Virtual design of a measuring device integrated in electroacupuncture stimulator on Arduino

The object of research is the electrical conductivity of biologically active points. Biologically active points as a method of non-traditional medical procedures and diagnostics, as well as being used for therapeutic purposes. Although this method has become the subject of mass research, a complete theory of the method has not yet been formed. Based on research, it is possible to say that there are different approaches to explaining the mechanism of action. These independent studies suggest the existence of unique electrical properties in the areas of the skin where biologically active points are located. However, due to technical and methodological problems, it was not in the interest of the scientific community, and as a result of solving the problem mentioned in recent history, interest in research in this field has increased.Nerve endings, called biologically active points or acupuncture points, are widely used in alternative medicine. The first step in electrostimulation of acupuncture points is the localization of the point. Localization is based on measuring the electrical conductivity of acupuncture points. The article discusses the virtual design of the measuring device, which is expected to be integrated with electrostimulators. As a result of the simulation, measurements were made and the accuracy class of the device was determined. Thus, it is possible to accurately measure electrical conductivity in biological objects through this device.The proposed device is designed on the basis of a modern element base. The basic element of the device is Arduino. A voltage divider scheme was used to determine the electrical conductivity of Arduino-based biologically active points. The purpose of using a voltage divider circuit is to protect the Arduino's analog input from overvoltage. Based on the measurements, the accuracy class of the proposed device was determined. As a result of the simulations, it was determined that the absolute error of the device is 0.463056, the relative error is 0.005742, and the accuracy class is 0.0463056.