As an important branch of medical robotics, a rehabilitation training robot for the hemiplegic upper limbs is a research hotspot of rehabilitation training. Based on the motion relearning program, rehabilitation technology, human anatomy, mechanics, computer science, robotics, and other fields of technology are covered. Based on an sEMG real-time training system for rehabilitation, the exoskeleton robot still has some problems that need to be solved in this field. Most of the existing rehabilitation exoskeleton robotic systems are heavy, and it is difficult to ensure the accuracy and real-time performance of sEMG signals. In this paper, we design a real-time training system for the upper limb exoskeleton robot based on the EMG signal. It has four main characteristics: light weight, portability, high precision, and low delay. This work includes the structure of the rehabilitation robotic system and the method of signal processing of the sEMG. An experiment on the accuracy and time delay of the sEMG signal processing has been done. In the experimental results, the recognition accuracy of the sEMG is 94%, and the average delay time is 300 ms, which meets the accuracy and real-time requirements.

In the process of artificial interventional therapy, the operation of artificial catheter is not accurate, which will bring strong radiation damage to surgeons. The purpose of this study is to develop a catheter operating system of surgical robot to assist doctors in remote operation and avoid the influence of radiation. BP neural network plays an important role in the flexibility and rapidity of control. According to the actual output of the system, the control parameters of the controller are constantly adjusted to achieve better output effect. This paper introduces the practical application of BP neural network PID controller in the remote operation of the system and compares with the traditional PID controller. The results show that the new control algorithm is feasible and effective. The results show that the synchronization performance of BP neural network PID controller is better than that of traditional PID controller.

The simulation of the gas flow field and electrostatic field in the photoionization detector by COMSOL was conducted based on principle investigation in the present study. Under the guidance of simulation results, structural optimization was carried out to significantly reduce the dead volume of the ionization chamber, and finally, the relationship between offset voltage and collection efficiency was obtained which led to a remarkable increase in the collection efficiency of charged ions in the photoionization detector. Then an ionization chamber with low interference and fast response was developed. Then experiment was performed with toluene as a VOCs gas under the condition of optimal gas flow rate of 50 ml, UV lamp ionization energy of 10.86 eV. The results showed that the ion collection efficiency reached 91% at a bias voltage of 150 V. Moreover, a preferred linearity of 99.99% was obtained, and a ppb level of LOD can be achieved. The determination results well-fitted the relationship between offset voltage and the response value obtained in the simulation.

This paper presents a novel robotic catheter system for MIS (minimally invasive surgery), we developed a PID controller to the robotic catheter system for improving the stability and consistency, and also, we do the experiment to evaluate the feasibility of developed PID controller, the developed robotic catheter system can be used for training unskilled surgeons to do the operation of intravascular neurosurgery. The novel robotic catheter operating system has good maneuverability, it can simulate surgeon's operating skill to insert and rotate catheter. The characteristic evaluations (rotating motion and inserting motion) have also been done to verify the validity of the system, the experimental results indicated that the stability and responsibility of system were good, the robotic catheter system was fitting to be used for training unskilled surgeons to do the operation of intravascular neurosurgery.

In interventional surgery, the manual operation of the catheter is not accurate. It is necessary to operate the catheter skillfully and effectively to protect the surgeon from radiation injury. The purpose of this paper is to design a new robot catheter operating system, which can help surgeons to complete the operation with high mechanical precision. On the basis of the original mechanical structure—real catheter, the operation information of the main end operator is collected. After the information is collected, the control algorithm of the system is improved, and the BP neural network is combined with the traditional PID controller to adjust the PID control parameters more effectively and intelligently so that the motor can reflect the output of the controller better and faster. The feasibility and superiority of the BP neural network PID controller are verified by simulation experiments.

Interventional surgery robots are essential in cardiovascular surgery as remote medical devices. By performing remote surgery, surgeons can reduce surgical fatigue and after-effects from heavy surgical instruments and radiation, ensuring that cardiovascular surgery is performed in a safe and reliable manner. To enhance stability during interventional procedures and reduce the impact of surgical risk due to factors where the robotic guidewire section from the end is vulnerable to mechanical jitter or blockage by blood flow, lipids, and thrombus inside the vessel, a new control method is proposed. The active disturbance rejection controller (ADRC) combined with intelligence algorithms is used to improve the performance of the controller by introducing the fuzzy inference algorithm and RBF neural network algorithm to self-adjust the parameters of the controller so that it has a greater ability to compensate for the disturbance factors appearing in the system. In numerical simulation experiments, the advantages and disadvantages of the ADRC combined with intelligence algorithms and the control performance of the conventional control strategy are analyzed in terms of the following: disturbance suppression performance and flexibility performance, respectively. Finally, different types of working conditions have been designed in the experimental platform to simulate the operation flow of in vivo vascular surgery. Experimental results show that the controller proposed in this paper meets the high accuracy, fast response, and low deviation required by interventional vascular surgery robots in complex surgical environments and can provide a more reliable guarantee for the stability of interventional surgery robots.