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In this study, a positive psychological capital (PPQ) was used to conduct a questionnaire survey on 1553 students in 5 colleges and universities in Sichuan Province to understand the current status and characteristics of college students’ psychological capital. The survey found that: The development of college students’ psychological capital and various dimensions is at the upper middle level; Compared with non-poor college students, it is found that the psychological capital and various dimensions of poor college students are significantly lower, and the girls with confidence are significantly lower Male students; Demographics (gender, grade), family background (birthplace, family structure, family economic status), and parenting style (mother parenting style, whether there is only one child) and other factors will affect the psychological capital status of college students.

Extracting features from EMG signal and using pattern recognition method to predict the user's intended movement are the core parts of myoelcrtic prostheses control strategy. To extract more information about muscle contraction strategy. To extract more information about muscle contraction state and body movement from EMG signals by selecting some efficient feature parameters is one of the most important researches in Rehabilitation field. Since EMG signal is a weak signal and affected easily by various interference factors in real time applications, studying the effect of these factors on the performance in classifying intended movements can provide guidelines for future research.

This article introduces the design of doppler radar microwave transmitting unit through the use of master-oscillator and power-amplifier radar transmitter. It emphasizes that in doppler radar system, to fulfill multi-functional requirements and adapt to different target environments, master-oscillator and power-amplifier radar transmitter should be used to achieve high frequency stability and choose transmitted waveform according to different situations in an automatic and flexible way.

With the purpose of improving the efficiency of experiments on aqueous two-phase system, optimizing experimental data and extracting the optimal value from results of experiments, experimental studies and applications in aqueous two-phase system are optimized through using SAS programming language and RSM algorithm in SAS statistical system, which compose the main content of this paper. The principle and formula of response surface methodology are mainly researched in this paper. In addition, explanation of response surface methodology through algorithm and description of such method through corresponding program are also studied.

System identification modeling is an essential precondition and foundation for the analysis, design and intelligent control of control system. Theory and method of identification modeling for rehabilitation training system for stroke patients' lower limbs based on support vector regression are mainly researched in this paper. In addition, simulated test is carried out to verify such method, based on which it can be said that such method is superior to other conventional methods in the aspect of accuracy and relevance.

In this paper, through the study of the characteristic rule of rolling massage experts' forearm surface EMG signal (sEMG) in rolling massage, the rolling massage analysis and evaluation methods based on the analysis of sEMG is presented. Therefore, during the implementation of rolling massage, muscle semg signals of the massage's three block muscle was collected at the real time, the relations between the electromyographic signal changeable characteristics and rolling method massage strength was discussed, meanwhile massager's muscle force situation was monitored, the ratio of muscle force was analyzed to assess and correct the massage action for the person whose action is not standard.

Learning algorithms of the support vector machine is to map the input vector to a high dimensional space through certain kernel function and separate the image of the original linear input vector with the maximum of interval under consideration. This paper is about the limb motion recognition problem of stroke patients, mapping the input vector to the reproducing kernel RKHS (reproducing Kernel Hilbert space) space and using the methods in linear space to solve nonlinear problems. Meanwhile, feature transformation is achieved by defining the inner product of samples in the feature space after its characteristics are changed. Experimental results show that the support vector machine which is made up of new Kernel function can greatly improve the recognition rate of action under the conditions of Mercer, providing theoretical basis for modeling of lower limb rehabilitation training system of stroke patients.