Individuals undergo significant changes in old age compared to their youth, which affects their lives. These changes occur in the skeletal, nervous, and muscular systems of the elderly, resulting in a decrease in walking speed. Therefore, in addition to conventional methods, there is a need for engineering approaches and perspectives in designing elderly rehabilitation to minimize the impact of aging on their lives. One of the methods that has better advantages compared to other methods is functional electrical stimulation. Before designing and implementing the stimulation system on individuals, it is necessary to simulate it on a neuromuscular skeletal model that represents walking. The selected model should have a suitable correlation with human data and consider skeletal, muscular, and nervous structures for eva‎luation of the electrical stimulation system. Based on this, by examining and eva‎luating different models, it was observed that the gear model has better performance and better conformity with human data. Since the gear model represents a young individual, the changes that occur in the elderly’s motor system are applied considering the characteristics of the model. To reduce the speed of the elderly model, an evolutionary adaptation strategy optimization algorithm was used to adjust the parameters of the neural part of the model, with its cost function based on the desired walking speed of the elderly model and less fatigue during walking. Additionally, the use of the algorithm ensures the consideration of uncertainty resulting from the physiological characteristics of each elderly individual. After creating an elderly model, there are complex challenges in designing functional electrical stimulation control for this model to improve the walking speed of the elderly individual. Initially, muscles that contribute to improving walking speed were selected based on expert opinions for functional electrical stimulation. A closed-loop control structure was used to design the controller, where the electrical stimulation signal is created based on the neural stimulation signal of the model in a proportional control manner. The proportional control coefficients of the controller need to be adjusted to increase the walking speed of the elderly model. For this purpose, an optimization algorithm was used to improve the speed through the cost function and minimize fatigue challenges due to electrical stimulation. The results of adjusting the control coefficients of the functional electrical stimulation control loop showed an increase in the walking speed of the elderly model, but it also resulted in sudden speed changes, which contradict the physiological characteristics of elderly individuals. Therefore, to prevent these sudden changes in speed, the cost function was modified to minimize the changes in the step length of the elderly model during movement and achieve consistency in the step length of the elderly model.

ايمان ايزدي نجف آبادي , احسان روحاني

مريم ذكري , جلال ذهبي