Development of a feedback-controlled elbow simulator: design validation and clinical application

This work involves three topics that advance the functionality of an elbow simulator in the Orthopaedic Biomechanics Laboratory at Allegheny General Hospital. To draw clinically and scientifically meaningful conclusions from future cadaver studies conducted with the simulator, its design must be validated and the accuracy of the data collection methods demonstrated. The simulator was designed to offer physiologically-correct adjustable moment arms throughout the elbow's range of motion. To validate this, muscle moment arms were measured in three cadaver elbow specimens. Flexion-extension moment arms were measured at three different pronation/supination angles: fully pronated, fully supinated, and neutral. Pronation-supination moment arms for four elbow muscles were measured at three different flexion-extension angles: 30°, 60°, and 90°. The numeric results compared well with those previously reported. The biceps and pronator teres flexion-extension moment arms varied with pronation-supination position, and vice versa. This represents the first use of closed-loop feedback control in an elbow simulator, one of the first reports of both flexion-extension and pronation-supination moment arms in the same specimens, and demonstrates the adjustability of the moment arms that the elbow simulator can produce.Towards accurate motion analysis of the radial head, two areas were investigated. The first identified the phenomena of camera-switching, which occurs in motion analysis when data from one or more cameras is temporarily excluded from the computation of a marker's three-dimensional position. Tests with static markers showed that camera-switching could cause up to 3.7 mm of perceived movement. The second area of investigation set the stage for future studies with cadaver elbows. A protocol was developed to quantify both the travel of the native radial head, radial head implants, and the finite helical axis during pronation-supination movement. The tracking of implant motion employs a unique circle-fitting algorithm to determine the implant's center. A video-based motion analysis system was used to collect marker position coordinates actuated by a precision micrometer table. MATLAB code was designed and implemented to compute both the radial head position and finite helical axis from these data. Immediate future work will use these algorithms to evaluate radial head implants in comparison to the native radial head

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Opinions and Outlooks on Morphological Computation

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research