Acquisition and fuzzy processing of physiological signals to obtain human stress level using low cost portable hardware

1Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

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).

Cite

CITATION STYLE

APA

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 Advances in Intelligent Systems and Computing (Vol. 649, pp. 68–78). Springer Verlag. https://doi.org/10.1007/978-3-319-67180-2_7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free