Hyperthermia has been introduced as a therapeutic method and adjuvant therapy in the treatment of some diseases such as breast and pancreatic cancers. On the other hand, other applications of hyperthermia have been considered. In this article, ways to treat knee pain caused by osteoarthritis, patellar chondromasia, rheumatism, knee infection, etc., have been studied using antenna hyperthermia. For antenna hyperthermia, is using a rectangular microstrip antenna, which is the simplest type of antenna. The antenna considered in this article has conformal conditions and is designed in the shape of a knee structure, to create a suitable knee covering. The antenna considered in this article has conformal conditions and is designed in the shape of a knee structure, to create a suitable knee covering. In addition to the geometric structure of the antenna, which fits the structure of the knee, the resonance frequency of the antenna is in the range of ISM standard frequencies and attempts have been made to place it at 2.4 GHz. On the other hand, to show the thermal pattern created by the antenna, the specific absorption rate of the tissue is investigated and its diagram is simulated by the antenna radiation field.

Blood transfusion is of great importance in the medical field, as blood donation centers are responsible for collecting and distributing blood and blood products. Artificial neural network is a data processing system getting ideas from the human brain and designs a data structure that acts like a neuron using programming science and by creating a network between these neurons and combining large amounts of data with smart algorithms and their rapid processing, the network is trained. In this study, data is extracted from the blood transfusion service center and the perceptron neural network, RBF neural network, Fisher’s discrimination ratio and genetic algorithm were examined, and finally the highest possible accuracy from the neural network was achieved.

One of the major causes of traffic accidents is driver’s drowsiness. For this reason, detecting whether the driver's eyes are open or closed is one of the critical factors in reducing road deaths. One way to detect whether your eyes are open or closed is to use EEG signals. EEG signals are obtained from the recording of electrical activity in the human brain. The present study uses a neural network that is applied to the driver's EEG signals to detect whether the eye is open or closed. The data of the EEG signals used in this paper consist of 14 features that are based on a statistical population of 600 people. Various neural network algorithms have been implemented for clustering these data into two classes of open or closed eyes, which are described in this paper. Perceptron neural network and radial base neural network (RBF) are two types of networks used in this paper. Also, in order to improve the execution speed and reduce the occupied space of the microcontroller, the genetic algorithm method has been used to optimize the fitting function of Fisher’s discriminant rate, in which the optimized function provides better results in the less occupied time and space.