Design and Evaluation of AIRGAIT Exoskeleton\u27s Leg Orthosis: Development of a Control Scheme and Strategy for a Noble Control of Antagonistic Mono- and Bi-Articular Actuators

芝浦工業大学201

MOSAR: A Soft-Assistive Mobilizer for Upper Limb Active Use and Rehabilitation

In this study, a soft assisted mobilizer called MOSAR from (Mobilizador Suave de Asistencia y Rehabilitación) for upper limb rehabilitation was developed for a 11 years old child with right paretic side. The mobilizer provides a new therapeutic approach to augment his upper limb active use and rehabilitation, by means of exerting elbow (flexion-extension), forearm (pronation-supination) and (flexion-extension along with ulnar-radial deviations) at the wrist. Preliminarily, the design concept of the soft mobilizer was developed through Reverse Engineering of his upper limb: first casting model, silicone model, and later computational model were obtained by 3D scan, which was the parameterized reference for MOSAR development. Then, the manufacture of fabric inflatable soft actuators for driving the MOSAR system were carried out. Lastly, a law close loop control for the inflation-deflation process was implemented to validate FISAs performance. The results demonstrated the feasibility and effectiveness of the FISAs for being a functional tool for upper limb rehabilitation protocols by achieving those previous target motions similar to the range of motion (ROM) of a healthy person or being used in other applications

Robotic simulators for tissue examination training with multimodal sensory feedback

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators

The development of an adaptive and reactive interface system for lower limb prosthetic application

Deep tissue injury (DTI) is a known problem correlating to the use of a prosthetic by a transtibial amputee (TTA), causing ulcer-like wounds on the residual limb caused by stress-induced cell necrosis. The magnitude of these stresses at the bone tissue interface has been identified computationally, far exceeding those measured at the skin's surface. Limited technology is available to directly target and reduce such cellular loading and actively reduce the risk of DTI from below-knee use. The primary aim of this project was to identify whether a bespoke prosthetic socket system could actively stiffen the tissues of the lower limb. Stabilising the residual tibia during ambulation and reducing stress concentrations on the cells. To achieve this, a proof-of-concept device was designed and manufactured, a system that allowed the change in displacement of a magnet to be responded to by counterbalancing load. The device was evaluated through experimentation on an able-bodied subject wearing an orthotic device designed to replicate the environment of a prosthetic socket. The chosen sensor effector system was validated against vector data generated by the Motek Medical Computer Assisted Rehabilitation Environment (CAREN.) The project explored a new concept of reactive loading of a below-knee prosthesis to reduce tibial/socket oscillation. The evaluation of the device indicated that external loading of the residual limb in such a manner could reduce the magnitude of rotation about the tibia and therefore minimise the conditions by which DTIs are known to occur. Efforts were made to move the design to the next iteration, focusing on implementing the target demographic.Deep tissue injury (DTI) is a known problem correlating to the use of a prosthetic by a transtibial amputee (TTA), causing ulcer-like wounds on the residual limb caused by stress-induced cell necrosis. The magnitude of these stresses at the bone tissue interface has been identified computationally, far exceeding those measured at the skin's surface. Limited technology is available to directly target and reduce such cellular loading and actively reduce the risk of DTI from below-knee use. The primary aim of this project was to identify whether a bespoke prosthetic socket system could actively stiffen the tissues of the lower limb. Stabilising the residual tibia during ambulation and reducing stress concentrations on the cells. To achieve this, a proof-of-concept device was designed and manufactured, a system that allowed the change in displacement of a magnet to be responded to by counterbalancing load. The device was evaluated through experimentation on an able-bodied subject wearing an orthotic device designed to replicate the environment of a prosthetic socket. The chosen sensor effector system was validated against vector data generated by the Motek Medical Computer Assisted Rehabilitation Environment (CAREN.) The project explored a new concept of reactive loading of a below-knee prosthesis to reduce tibial/socket oscillation. The evaluation of the device indicated that external loading of the residual limb in such a manner could reduce the magnitude of rotation about the tibia and therefore minimise the conditions by which DTIs are known to occur. Efforts were made to move the design to the next iteration, focusing on implementing the target demographic

Accurate multivariable arbitrary piecewise model regression of McKibben and Peano muscle static and damping force behavior

Machines that efficiently and safely interact with the uncertainty of the natural world need actuators with the properties of living creatures' muscles. However, the inherent nonlinearity of the static and damping properties that the most promising of these muscle-like actuators have makes them difficult to control. Our ability to accurately control these actuators requires accurate models of their behavior. One muscle-like actuator for which no accurate models have been specifically developed is the Peano muscle. This paper presents and validates a model generation algorithm, multivariable arbitrary piecewise model regression (MAPMORE), that produces accurate models for predicting the static and damping force behavior of Peano muscles, as well as of the popular McKibben muscle. MAPMORE builds a training data processing, muscle-specific model term dictionary, and piecewise function fusion framework around Billings et al's forward regression orthogonal least squares estimator algorithm. We demonstrate that MAPMORE's static and damping force models have a normalized root mean square error (NRMSE) of 48%–88% of the NRMSE of the most accurate of Peano and McKibben muscles' existing models. The improved accuracy of MAPMORE's models for these artificial muscles potentially aids the muscles' ability to be accurately controlled and hence is a step towards enabling machines that interact with the real world. Further steps could be made by improving MAPMORE's accuracy through the addition of hysteresis operator and lagged terms in the damping force dictionary

Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, have gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. As such, this article serves as a guideline on the fundamentals of identifying nonlinear block-oriented models for new practitioners, apart from presenting a comprehensive summary of cutting-edge trends within the context of this topic area

Development of an In-Vitro Passive and Active Motion Simulator for the Investigation of Shoulder Function and Kinematics

Injuries and degenerative diseases of the shoulder are common and may relate to the joint’s complex biomechanics, which rely primarily on soft tissues to achieve stability. Despite the prevalence of these disorders, there is little information about their effects on the biomechanics of the shoulder, and a lack of evidence with which to guide clinical practice. Insight into these disorders and their treatments can be gained through in-vitro biomechanical experiments where the achieved physiologic accuracy and repeatability directly influence their efficacy and impact. This work’s rationale was that developing a simulator with greater physiologic accuracy and testing capabilities would improve the quantification of biomechanical parameters. This dissertation describes the development and validation of a simulator capable of performing passive assessments, which use experimenter manipulation, and active assessments – produced through muscle loading. Respectively, these allow the assessment of functional parameters such as stability, and kinematic/kinetic parameters including joint loading. The passive functionality enables specimen motion to be precisely controlled through independent manipulation of each rotational degree of freedom (DOF). Compared to unassisted manipulation, the system improved accuracy and repeatability of positioning the specimen (by 205% & 163%, respectively), decreased variation in DOF that are to remain constant (by 6.8°), and improved achievement of predefined endpoints (by 21%). Additionally, implementing a scapular rotation mechanism improved the physiologic accuracy of simulation. This enabled the clarification of the effect of secondary musculature on shoulder function, and the comparison of two competing clinical reconstructive procedures for shoulder instability. This was the first shoulder system to use real time kinematic feedback and PID control to produce active motion, which achieved unmatched accuracy ( These developments can be a powerful tool for increasing our understanding of the shoulder and also to provide information which can assist surgeons and improve patient outcomes