Abstract
This work presents a hardware and software solution that implements algorithms based on intelligent computing techniques for estimating the stress level using low cost platforms. These algorithms process the acquired physiological signals directly from the sensors using advanced filtering and processing techniques and algorithms based on fuzzy logic. For this purpose, a hardware configuration based on the Arduino Uno and Raspberry Pi 3 platforms has been chosen. These platforms perform the acquisition, processing and upload of the data to a server via WiFi. In the implementation of the server a configuration based on Linux, Apache, MySQL and PHP (LAMP) has been carried out. The parameters used to estimate the stress level derive from the following physiological signals: the electrocardiogram (ECG) and the galvanic skin response (GSR).
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Acknowledgements
This work comes under the framework of the project IT874-13 granted by the Basque Regional Government. It would not have been possible to perform it without the support of the University of the Basque Country, to which we are deeply grateful.
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Zalabarria, U., Irigoyen, E., Martínez, R., Arechalde, J. (2018). Acquisition and Fuzzy Processing of Physiological Signals to Obtain Human Stress Level Using Low Cost Portable Hardware. In: Pérez García, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. SOCO ICEUTE CISIS 2017 2017 2017. Advances in Intelligent Systems and Computing, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-67180-2_7
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DOI: https://doi.org/10.1007/978-3-319-67180-2_7
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