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- All Subjects: Biomedical Engineering
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- Creators: Lee, Hyunglae
Description
Locomotion is of prime importance in enabling human beings to effectively respond
in space and time to meet different needs. Approximately 2 million Americans live
with an amputation with most of those amputations being of the lower limbs. To
advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt
performance at a level of intelligence seen in human walking. As such, this thesis
focuses on the mechanisms involved during human walking, while transitioning from
rigid to compliant surfaces such as from pavement to sand, grass or granular media.
Utilizing a unique tool, the Variable Stiffness Treadmill (VST), as the platform for
human walking, rigid to compliant surface transitions are simulated. The analysis of
muscular activation during the transition from rigid to different compliant surfaces
reveals specific anticipatory muscle activation that precedes stepping on a compliant
surface. There is also an indication of varying responses for different surface stiffness
levels. This response is observed across subjects. Results obtained are novel and
useful in establishing a framework for implementing control algorithm parameters to
improve powered ankle prosthesis. With this, it is possible for the prosthesis to adapt
to a new surface and therefore resulting in a more robust smart powered lower limb
prosthesis.
in space and time to meet different needs. Approximately 2 million Americans live
with an amputation with most of those amputations being of the lower limbs. To
advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt
performance at a level of intelligence seen in human walking. As such, this thesis
focuses on the mechanisms involved during human walking, while transitioning from
rigid to compliant surfaces such as from pavement to sand, grass or granular media.
Utilizing a unique tool, the Variable Stiffness Treadmill (VST), as the platform for
human walking, rigid to compliant surface transitions are simulated. The analysis of
muscular activation during the transition from rigid to different compliant surfaces
reveals specific anticipatory muscle activation that precedes stepping on a compliant
surface. There is also an indication of varying responses for different surface stiffness
levels. This response is observed across subjects. Results obtained are novel and
useful in establishing a framework for implementing control algorithm parameters to
improve powered ankle prosthesis. With this, it is possible for the prosthesis to adapt
to a new surface and therefore resulting in a more robust smart powered lower limb
prosthesis.
ContributorsObeng, Ruby Afriyie (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Thesis advisor) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2019
Description
There are a large group of amputees living in the country and the number of them is supposed to increase a lot in the following years. Among them, lower-limb amputees are the majority. In order to improve the locomotion of lower-limb amputees, many prostheses have been developed. Most commercially available prostheses are passive. They can not actively provide pure torque as an intact human could do. Powered prostheses have been the focus during the past decades. Some advanced prostheses have been successful in walking on level ground as well as on inclined surface and climbing stairs. However, not much work has been done regarding walking on compliant surfaces. My preliminary studies on myoelectric signals of the lower limbs during walking showed that there exists difference in muscle activation when walking on compliant surfaces. However, the mapping of muscle activities to joint torques for a prosthesis that will be capable of providing the required control to walk on compliant surfaces is not straightforward. In order to explore the effects of surface compliance on leg joint torque, a dynamic model of the lower limb was built using Simscape. The simulated walker (android) was commanded to track the same kinematics data of intact human walking on solid surface. Multiple simulations were done while varying ground stiffness in order to see how the torque at the leg joints would change as a function of the ground compliance. The results of this study could be used for the control of powered prostheses for robust walking on compliant surfaces.
ContributorsWang, Junxin, 1989- (Author) / Artemiadis, Panagiotis (Thesis advisor) / Yong, Sze Zheng (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2019
Description
For a conventional quadcopter system with 4 planar rotors, flight times vary between 10 to 20 minutes depending on the weight of the quadcopter and the size of the battery used. In order to increase the flight time, either the weight of the quadcopter should be reduced or the battery size should be increased. Another way is to increase the efficiency of the propellers. Previous research shows that ducting a propeller can cause an increase of up to 94 % in the thrust produced by the rotor-duct system. This research focused on developing and testing a quadcopter having a centrally ducted rotor which produces 60 % of the total system thrust and 3 other peripheral rotors. This quadcopter will provide longer flight times while having the same maneuvering flexibility in planar movements.
ContributorsLal, Harsh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Lee, Hyunglae (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
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
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
Fall accident is a significant problem associated with our society both in terms of economic losses and human suffering [1]. In 2016, more than 800,000 people were hospitalized and over 33,000 deaths resulted from falling. Health costs associated with falling in 2016 yielded at 33% of total medical expenses in the US- mounting to approximately $31 billion per year. As such, it is imperative to find intervention strategies to mitigate deaths and injuries associated with fall accidents. In order for this goal to be realized, it is necessary to understand the mechanisms associated with fall accidents and more specifically, the movement profiles that may represent the cogent behavior of the locomotor system that may be amendable to rehabilitation and intervention strategies. In this light, this Thesis is focused on better understanding the factors influencing dynamic stability measure (as measured by Lyapunov exponents) during over-ground ambulation utilizing wireless Inertial Measurement Unit (IMU).
Four pilot studies were conducted: the First study was carried out to verify if IMU system was sophisticated enough to determine different load-carrying conditions. Second, to test the effects of walking inclinations, three incline levels on gait dynamic stability were examined. Third, tested whether different sections from the total gait cycle can be stitched together to assess LDS using the laboratory collected data. Finally, the fourth study examines the effect of “stitching” the data on dynamic stability measure from a longitudinally assessed (3-day continuous data collection) data to assess the effects of free-range data on assessment of dynamic stability.
Results indicated that load carrying significantly influenced dynamic stability measure but not for the floor inclination levels – indicating that future use of such measure should further implicate normalization of dynamic stability measures associated with different activities and terrain conditions. Additionally, stitching method was successful in obtaining dynamic stability measure utilizing free-living IMU data.
Four pilot studies were conducted: the First study was carried out to verify if IMU system was sophisticated enough to determine different load-carrying conditions. Second, to test the effects of walking inclinations, three incline levels on gait dynamic stability were examined. Third, tested whether different sections from the total gait cycle can be stitched together to assess LDS using the laboratory collected data. Finally, the fourth study examines the effect of “stitching” the data on dynamic stability measure from a longitudinally assessed (3-day continuous data collection) data to assess the effects of free-range data on assessment of dynamic stability.
Results indicated that load carrying significantly influenced dynamic stability measure but not for the floor inclination levels – indicating that future use of such measure should further implicate normalization of dynamic stability measures associated with different activities and terrain conditions. Additionally, stitching method was successful in obtaining dynamic stability measure utilizing free-living IMU data.
ContributorsMoon, Seong Hyun (Author) / Lockhart, Thurmon Eddy (Thesis advisor) / Lee, Hyunglae (Committee member) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2017
Description
A robotic swarm can be defined as a large group of inexpensive, interchangeable
robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
ContributorsKaravas, Georgios Konstantinos (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring M. (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2017
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 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
Description
Low back pain (LBP) is the most common symptom leading to hospitalization and medical assistance. In the US, LBP is the fifth most prevalent case for visiting hospitals. Approximately 2.06 million LBP incidents were reported during the timeline between 2004 and 2008. Globally, LBP occurrence increased by almost 200 million from 1990 to 2017. This problem is further implicated by physical and financial constraints that impact the individual’s quality of life. The medical cost exceeded $87.6 billion, and the lifetime prevalence was 84%. This indicates that the majority of people in the US will experience this symptom. Also, LBP limits Activities of Daily Living (ADL) and possibly affects the gait and postural stability. Prior studies indicated that LBP patients have slower gait speed and postural instability. To alleviate this symptom, the epidural injection is prescribed to treat pain and improve mobility function. To evaluate the effectiveness of LBP epidural injection intervention, gait and posture stability was investigated before and after the injection. While these factors are the fundamental indicator of LBP improvement, ADL is an element that needs to be significantly considered. The physical activity level depicts a person’s dynamic movement during the day, it is essential to gather activity level that supports monitoring chronic conditions, such as LBP, osteoporosis, and falls. The objective of this study was to assess the effects of Epidural Steroid Injection (ESI) on LBP and related gait and postural stability in the pre and post-intervention status. As such, the second objective was to assess the influence of ESI on LBP, and how it influences the participant’s ADL physical activity level. The results indicated that post-ESI intervention has significantly improved LBP patient’s gait and posture stability, however, there was insufficient evidence to determine the significant disparity in the physical activity levels. In conclusion, ESI depicts significant positive effects on LBP patients’ gait and postural parameters, however, more verification is required to indicate a significant effect on ADL physical activity levels.
ContributorsMoon, Seong Hyun (Author) / Lockhart, Thurmon (Thesis advisor) / Honeycutt, Claire (Committee member) / Peterson, Daniel (Committee member) / Lee, Hyunglae (Committee member) / Soangra, Rahul (Committee member) / Arizona State University (Publisher)
Created2023
Description
The Soft Robotic Hip Exosuit (SR-HExo) was designed, fabricated, and tested in treadmill walking experiments with healthy participants to gauge effectivity of the suit in assisting locomotion and in expanding the basin of entrainment as a method of rehabilitation. The SR-HExo consists of modular, compliant materials to move freely with a user’s range of motion and is actuated with X-oriented flat fabric pneumatic artificial muscles (X-ff-PAM) that contract when pressurized and can generate 190N of force at 200kPa in a 0.3 sec window. For use in gait assistance experiments, X-ff-PAM actuators were placed anterior and posterior to the right hip joint. Extension assistance and flexion assistance was provided in 10-45% and 50-90% of the gait cycle, respectively. Device effectivity was determined through range of motion (ROM) preservation and hip flexor and extensor muscular activity reduction. While the active suit reduced average hip ROM by 4o from the target 30o, all monitored muscles experienced significant reductions in electrical activity. The gluteus maximus and biceps femoris experienced electrical activity reduction of 13.1% and 6.6% respectively and the iliacus and rectus femoris experienced 10.7% and 27.7% respectively. To test suit rehabilitative potential, the actuators were programmed to apply periodic torque perturbations to induce locomotor entrainment. An X-ff-PAM was contracted at
the subject’s preferred gait frequency and, in randomly ordered increments of 3%, increased up to 15% beyond.
Perturbations located anterior and posterior to the hip were tested separately to assess impact of location on entrainment characteristics. All 11 healthy participants achieved entrainment in all 12 experimental conditions in both
suit orientations. Phase-locking consistently occurred around toe-off phase of the gait cycle (GC). Extension perturbations synchronized earlier in the gait cycle (before 60% GC where peak hip extension occurs) than flexion perturbations (just after 60% GC at the transition from full hip extension to hip flexion), across group averaged results. The study demonstrated the suit can significantly extend the basin of entrainment and improve transient response compared to previously reported results and confirms that a single stable attractor exists during gait entrainment to unidirectional hip perturbations.
ContributorsBaye-Wallace, Lily (Author) / Lee, Hyunglae (Thesis advisor) / Marvi, Hamidreza (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2021