Gait asymmetrical evaluation of lower limb amputees using wearable inertial sensors.

This study presents an analysis and evaluation of gait asymmetry (GA) based on the temporal gait parameters identified using a portable gait event detection system, placed on the lateral side of the shank of both lower extremities of the participants. Assessment of GA was carried out with seven control subjects (CS), one transfemoral amputee (TFA) and one transtibial amputee (TTA) while walking at different speeds on overground (OG) and treadmill (TM). Gait cycle duration (GCD), stance phase duration (SPD), swing phase duration (SwPD), and the sub-phases of the gait cycle (GC) such as Loading-Response (LR), Foot-Flat (FF), and Push-Off (PO), Swing-1 (SW-1) and Swing-2 (SW-2) were evaluated. The results revealed that GCD showed less asymmetry as compared to other temporal parameters in both groups. A significant difference (p < 0.05) was observed between the groups for SPD and SwPD with lower limb amputees (LLA) having a longer stance and shorter swing phase for their intact side compared to their amputated side, resulting, large GA for TFA compared to CS and TTA. The findings could potentially contribute towards a better understanding of gait characteristics in LLA and provide a guide in the design and control of lower limb prosthetics/orthotics.

Performance evaluation of PSO-PID and PSO-FLC for continuum robot's developed modeling and control.

Continuum robots are complex structures that require sophisticated modeling and control methods to achieve accurate position and motion tracking along desired trajectories. They are highly coupled, nonlinear systems with multiple degrees of freedom that pose a significant challenge for conventional approaches. In this paper, we propose a system dynamic model based on the Euler-Lagrange formulation with the assumption of piecewise constant curvature (PCC), where we accounts for the elasticity and gravity effects of the continuum robot. We also develop and apply a particle swarm optimization (PSO) algorithm to optimize the parameters of our developed controllers: an inverse dynamic proportional integral derivative (PID) controller and an inverse dynamic fuzzy logic controller (FLC), where we use the integral time of absolute error (ITAE) as the objective function for the PSO algorithm. We validate our proposed model and optimized controllers through different designed trajectories, simulated using our developed unique animated MATLAB simulation. The results show that the PSO-PID controller improves the rise time, overshoot percentage, and settling time by 16.3%, 31.1%, and 64.9%, respectively, compared to the PID controller without PSO. The PSO-FLC controller shows the best performance among all controllers, with a settling time of 0.7 s and a rise time of 0.4 s, leading to the highest level of precision in trajectory tracking. The ITAE error for the PSO-FLC controller is 11.4% and 29.9% lower than that of the PSO-PID and FLC controllers, respectively.

Optimizing power consumption and position control in an electro-hydraulic system with cylinder bypass and NN-MPC.

This study introduces an innovative approach to enhance the energy efficiency and position control performance of electro-hydraulic systems, employing a comprehensive comparative analysis. It presents and evaluates three control techniques: Proportional-Integral-Derivative (PID) control, Model Predictive Control (MPC), and Neural Network Model Predictive Control (NN-MPC). These methods are systematically assessed across varying load conditions. Notably, our research unequivocally establishes the exceptional performance of the NN-MPC approach, even when confronted with load variations. Furthermore, the study conducts an exhaustive examination of energy consumption by comparing a conventional system, where a flow control valve is not utilized as a hydraulic cylinder bypass, with a proposed system that employs a fully open Flow Control Valve (FCV). The results underscore the remarkable energy savings achieved, reaching up to 9% at high load levels.

A conceptual design of circular adaptive façade module for reuse.

Climate change has an impact on the ecosystem, and subsequently, it affects the built environment. Building envelope has a vital role in controlling the integration between indoor and outdoor environmental quality. The responsivity of the façade has proven its efficiency in optimizing the global energy performance of buildings. Adaptive façades are multifunctional reconciling envelope dynamic systems that improve sustainability with the purpose of utilizing environmental parameters. This paper tackles the research gap in integrating façades circularity, adaptive envelopes, and design for disassembly. The research investigates the merge between biodegradability, circularity of adaptive façades components, and interior space micro-climate control for energy efficiency. This paper presents a proof of concept for a circular adaptive façade during two phases in its life cycle: operation and reuse phases. A scientific quantitative method took place which is based on a hybrid method; computational simulation, smart control, and an up-scale model. Adaptability is investigated through the façade life cycle from design to disassembly instead of demolition and consequent waste production, by exploiting sustainable materials. As a result, an empirical prototype is constructed. The prototype provides 3 levels of adaptability across the design, operation, and disassembly for reuse. Subsequently, this work proposes an up-scale physical model that can help in mitigating the climate change effects.

Localization of composite prosthetic feet: manufacturing processes and production guidelines.

Amputation levels in Egypt and the surrounding neighborhood require a state intervention to localize the manufacturing of prosthetic feet. Amputations are mainly due to chronic diseases, accidents, and hostilities' casualties. The prosthetic foot type is traditionally classified according to the number of axial rotational movements, and is recently classified according to the energy activeness of the foot. The localization of this industry needs a preliminary survey of the domestic technological levels with respect to the foot type. Upon the results of this survey, the energy storage response foot has appealing metrics to proceed with its manufacturing. A prototype manufacturing chain is designed and a set of these feet with a certain commercial size of 27 is manufactured. Resin impregnation technology for carbon fiber composites is followed in this work. The feet are tested according to ISO 22,675. Based on the dimensional and mechanical results, a manufacturing value chain is proposed with the prospective resin transfer molding technology. This value chain will guarantee the required localization as well as the natural growth of this value chain with all related activities like accreditation of practices as well as manpower certification.

An Improved Approach for Grasp Force Sensing and Control of Upper Limb Soft Robotic Prosthetics.

The following research proposes a closed loop force control system, which is implemented on a soft robotic prosthetic hand. The proposed system uses a force sensing approach that does not require any sensing elements to be embedded in the prosthetic's fingers, therefore maintaining their monolithic structural integrity, and subsequently decreasing the cost and manufacturing complexity. This is achieved by embedding an aluminum test specimen with a full bridge strain gauge circuit directly inside the actuator's housing rather than in the finger. The location of the test specimen is precisely at the location of the critical section of the bending moment on the actuator housing due to the tension in the driving tendon. Therefore, the resulting loadcell can acquire a signal proportional to the prosthetic's grasping force. A PI controller is implemented and tested using this force sensing approach. The experiment design includes a flexible test object, which serves to visually demonstrate the force controller's performance through the deformation that the test object experiences. Setpoints corresponding to "light", "medium", and "hard" grasps were tested with pinch, tripod, and full grasps and the results of these tests are documented in this manuscript. The developed controller was found to have an accuracy of ±2%. Additionally, the deformation of the test object increased proportionally with the given grasp force setpoint, with almost no deformation during the light grasp test, slight deformation during the medium grasp test, and relatively large deformation of the test object during the hard grasp test.

Design of a Data Glove for Assessment of Hand Performance Using Supervised Machine Learning.

The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitation robotics and automated assessment systems can ease this burden by assisting in the rehabilitation of patients with a high level of recovery. This assistance will enable medical professionals to either better provide for patients with severe injuries or treat more patients. It also translates into financial assistance as well in the long run. This paper demonstrated an automated assessment system for in-home rehabilitation utilizing a data glove, a mobile application, and machine learning algorithms. The system can be used by poststroke patients with a high level of recovery to assess their performance. Furthermore, this assessment can be sent to a medical professional for supervision. Additionally, a comparison between two machine learning classifiers was performed on their assessment of physical exercises. The proposed system has an accuracy of 85% (±5.1%) with careful feature and classifier selection.