Low-Intensity Blood Flow Restriction Training as a Preoperative Rehabilitative Modality to Improve Postoperative Outcomes for Anterior Cruciate Ligament Reconstruction

171649-Thumbnail Image.png
Description
One of the long-standing issues that has arisen in the sports medicine field is identifying the ideal methodology to optimize recovery following anterior cruciate ligament reconstruction (ACLR). The perioperative period for ACLR is notoriously heterogeneous in nature as it consists…

One of the long-standing issues that has arisen in the sports medicine field is identifying the ideal methodology to optimize recovery following anterior cruciate ligament reconstruction (ACLR). The perioperative period for ACLR is notoriously heterogeneous in nature as it consists of many variables that can impact surgical outcomes. While there has been extensive literature published regarding the efficacy of various recovery and rehabilitation topics, it has been widely acknowledged that certain modalities within the field of ACLR rehabilitation need further high-quality evidence to support their use in clinical practice, such as blood flow restriction (BFR) training. BFR training involves the application of a tourniquet-like cuff to the proximal aspect of a limb prior to exercise; the cuff is inflated so that it occludes venous flow but allows arterial inflow. BFR is usually combined with low-intensity (LI) resistance training, with resistance as low as 20% of one-repetition maximum (1RM). LI-BFR has been used as an emerging clinical modality to combat postoperative atrophy of the quadriceps muscles for those who have undergone ACLR, as these individuals cannot safely tolerate high muscular tension exercise after surgery. Impairments of the quadriceps are the major cause of poor functional status of patients following an otherwise successful ACLR procedure; however, these impairments can be mitigated with preoperative rehabilitation done before surgery. It was hypothesized that the use of a preoperative LI-BFR training protocol could help improve postoperative outcomes following ACLR; primarily, strength and hypertrophy of the quadriceps. When compared with a SHAM control group, subjects who were randomized to a BFR intervention group made greater preoperative strength gains in the quadriceps and recovered quadriceps mass at an earlier timepoint than that of the SHAM group aftersurgery; however, the gains made in strength were not able to be maintained in the 8-week postoperative period. While these results do not support the use of LI-BFR from the short-term perspective after ACLR, follow-up data will be used to investigate trends in re-injury and return to sport rates to evaluate the efficacy of the use of LI-BFR from a long-term perspective.
Date Created
2022
Agent

Vision-Based Control Using Object Detection and Depth Estimation for Robotic Pick and Place Tasks in Construction Applications

171397-Thumbnail Image.png
Description
The construction industry holds great promise for improvement through the use of robotic technologies in its workflow. Although this industry was an early adopter of such technologies, growth in construction robotics research and its integration into current construction projects is…

The construction industry holds great promise for improvement through the use of robotic technologies in its workflow. Although this industry was an early adopter of such technologies, growth in construction robotics research and its integration into current construction projects is progressing slowly. Some significant factors that have contributed to the slow pace are high capital costs, low return on investments, and decreasing public infrastructure budgets. Consequently, there is a clear need to reduce the overall costs associated with new construction robotics technologies, which would enable greater dissemination. One solution is to use a swarm robotics approach, in which a large group of relatively low-cost agents are employed to produce a target collective behavior. Given the development of deep learning algorithms for object detection and depth estimation, and novel technologies such as edge computing and augmented reality, it is becoming feasible to engineer low-cost swarm robotic systems that use a vision-only control approach. Toward this end, this thesis develops a vision-based controller for a mobile manipulator robot that relies only on visual feedback from a monocular camera and does not require prior information about the environment. The controller uses deep-learning based methods for object detection and depth estimation to accomplish material retrieval and deposition tasks. The controller is demonstrated in the Gazebo robot simulator for scenarios in which a mobile manipulator must autonomously identify, pick up, transport, and deposit individual blocks with specific colors and shapes. The thesis concludes with a discussion of possible future extensions to the proposed solution, including its scalability to swarm robotic systems.
Date Created
2022
Agent

The Impact of Variable Pressure on Subject Entrainment to the Soft Robotics Ankle Foot Orthosis

Description

The concept of entrainment broadly applies the locking of phases between 2 independent systems [17]. This physical phenomenon can be applied to modify neuromuscular movement in humans during bipedal locomotion. Gait entrainment to robotic devices have shown great success as…

The concept of entrainment broadly applies the locking of phases between 2 independent systems [17]. This physical phenomenon can be applied to modify neuromuscular movement in humans during bipedal locomotion. Gait entrainment to robotic devices have shown great success as alternatives to labor intensive methods of rehabilitation. By applying additional torque at the ankle joint, previous studies have exhibited consistent gait entrainment to both rigid and soft robotic devices. This entrainment is characterized by consistent phase locking of plantarflexion perturbations to the ‘push off’ event within the gait cycle. However, it is unclear whether such phase locking can be attributed to the plantarflexion assistance from the device or the sensory stimulus of movement at the ankle. To clarify the mechanism of entrainment, an experiment was designed to expose the user to a multitude of varying torques applied at the ankle to assist with plantar flexion. In this experiment, no significant difference in success of subject entrainment occurred when additional torque applied was greater than a detectable level. Force applied at the ankle varied from ~60N to ~130N. This resulted in successful entrainment ~88\% of the time at 98 N, with little to no increase in success as force increased thereafter. Alternatively, success of trials decreased significantly as force was reduced below this level, causing the perturbations to become undetectable by participants. Ultimately this suggests that higher levels of actuator pressure, and thus greater levels of torque applied to the foot, do not increase the likelihood of entrainment during walking. Rather, the results of this study suggest that proper detectable sensory stimulus is the true mechanism for entrainment.

Date Created
2022-12
Agent

Investigations into Human Ankle Stiffness

168588-Thumbnail Image.png
Description
Mechanical impedance is a concept that is used to model biomechanical propertiesof human joints. These models can then be utilized to provide insight into the inner workings of the human neuromuscular system or to provide insight into how to best design controllers…

Mechanical impedance is a concept that is used to model biomechanical propertiesof human joints. These models can then be utilized to provide insight into the inner workings of the human neuromuscular system or to provide insight into how to best design controllers for robotic applications that either attempt to mimic capabilities of the human neuromuscular system or physically interact with it. To further elucidate patterns and properties of how the human neuromuscular system modulates mechanical impedance at the human ankle joint, multiple studies were conducted. The first study was to assess the ability of linear regression models to characterize the change in stiffness - a component of mechanical impedance - seen at the human ankle during the stance phase of walking in the Dorsiflexion-Plantarflexion (DP) direction. A collection of biomechanical variables were used as input variables. The R^2 value of the best performing model was 0.71. The second and third studies were performed to showcase the ability of a newly developed twin dual-axis platform, which goes beyond the limits of a single dual-axis platform, to quantify bilateral stiffness properties. The second study quantified the bilateral mechanical stiffness of the human ankle joint for healthy able-bodied subjects during the stance phase of walking and during quiet standing in both the DP and inversion-eversion directions. Subjects showed a high level of subject specific symmetry. Lastly, a similar bilateral ankle characterization study was conducted on a set of subjects with multiple sclerosis, but only during quiet standing and in the DP direction. Results showed a high level of discrepancy between the subject’s most-affected and least-affected limbs with a larger range and variance than in the healthy population.
Date Created
2022
Agent

Swarm Robotic Consensus Strategies for Multi-Target Tracking And Feature Reconstruction

168583-Thumbnail Image.png
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…

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.
Date Created
2022
Agent

A Soft Robotic Hip Exosuit (SR-HExo) for Assistance and Rehabilitation of Human Locomotion

168484-Thumbnail Image.png
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…

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.
Date Created
2021
Agent

Characterization of Human Postural Balance under Compliance and Deep Learning for Predicting Environmental Conditions during Postural Balance

168324-Thumbnail Image.png
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…

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.
Date Created
2021
Agent

Perturbation-based Training on Compliant Surfaces to Improve Balance in Children with Cerebral Palsy

164786-Thumbnail Image.png
Description

Children with cerebral palsy suffer from balance deficits that may greatly reduce their quality of life. However, recent advancements in robotics allow for balance rehabilitation paradigms that provide greater control of the training environment and more robust measurement techniques. Previous…

Children with cerebral palsy suffer from balance deficits that may greatly reduce their quality of life. However, recent advancements in robotics allow for balance rehabilitation paradigms that provide greater control of the training environment and more robust measurement techniques. Previous works have shown functional balance improvement using standing surface perturbations and compliant surface balancing. Visual feedback during balance training has also been shown to improve postural balance control. However, the combined effect of these interventions has not been evaluated. This paper presents a robot-aided rehabilitation study for two children with cerebral palsy on a side-specific performance-adaptive compliant surface with perturbations. Visual feedback of the participant’s center of pressure and weight distribution were used to evaluate successful balance and trigger perturbations after a period of successful balancing. The platform compliance increased relative to the amount of successful balance during each training interval. Participants trained for 6 weeks including 10, less than 2 hours long, training sessions. Improvements in functional balance as assessed by the Pediatric Balance Scale, the Timed 10 Meter Walk Test, and the 5 Times Sit-to-Stand Test were observed for both participants. There was a reduction in fall risk as evidenced by increased Virtual Time to Contact and an increase in dynamic postural balance supported by a faster Time to Perturb, Time to Stabilize, and Percent Stabilized. A mixed improvement in static postural balance was also observed. This paper highlights the efficacy of robot-aided rehabilitation interventions as a method of balance therapy for children with cerebral palsy.

Date Created
2021-12
Agent

Magnetic Needle Steering and Applications for Less Invasive
Surgery Methodology

164508-Thumbnail Image.png
Description

Medical technology, while improving greatly with time, often requires a sacrifice in the form of invasiveness in order to reach target areas within the body, such as the brain, liver, or heart. This project aims to utilize a magnetic, flexible…

Medical technology, while improving greatly with time, often requires a sacrifice in the form of invasiveness in order to reach target areas within the body, such as the brain, liver, or heart. This project aims to utilize a magnetic, flexible needle design to reach these target areas for surgery and drug administration with minimal invasiveness. The metallic needle tip is guided by an external system consisting of a UR16e robotic arm with a magnetic end effector. As a longer running project, the primary focuses of this research are to develop the system by which the robotic arm guides the needle, investigate and implement fiber Bragg grating sensors as a means of real time path imaging and feedback, and conduct preliminary tests to validate that the needle is accurately controlled by the robotic arm. Testing with different mediums such as gel or phantom tissue, and eventually animal experiments will follow in a future publication due to time constraints.

Date Created
2022-05
Agent

Magnetic Needle Steering for Medical Applications

161936-Thumbnail Image.png
Description
Many medical procedures, like surgeries, deal with the physical manipulation of sensitive internal tissues. Over time, new medical tools and techniques have been developed to improve the safety and efficacy of these procedures. Despite the leaps and bounds of progress…

Many medical procedures, like surgeries, deal with the physical manipulation of sensitive internal tissues. Over time, new medical tools and techniques have been developed to improve the safety and efficacy of these procedures. Despite the leaps and bounds of progress made up to the present day, three major obstacles (among others) persist, bleeding, pain, and the risk of infection. Advances in minimally invasive treatments have transformed many formerly risky surgical procedures into very safe and highly successful routines. Minimally invasive surgeries are characterized by small incision profiles compared to the large incisions in open surgeries, minimizing the aforementioned issues. Minimally invasive procedures lead to several benefits, such as shorter recovery time, fewer complications, and less postoperative pain. In minimally invasive surgery, doctors use various techniques to operate with less damage to the body than open surgery. Today, these procedures have an established, successful history and promising future. Steerable needles are one of the tools proposed for minimally invasive operations. Needle steering is a method for guiding a long, flexible needle through curved paths to reach targets deep in the body, eliminating the need for large incisions. In this dissertation, we present a new needle steering technology: magnetic needle steering. This technology is proposed to address the limitations of conventional needle steering that hindered its clinical applications. Magnetic needle steering eliminates excessive tissue damage, restrictions of the minimum radius of curvature, and the need for a complex nonlinear model, to name a few. It also allows fabricating the needle shaft out of soft and tissue-compliant materials. This is achieved by first developing an electromagnetic coil system capable of producing desired magnetic fields and gradients; then, a magnetically actuated needle is designed, and its effectiveness is experimentally evaluated. Afterward, the scalability of this technique was tested using permanent magnets controlled with a robotic arm. Furthermore, different configurations of permanent magnets and their influence on the magnetic field are investigated, enabling the possibility of designing a desired magnetic field for a specific surgical procedure and operation on a particular organ. Finally, potential future directions towards animal studies and clinical trials are discussed.
Date Created
2021
Agent
Subscribe to Lee, Hyunglae