In this paper, the work has been carried out taking SIW and Leaky Wave Antenna. Electromagnetic waves based method is accurate and feasible.

In this paper, different methods which are used for monitoring respiratory activity have been studied. The conventional body mounted sensors can also infect sensor as the virus can stay on surface which limits the reuse of sensors for many days. Proper and real-time monitoring of the respiratory activity of a patient is very important because failure of respiratory activity is difficult to predict in advance and this can become life critical in just few minutes. The contact force is always within a safe and stable range, and the average contact force is about 5.2 N. The preliminary results show that the control strategy performs well in the constant force-tracking of medical auscultation tasks. The control strategy is tested in a real environment.

We have carried out a large number of simulation experiments, and the error between the tracking of normal force and expected force is basically within ☐.5 N. We propose a constant force-tracking control method for dynamic environments and a modeling method that satisfies physical characteristics to simulate the dynamic breathing process and design an optimal reward function for the task of achieving efficient learning of the control strategy. Therefore, this paper investigates how to use deep reinforcement learning to solve dynamic medical auscultation tasks. Intelligent medical robots can effectively help doctors carry out a series of medical diagnoses and auxiliary treatments and alleviate the current shortage of social personnel.

Breath by S. Atzeni