A Robotic Neuro-Musculoskeletal Simulator for Spine Research

An influential conceptual framework advanced by Panjabi represents the living spine as a complex neuromusculoskeletal system whose biomechanical functioning is rather finely dependent upon the interactions among and between three principal subsystems: the passive musculoskeletal subsystem (osteoligamentous spine plus passive mechanical contributions of the muscles), the active musculoskeletal subsystem (muscles and tendons), and the neural and feedback subsystem (neural control centers and feedback elements such as mechanoreceptors located in the soft tissues) [1]. The interplay between subsystems readily encourages thought experiments of how pathologic changes in one subsystem might influence another--for example, prompting one to speculate how painful arthritic changes in the facet joints might affect the neuromuscular control of spinal movement. To answer clinical questions regarding the interplay between these subsystems the proper experimental tools and techniques are required. Traditional spine biomechanical experiments are able to provide comprehensive characterization of the structural properties of the osteoligamentous spine. However, these technologies do not incorporate a simulated neural feedback from neural elements, such as mechanoreceptors and nociceptors, into the control loop. Doing so enables the study of how this feedback--including pain-related--alters spinal loading and motion patterns. The first such development of this technology was successfully completed in this study and constitutes a Neuro-Musculoskeletal Simulator. A Neuro-Musculoskeletal Simulator has the potential to reduce the gap between bench and bedside by creating a new paradigm in estimating the outcome of spine pathologies or surgeries. The traditional paradigm is unable to estimate pain and is also unable to determine how the treatment, combined with the natural pain avoidance of the patient, would transfer the load to other structures and potentially increase the risk for other problems. The novel Neuro-Musculo

Modeling the human tibio-femoral joint using ex vivo determined compliance matrices.

Several approaches have been used to devise a model of the human tibio-femoral joint for embedment in lower limb musculoskeletal models. However, no study has considered the use of cadaveric 6x6 compliance (or stiffness) matrices to model the tibio-femoral joint under normal or pathological conditions. The aim of this paper is to present a method to determine the compliance matrix of an ex vivo tibio-femoral joint for any given equilibrium pose. Experiments were carried out on a single ex vivo knee, first intact and, then, with the anterior cruciate ligament (ACL) transected. Controlled linear and angular displacements were imposed in single degree-of-freedom (DoF) tests to the specimen and resulting forces and moments measured using an instrumented robotic arm. This was done starting from seven equilibrium poses characterized by the following flexion angles: 0°, 15°, 30°, 45°, 60°, 75°and 90°. A compliance matrix for each of the selected equilibrium poses and for both the intact and ACL deficient specimen was calculated. The matrix, embedding the experimental load-displacement relationship of the examined DoFs, was calculated using a linear least squares inversion based on a QR decomposition, assuming symmetric and positive-defined matrices. Single compliance matrix terms were in agreement with the literature. Results showed an overall increase of the compliance matrix terms due to the ACL transection (2.6 ratio for rotational terms at full extension) confirming its role in the joint stabilization. Validation experiments were carried out by performing a Lachman test (the tibia is pulled forward) under load control on both the intact and ACL-deficient knee and assessing the difference (error) between measured linear and angular displacements and those estimated using the appropriate compliance matrix. This error increased non-linearly with respect to the values of the load. In particular, when an incremental posterior-anterior force up to 6 N was applied to the tibia of the intact specimen, the errors on the estimated linear and angular displacements were up to 0.6 mm and 1.5°, while for a force up to 18 N the errors were 1.5 mm and 10.5°, respectively. In conclusion, the method used in this study may be a viable alternative to characterize the tibio-femoral load-dependent behavior in several applications

Relationship Between Arch Height and Midfoot Joint Pressures During Gait

A foot arch is a multi-segmented curved structure which acts as a spring during locomotion. It is well known that ligaments are important components contributing to this spring-like property of the arch. In addition, intrinsic and extrinsic foot muscles contribute to arch support. According to the windlass foot model, arch height and midfoot joint orientation change during gait. However, it is not known whether altered joint configurations result in increased joint stress during gait. If so, it is possible for there to be a vicious cycle in which joint stress increases as the arch height diminishes, which may then lead to further increases in joint stresses and eventual bone destruction. The purpose of this study was to examine joint pressure differences of the midfoot in normal and diabetic feet during walking simulation using a robotic system. This study focused on the relative importance of muscles, ligaments and bony structures. Sixteen cadaver foot specimens were used in this study. Joint pressures were measured dynamically during full stance at four medial locations (the first cuneometatarsal, medial cuneonavicular, middle cuneonavicular, and first intercuneiform). Human gait at 25 typical walking speed and 66.7 body weight was simulated with the Universal Musculoskeletal Simulator. It was shown that diabetic cadaver feet had, on average, a 46 higher peak in pressures, than control cadaver feet across all four tested joints. There were inverse correlations between the arch height and the peak joint pressure during the simulated arch collapse. It was proven that the acquired flat foot, caused by the tibialis posterior dysfunction, caused medial peak joint pressure increase by 12 across all tested joints. These results could be used in furthering our understanding of the etiology of diabetic foot diseases. Also, these findings could suggest better treatment for diabetic patients, who are at risk for Charcot foot abnormalitie

Relationship Between Arch Height and Midfoot Joint Pressures During Gait

A foot arch is a multi-segmented curved structure which acts as a spring during locomotion. It is well known that ligaments are important components contributing to this spring-like property of the arch. In addition, intrinsic and extrinsic foot muscles contribute to arch support. According to the windlass foot model, arch height and midfoot joint orientation change during gait. However, it is not known whether altered joint configurations result in increased joint stress during gait. If so, it is possible for there to be a vicious cycle in which joint stress increases as the arch height diminishes, which may then lead to further increases in joint stresses and eventual bone destruction. The purpose of this study was to examine joint pressure differences of the midfoot in normal and diabetic feet during walking simulation using a robotic system. This study focused on the relative importance of muscles, ligaments and bony structures. Sixteen cadaver foot specimens were used in this study. Joint pressures were measured dynamically during full stance at four medial locations (the first cuneometatarsal, medial cuneonavicular, middle cuneonavicular, and first intercuneiform). Human gait at 25 typical walking speed and 66.7 body weight was simulated with the Universal Musculoskeletal Simulator. It was shown that diabetic cadaver feet had, on average, a 46 higher peak in pressures, than control cadaver feet across all four tested joints. There were inverse correlations between the arch height and the peak joint pressure during the simulated arch collapse. It was proven that the acquired flat foot, caused by the tibialis posterior dysfunction, caused medial peak joint pressure increase by 12 across all tested joints. These results could be used in furthering our understanding of the etiology of diabetic foot diseases. Also, these findings could suggest better treatment for diabetic patients, who are at risk for Charcot foot abnormalitie

Achieving human-like dexterity in robotic hands : inspiration from human hand biomechanics and neuromuscular control

The human hand's unique biomechanical structure and neuromuscular control combine to produce amazing dexterous capabilities in a way that is still not fully understood. The Anatomically Correct Testbed (ACT) hand is a robotic system that is designed as a physical simulation of the human hand, and can help us examine and potentially uncover the roles of biomechanics and neural control in achieving dexterity. In this dissertation, I utilize the ACT hand and other robotic systems to explore the underlying sources of human hand dexterity, with the goal of understanding the fundamental differences between robotic and human hands in terms of (i) mechanical joint/tendon structure and (ii) control strategies. To begin, I develop comprehensive mechanical models that describe the musculoskeletal and tendon mechanics of the fingers and thumb of the human hand. Then, I work to isolate the contributions of biomechanical structure and neuromuscular control toward human dexterity. I have developed and implemented control strategies for achieving fine object manipulation first with the robotic hand of a space humanoid, Robonaut 2, and then with the ACT hand. I examined the unique control challenges, including uncontrollable joints and the requirement of accurate internal models, that arise due to the human hand's complex musculotendon structure and the potential advantages offered by the human hand's design, such as passive joint coupling to facilitate grasp shape adaptation and force production capabilities that are ideally suited for common manipulation tasks. Finally, inspired by the neuromuscular control strategies of the human hand, I have developed a novel hierarchical control strategy for the ACT hand and experimentally demonstrated improved grasp stability and manipulation capabilities compared to conventional robotic control laws. Through an in-depth exploration of human hand biomechanics and neuromuscular control, theoretical control analysis of robotic and human hands, and experimental demonstration of fine object manipulation, this work uncovers crucial insights into the sources of human hand dexterity that have the potential to drive innovative design and control strategies and bring robotic and prosthetic hands closer to human levels of dexterity.Mechanical Engineerin