An Enhanced Model Free Adaptive Control Approach for Functional Electrical Stimulation Assisted Knee Joint Regulation and Control.

Functional electrical stimulation has been widely used in the neurologically disabled population as a rehabilitation method because of its intrinsic and higher ability to activate paralyzed muscles. However, the nonlinear and time-varying nature of the muscle against exogenous electrical stimulus makes it very challenging to achieve optimal control solutions in real-time, that results in difficulty in achieving functional electrical stimulus-assisted limb movement control in the real-time rehabilitation process. Model-based control methods have been suggested in many functional electrical stimulations elicited limb movement applications. However, in the presence of uncertainties and dynamic variations during the process the model-based control methods are unable to give a robust performance. In this work, a model-free adaptable control approach is designed to regulate knee joint movement with electrical stimulus assistance without prior knowledge of the dynamics of the subjects. The model free adaptive control with a data-driven approach is provided with recursive feasibility, compliance with input constraints, and exponential stability. The experimental results obtained from both able-bodied participants and a participant with spinal cord injury validate the ability of the proposed controller to allocate electrical stimulus for regulating seated knee joint movement in the pre-defined trajectory.

An Integrated Dynamic Closed Loop Simulation Platform for Elbow Flexion Augmentation Using an Upper Limb Exosuit Model.

Wearable robotic devices are designed to assist, enhance or restore human muscle performance. Understanding how a wearable robotic device changes human biomechanics through complex interaction is important to guide its proper design, parametric optimization and functional success. The present work develops a human-machine-interaction simulation platform for closed loop dynamic analysis with feedback control and to study the effect of soft-robotic wearables on human physiology. The proposed simulation platform incorporates Computed Muscle Control (CMC) algorithm and is implemented using the MATLAB -OpenSim interface. The framework is generic and will allow incorporation of any advanced control strategy for the wearable devices. As a demonstration, a Gravity Compensation (GC) controller has been implemented on the wearable device and the resulting decrease in the joint moments, muscle activations and metabolic costs during a simple repetitive load lifting task with two different speeds is investigated.

Transfemoral amputee's limit of stability and sway analysis during weight shifting exercise with a vibrotactile feedback system.

Amputation in the transfemoral amputee (TFA) results in loss of sensory feedback of the amputated limb and therefore results in the poor postural stability. To assess the postural stability, the limit of stability (LOS) is a reliable parameter. In this study, we have investigated the effect of vibrotactile feedback (VF) on the LOS during the weight shifting exercise (WSE) for a TFA. The data of centre of pressure (COP) during WSE was collected from five TFA and five healthy individuals using a zebris force plate. The VF was provided on the amputated/healthy limb's anterior and posterior part of the stump/thigh during forward and backward WSE, respectively. A customized foot insole with 24 embedded dielectric sensors was used to drive the vibratory motor. The effect of VF was analyzed by pre and post-test. Results show that with the use of VF, TFA significantly improved (t-test, p < .05) the sound limb's LOS during forward WSE. Also, ANOVA analysis between WSE divisions shows that the prosthetic limb does not follow the path of WSE. We further examine the spectral power using the Welch method to determine the dominant sway frequency of COP. It shows a decreased frequency between 0.5-2 Hz in the healthy and decreased frequency between 0-0.5 Hz and >2 Hz in the amputee with VF. It concluded that VF could improve the LOS of TFA during WSE which ultimately leads to postural stability enhancement.

Approximate N-Player Nonzero-Sum Game Solution for an Uncertain Continuous Nonlinear System.

An approximate online equilibrium solution is developed for an N -player nonzero-sum game subject to continuous-time nonlinear unknown dynamics and an infinite horizon quadratic cost. A novel actor-critic-identifier structure is used, wherein a robust dynamic neural network is used to asymptotically identify the uncertain system with additive disturbances, and a set of critic and actor NNs are used to approximate the value functions and equilibrium policies, respectively. The weight update laws for the actor neural networks (NNs) are generated using a gradient-descent method, and the critic NNs are generated by least square regression, which are both based on the modified Bellman error that is independent of the system dynamics. A Lyapunov-based stability analysis shows that uniformly ultimately bounded tracking is achieved, and a convergence analysis demonstrates that the approximate control policies converge to a neighborhood of the optimal solutions. The actor, critic, and identifier structures are implemented in real time continuously and simultaneously. Simulations on two and three player games illustrate the performance of the developed method.