Iterative learning control for stroke rehabilitation with input dependent muscle fatigue modeling

Abstract

Abstract-The consequences of a stroke is a major and increasing problem world wide. Many people who suffer a stroke are left with permanent impairment but the possibility exists that suitable rehabilitation could increase mobility and, for example, enable independent living. This, in turn, requires effective rehabilitation where it is known that currently available methods are relatively poor and are not well suited to home use, where the latter aspect is critical to improving practice and reducing costs. An accepted method to relearn lost function, such as reaching out to an object, is repeated attempts with learning from previous from those already completed with the application of applied stimulation if required. This requirement is analogous to iterative learning control and much progress, with supporting clinical trials data, has been reported on using this engineering design method to regulate the applied stimulation such that patient improvement in completing the task corresponds to increasing voluntary input and reduced stimulation. The applied stimulation in this application can induce muscle fatigue and this paper gives new result on enhancing the control laws to mitigate this unwanted effect.

Multiperiodic Repetitive Control for Functional Electrical Stimulation-Based Wrist Tremor Suppression

“…Thirdly, there are inevitable model uncertainties associated with the wrist musculoskeletal model used in controller design, a rigorous analysis and further improvement of the robustness performance of the repetitive controller is also a problem to be considered in the future research. Fourthly, in the next stage of our research, muscle fatigue will be incorporated into the design by explicitly including a model of muscle fatigue [43], and/or developing possible ways of reducing the required FES levels. Finally, the experimental results of healthy participants and intention tremor patient confirm the feasibility and effectiveness of this paper.…”

Control design of a de-weighting upper-limb exoskeleton: extended-based fuzzy

“…Although the results from this approach shows promising outcome, however, several needs still need to be done especially, for the usage of ILC and the fatigue model itself [17]. [25] enhanced [17] by improving the muscle and fatigue model. However, these two works are focusing only on the rehabilitation application [25].…”

“…[25] enhanced [17] by improving the muscle and fatigue model. However, these two works are focusing only on the rehabilitation application [25]. Hence, in this work, the focus is to investigate the effectiveness of the control approach of the exoskeleton in assisting fatigue people while doing work in domestic environment.…”