Biofeedback of states of anxiety through automated detection processes using different technologies

  • Authors

    • Benjamin Maraza Quispe Teaching researcher
    • Luis Alfaro Casas Teaching researcher
    • Olga Melina Alejandro Oviedo Teaching researcher
    • Crisia Vivanco Chávez Teaching researcher
    • Yony Jiménez Villegas Teaching researcher
    • Simón Choquehuayta Palomino Teaching researcher
    • José Herrera Quispe Teaching researcher
    • Nicolas Caytuiro Silva Teaching researcher
  • Anxiety, Anxiety and Depression Test, Biofeedback, Microcontrollers, Neural Networks.
  • In this work, a system model is proposed, which applies biofeedback techniques, through automatic detection procedures, using different technologies, constituted by a system formed by a prototype based on a set of "Arduino" microcontrollers, which monitor the levels of anxiety, using as a measurement technique, the Body Temperature Variables, and the Galvanic Skin Response. The measurement is validated by comparing Zung's self-report and depressive symptoms scale, which offers diagnostic approaches, which comprise most of the characteristics of anxiety or depression, involving affective, physiological and psychological aspects, with a range of punctuations. From 20 to 80 points. The presence of anxiety or depression is assumed with scores higher than 50%; controlled in an environment of the Android operating system, which interprets the data obtained, analyzing and sending them from an "Arduino Uno" plate, to display them through an application (App), using the App Inventor platform, which receives the signals from anxiety levels, using radiofrequency waves with Bluetooth technology, in order to provide self-management treatment of timely and effective anxiety levels to achieve the improvement of quality of life. This research work is motivated, because the anxiety sustained for long periods of time, can be a risk factor for diseases, lack of productivity and work absences, therefore, it can be considered as a factor that causes significant economic losses. The results obtained were satisfactory, since it was possible to considerably reduce the levels of anxiety, through the application of the techniques of the model that applies biofeedback techniques.



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  • How to Cite

    Maraza Quispe, B., Alfaro Casas, L., Melina Alejandro Oviedo, O., Chávez, C. V., Villegas, Y. J., Choquehuayta Palomino, S., Herrera Quispe, J., & Caytuiro Silva, N. (2018). Biofeedback of states of anxiety through automated detection processes using different technologies. International Journal of Engineering & Technology, 7(3), 1609-1614.