Application of Intelligent Control in Medical Education The application of intelligent control system to the teaching effect evaluation of functional comprehensive experimental teaching is important. Intelligent control is to study and use some structure mechanism of human brain, knowledge and experience to control the system. With the intelligent control, the problem of control pattern can be regarded as the problem of recognition pattern. The recognition pattern is the change of recognized signal into the action signal. It is generally believed that the control system of neural network has good intelligence and robustness. It can deal with the control problem of complicated industrial production process with high dimension, nonlinearity, strong coupling and uncertainty. Its remarkable characteristic is that it has the learning ability, it can constantly correct the connection between units and store them, so it has good mapping ability for the nonlinear system which is difficult to model. The key modification can be regarded as the modification of the mapping to achieve the desired objective function.

Intelligent wearable rehabilitation robot control system based on mobile communication network Abstract   A large number of disabled people are caused by major diseases and accidents. Because disabled patients cannot exercise freely on their own, in order to prevent muscle atrophy, the most effective treatment is to exercise the patientsxe2x80x99 limbs. Therefore, it is necessary to choose a more suitable rehabilitation training method to replace the traditional artificial rehabilitation training method, and the use of intelligent wearable rehabilitation robots to treat hemiplegia patients is particularly important for the rehabilitation treatment of hemiplegia patients. Rehabilitation robots can promote the development of medical technology and medical equipment, and have important practical significance for patients to overcome disease and recover health and build a harmonious family. This paper mainly studies the EMG research of the control system of intelligent wearable rehabilitation robot based on mobile communication network. This paper studies the way of stimulating signals and the processing of signal feedback in the process of electromyographic stimulation of rehabilitation robots to improve the rehabilitation effect of robots after stimulation; explores the problem of using biofeedback and fuzzy control rules to control patients for rehabilitation training, which urges patients actively participate in rehabilitation treatment, effectively guide the recovery of patientsxe2x80x99 selfconsciousness, and build a variety of training modes for rehabilitation robots to enhance the robotxe2x80x99s ability to adapt to different groups of people. In the experiments of this paper, the time window for data processing is 256ms, and the delay is also 256ms. It can be seen that the original SEMG signal of the control signal has some delay compared with the filtered SEMG signal.