The practicality of modern wearable electronic devices is determined by the autonomy of their power supply sources. The concept of collecting and converting auxiliary, background energy from energy sources of the environment offers various options for solving the problem of such energy dependence. However, at the moment, the problem does not have a complex solution and is actually being transferred to new planes. One of them: how to evaluate the feasibility and effectiveness of the applying and usage of such low-power and non-permanent energy sources. In the article it is discussed and substantiated the possibility of using electronic-mechanical microsensors, which are available in any smartphone, to study the potential energy effect from the use of background energy sources. The purpose of the article is to tell everyone who are interested in modern technologies of collecting and converting various types of environmental energy about the possibility of using a widely available and budgetary smartphone with the Android operating system to study the individual characteristics of human movement as a source of auxiliary, background energy. In addition, it is said about the usage of collected and accumulated energy, a review of technologies and a comparison of the energy density of different methods of energy collection were made. The results of architectural modeling and an example of a prototype software for the study of mechanical energy sources are given. To obtain the result, an application has been developed that reads data from accelerometer sensors with a given frequency, designed to study and evaluate the possibility of using the mechanical energy of human movement as a source of electrical energy to power autonomous electronic devices. Despite the work has been done, which was aimed at achieving this goal, the continuation of research requires expanding the capabilities of the developed application on the one hand by sharing various sensors for a complex study of the possibility of obtaining human interaction energy with the environment and applying modern methods and digital filtering algorithms to ensure accuracy and reliability of measurements