Design of a robotic device actuated by cables for human lower limb rehabilitation using self-adaptive differential evolution and robust optimization

Abstract

ABSTRACT:In engineering designed systems it is commonly considered that mathematical models, variables, and parameters are sufficiently reliable, i.e., there are no errors in modeling and estimation. However, the systems to be optimized can be sensitive to small changes in the designed variables causing significant changes in the objective function. Robust optimization is an approach for modeling optimization problems under uncertainty in which the modeler aims to find decisions that are optimal for the worst-case realization of the uncertainties within a given set of values. In this contribution, a self-adaptive heuristic optimization method, namely the Self-Adaptive Differential Evolution (SADE), is evaluated. Differently from the canonical Differential Evolution algorithm (DE), the SADE strategy is able to update the required parameters such as population size, crossover parameter, and perturbation rate, dynamically. This is done by considering a defined convergence rate on the evolution process of the algorithm in order to reduce the number of evaluations of the objective function. For illustration purposes, the SADE strategy is associated with the Mean Effective Concept (MEC) for insertion robustness, is applied to minimize forces applied in cables used for the rehabilitation of the human lower limbs by determining the positioning of motors. The results show that the methodology that was proposed (SADE+MEC) appears as an interesting strategy for the treatment of robust optimization problems.

Development of a novel body weight support system for gait rehabilitation

“…The control of the actuators was designed according to the following criteria: settling time t s less than 0.2 s, overshoot close to zero, and zero stationary error. Therefore, to estimate the parameters K P , K I , and K D , it used a meta-heuristic optimization system based on a differential evolution algorithm [33]. To use this system, several tests were performed automatically in the system, analyzing the system response to a known fixed input and collecting the corresponding response telemetry of each execution.…”

Predictive equation for a circular trajectory period in a cable-driven robot for rehabilitation

“…These robots have characteristics that can make them suitable for rehabilitation purposes, such as large workspace, transportability, flexibility, configurability, low weight/inertia. In addition, these devices do not intimidate or constrain the patient like industrial robots [7][8][9].…”

Conceptual design of a rehabilitation device based on cam-follower and crank-rocker mechanisms hand actioned

“…Conventional rehabilitation is performed manually by physiotherapists, using treadmills and systems to support the patient's weight [5]. In order to reduce physiotherapists' work, many groups have developed robotic devices for aiding in rehabilitation [6][7][8][9][10][11][12][13][14][15]. They have advantages when compared to traditional rehabilitation methods, such as: allowing physicians to take objective measures regarding the progress made by the patient, scheduling a personalized training plan, having a more precise trajectory performed than the one obtained manually, favoring high repeatability, besides some devices enabling the active participation of the patient during the movement [5].…”