An optimized and chaotic intelligent system for a 3DOF rehabilitation robot for lower limbs based on neural network and genetic algorithm

Nowadays due to the large number of patients that require physiotherapy, the need for rehabilitation service has increased tremendously. Applied exercises in rehabilitation practices such as passive, assistive, and resistance exercises regarding these patients' conditions play an important role in helping patients recover their ability to move, walk and do basic tasks. Rehabilitation of disabled patients, who suffer from movement disability is a prolonged and sumptuous task that requires patience. Moreover, it does cause some mental problems for the therapist. To tackle these obstacles, rehabilitation equipment is continuously modified based on the requirement and welfare of the patients. Meanwhile, researches related to the use of robots in the field of rehabilitation has surged. This paper proposes a new chaotic map that is used to select the desired path coordination for each joint and it is based on each joint's degree of freedom. Moreover, an optimized method for a 3DOF robot is presented using an optimal intelligent control system for the rehabilitation of hip and knee joints. Angles and velocity of the knee and hip joints are optimized by the Genetic Algorithm to get to the desired route and are then calculated by Artificial Neural Networks. The experimental results show that the presented technique can learn the action of the physiotherapist at each stage, for each patient, and to imitate independently.

Automated summary

With the increasing number of patients requiring physiotherapy, there is a growing demand for rehabilitation services. Different types of exercises play a significant role in helping patients recover their ability. Rehabilitation is a lengthy process that requires patience and continuous effort. The continuous improvement of rehabilitation equipment and the use of robots in rehabilitation are currently key areas of research.