Achieving Practical Functional Electrical Stimulation-driven Reaching Motions In An Individual With Tetraplegia

Functional electrical stimulation (FES) is a promising technique for restoring the ability to complete reaching motions to individuals with tetraplegia due to a spinal cord injury (SCI). FES has proven to be a successful technique for controlling many functional tasks such as grasping, standing, and even limited walking. However, translating these successes to reaching motions has proven difficult due to the complexity of the arm and the goaldirected nature of reaching motions. The state-of-the-art systems either use robots to assist the FES-driven reaching motions or control the arm of healthy subjects to complete planar motions. These controllers do not directly translate to controlling the full-arm of an individual with tetraplegia because the muscle capabilities of individuals with spinal cord injuries are unique and often limited due to muscle atrophy and the loss of function caused by lower motor neuron damage. This dissertation aims to develop a full-arm FES-driven reaching controller that is capable of achieving 3D reaching motions in an individual with a spinal cord injury. Aim 1 was to develop a complete-arm FES-driven reaching controller that can hold static hand positions for an individual with high tetraplegia due to SCI. We developed a combined feedforward-feedback controller which used the subject-specific model to automatically determine the muscle stimulation commands necessary to hold a desired static hand position. Aim 2 was to develop a subject-specific model-based control strategy to use FES to drive the arm of an individual with high tetraplegia due to SCI along a desired path in the subject’s workspace. We used trajectory optimization to find feasible trajectories which explicitly account for the unique muscle characteristics and the simulated arm dynamics of our subject with tetraplegia. We then developed a model predictive control controller to iii control the arm along the desired trajectory. The controller developed in this dissertation is a significant step towards restoring full arm reaching function to individuals with spinal cord injuries

Neurology

Contains research objectives and reports on five research projects.U.S. Public Health Service (MH-06175-02)U.S. Navy (Office of Naval Research (Nonr-1841(70))U. S. Air Force (AF 49(638)-1313)U.S. Public Health Service (B-3055-4)U.S. Public Health Service (B-3090-4

Development of a micromanipulator-based loading device for mechanoregulation study of human mesenchymal stem cells in three-dimensional collagen constructs

Mechanical signal is important for regulating cellular activities, including proliferation, metabolism, matrix production, and orientation. Bioreactors with loading functions can be used to precondition cells in three-dimensional (3D) constructs so as to study the cellular responses to mechanical stimulation. However, full-scale bioreactor is not always an affordable option considering the high cost of equipments and the liter-sized medium with serum and growth factor supplements. In this study, a custom-built loading system was developed by coupling a conventional camera-equipped inverted research microscope with two micromanipulators. The system was programmed to deliver either cyclic compressive loading with different frequencies or static compressive loading for 1 week to investigate the cellular responses of human mesenchymal stem cells (hMSCs) entrapped in a 3D construct consists of reconstituted collagen fibers. Cellular properties, including their alignment, cytoskeleton, and cell metabolism, and properties of matrix molecules, such as collagen fiber alignment and glycosaminoglycan deposition, were evaluated. Using a MatLab-based image analysis program, reorientation of the entrapped cells from a random distribution to a preferred alignment along the loading direction in constructs with both static and cyclic compression has been demonstrated, but no such alignment was found in the free-floating controls. Fluorescent staining on filamentous actin cytoskeleton also confirmed the finding. Nevertheless, the collagen fiber meshwork entrapping the hMSCs remained randomly distributed, and no change in cellular metabolism and glycosaminoglycans production was noted. The current study provides a simple and affordable option toward setting up a mechanoregulation facility based on existing laboratory equipments and sheds new insights on the effect of mechanical loading on the alignment of hMSCs in 3D collagen constructs. Copyright © 2010, Mary Ann Liebert, Inc.published_or_final_versio

Motor control-based assessment of therapy effects in individuals post-stroke: implications for prediction of response and subject-specific modifications

Producing a coordinated motion such as walking is, at its root, the result of healthy communication pathways between the central nervous system and the musculoskeletal system. The central nervous system produces an electrical signal responsible for the excitation of a muscle, and the musculoskeletal system contains the necessary equipment for producing a movement-driving force to achieve a desired motion. Motor control refers to the ability an individual has to produce a desired motion, and the complexity of motor control is a mathematical concept stemming from how the electrical signals from the central nervous system translate to muscle activations. Exercising a high-level complexity of motor control is critical to producing a smooth motion. However, the occurrence of a sudden, detrimental neurological event like a stroke damages these connecting pathways between these two systems, and the result is a motion that is uncoordinated and energy-inefficient due to diminished motor control complexity. Stroke is a leading cause of disability with nearly 800,000 stroke victims each year in the U.S. alone, amounting to an estimated cost of $45.5B. Impaired mobility following a stroke is a widespread effect, with more than half of survivors over the age of 65 affected in this way, and up to 80% of survivors at some point experiencing hemiparesis during post-stroke recovery. As such, given the importance of independent mobility for quality of life, improving gait mechanics and mobility of stroke survivors has been the goal of rehabilitation efforts for decades. In this work, we mold together the forefronts of statistics and computational physics-based modeling to obtain insight and information about post-stroke hemiparetic gait mechanics and what drives them that would otherwise be unavailable. We expand upon previous work to quantify motor control complexity as it relates to the health of the neuromuscular system and analyze the effect of a specific therapy on motor control of individuals post-stroke. Secondly, we aim to develop a predictive model to conclude whether an individual will respond to the therapy based on kinematic and dynamic features from pre-therapy recordings. Lastly, we will determine how to individually tailor this therapy in order to achieve maximum improvement in motor control complexity in order to improve gait mechanics in individuals post-stroke

Feasibility of Using an Equilibrium Point Strategy to Control Reaching Movements of Paralyzed Arms with Functional Electrical Stimulation

Functional electrical stimulation (FES) is a technology capable of improving the quality of life for those with the loss of limb movement related to spinal cord injuries. Individuals with high-level tetraplegia, in particular, have lost all movement capabilities below the neck. FES has shown promise in bypassing spinal cord damage by sending electrical impulses directly to a nerve or muscle to trigger a desired function. Despite advancements in FES, full-arm reaching motions have not been achieved, leaving patients unable to perform fundamental tasks such as eating and grooming. To overcome the inability in current FES models to achieve multi-joint coordination, a controller utilizing muscle activations to achieve full-arm reaching motions using equilibrium point control on a computer-simulated human arm was developed. Initial simulations performed on the virtual arm generated muscle activations and joint torques required to hold a static position. This data was used as a model for Gaussian Process Regression to obtain muscle activations required to hold any desired static position. The accuracy of the controller was tested on twenty joint positions and was capable of holding the virtual arm within a mean of 1.1 ± 0.13 cm from an original target position. Once held in a static position, external forces were introduced to the simulation to evaluate if muscle activations returned the arm towards the original position after being moved away within a basin of attraction. It was found that the basin of attraction was limited to a 15 cm sphere around the joint position, regardless of position in the workspace. Muscle activations were then tested and found to successfully perform movements between points within the basin. The development of a controller capable of equilibrium point controlled movement is the initial step in recreating these movements in high-level tetraplegia patients with an implanted FES

Feasibility of Using an Equilibrium Point Strategy to Control Reaching Movements of Paralyzed Arms with Functional Electrical Stimulation

Functional electrical stimulation (FES) is a technology capable of improving the quality of life for those with the loss of limb movement related to spinal cord injuries. Individuals with high-level tetraplegia, in particular, have lost all movement capabilities below the neck. FES has shown promise in bypassing spinal cord damage by sending electrical impulses directly to a nerve or muscle to trigger a desired function. Despite advancements in FES, full-arm reaching motions have not been achieved, leaving patients unable to perform fundamental tasks such as eating and grooming. To overcome the inability in current FES models to achieve multi-joint coordination, a controller utilizing muscle activations to achieve full-arm reaching motions using equilibrium point control on a computer-simulated human arm was developed. Initial simulations performed on the virtual arm generated muscle activations and joint torques required to hold a static position. This data was used as a model for Gaussian Process Regression to obtain muscle activations required to hold any desired static position. The accuracy of the controller was tested on twenty joint positions and was capable of holding the virtual arm within a mean of 1.1 ± 0.13 cm from an original target position. Once held in a static position, external forces were introduced to the simulation to evaluate if muscle activations returned the arm towards the original position after being moved away within a basin of attraction. It was found that the basin of attraction was limited to a 15 cm sphere around the joint position, regardless of position in the workspace. Muscle activations were then tested and found to successfully perform movements between points within the basin. The development of a controller capable of equilibrium point controlled movement is the initial step in recreating these movements in high-level tetraplegia patients with an implanted FES