability at each operation point on a phase plane. The obtained stability regions are conservative because both vehicle and tire stability are simultaneously considered. Such a conservative feature is specifically important for characterizing the stability properties of AGVs.
Second, to analyze vehicle stability, two novel features of the estimated vehicle lateral driving stability regions are studied. First, a shifting vector is formulated to explicitly describe the shifting feature of the lateral stability regions with respect to the vehicle steering angles. Second, dynamic margins of the stability regions are formulated and applied to avoid the penetration of vehicle state trajectory with respect to the region boundaries. With these two features, the shiftable stability regions are feasible for real-time stability analysis.
Third, to keep the vehicle states (lateral velocity and yaw rate) always stay in the shiftable stability regions, different control methods are developed and evaluated. Based on different vehicle control configurations, two dynamic sliding mode controllers (SMC) are designed. To better control vehicle stability without suffering chattering issues in SMC, a non-overshooting model predictive control is proposed and applied. To further save computational burden for real-time implementation, time-varying control-dependent invariant sets and time-varying control-dependent barrier functions are proposed and adopted in a stability-guaranteed vehicle control problem.
Finally, to validate the correctness and effectiveness of the proposed theories, definitions, and control methods, illustrative simulations and experimental results are presented and discussed.
ContributorsHuang, Yiwen (Author) / Chen, Yan (Thesis advisor) / Lee, Hyunglae (Committee member) / Ren, Yi (Committee member) / Yong, Sze Zheng (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
This paper presents a variable damping controller that can be implemented into wearable and exoskeleton robots. The variable damping controller functions by providing different levels of robotic damping from negative to positive to the coupled human-robot system. The wearable ankle robot was used to test this control strategy in the different directions of motion. The range of damping applied was selected based on the known inherent damping of the human ankle, ensuring that the coupled system became positively damped, and therefore stable. Human experiments were performed to understand and quantify the effects of the variable damping controller on the human user. Within the study, the human subjects performed a target reaching exercise while the ankle robot provided the system with constant positive, constant negative, or variable damping. These three damping conditions could then be compared to analyze the performance of the system. The following performance measures were selected: maximum speed to quantify agility, maximum overshoot to quantify stability, and muscle activation to quantify effort required by the human user. Maximum speed was found to be statistically the same in the variable damping controller and the negative damping condition and to be increased from positive damping controller to variable damping condition by 57.9%, demonstrating the agility of the system. Maximum overshoot was found to significantly decrease overshoot from the negative damping condition to the variable damping controller by 39.6%, demonstrating an improvement in system stability with the variable damping controller. Muscle activation results showed that the variable damping controller required less effort than the positive damping condition, evidenced by the decreased muscle activation of 23.8%. Overall, the study demonstrated that a variable damping controller can balance the trade-off between agility and stability in human-robot interactions and therefore has many practical implications.
ContributorsArnold, James Michael (Author) / Lee, Hyunglae (Thesis director) / Yong, Sze Zheng (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School for Engineering of Matter,Transport & Enrgy (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
Advancements in the field of design and control of lower extremity robotics requires a comprehensive understanding of the underlying mechanics of the human ankle. The ankle joint acts as an essential interface between the neuromuscular system of the body and the physical world, especially during locomotion. This paper investigates how the modulation of ankle stiffness is altered throughout the stance phase of the gait cycle depending on the environment the ankle is interacting with. Ten young healthy subjects with no neurological impairments or history of ankle injury were tested by walking over a robotic platform which collected torque and position data. The platform performed a perturbation on the ankle at 20%, 40%, and 60% of their stance phase in order to estimate ankle stiffness and evaluate if the environment plays a role on its modulation. The platform provided either a rigid environment or a compliant environment in which it was compliant and deflected according to the torque applied to the platform. Subjects adapted in different ways to achieve balance in the different environments. When comparing the environments, subjects modulated their stiffness to either increase, decrease, or remain the same. Notably, stiffness as well as the subjects’ center of pressure was found to increase with time as they transitioned from late loading to terminal stance (heel strike to toe-off) regardless of environmental conditions. This allowed for a model of ankle stiffness to be developed as a function of center of pressure, independent of whether a subject is walking on the rigid or compliant environment. The modulation of stiffness parameters characterized in this study can be used in the design and control of lower extremity robotics which focus on accurate biomimicry of the healthy human ankle. The stiffness characteristics can also be used to help identify particular ankle impairments and to design proper treatment for individuals such as those who have suffered from a stroke or MS. Changing environments is where a majority of tripping incidents occur, which can lead to significant injuries. For this reason, studying healthy ankle behavior in a variety of environments is of particular interest.
ContributorsBliss, Clayton F (Author) / Lee, Hyunglae (Thesis director) / Marvi, Hamid (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05