Acquisition and Fuzzy Processing of Physiological Signals to Obtain Human Stress Level Using Low Cost Portable Hardware
| Autor: | Javier Arechalde, Raquel Suriá Martínez, Unai Zalabarria, Eloy Irigoyen |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry 020208 electrical & electronic engineering Process (computing) 020206 networking & telecommunications Human stress 02 engineering and technology Fuzzy logic Raspberry pi Upload Software Arduino Embedded system 0202 electrical engineering electronic engineering information engineering Skin conductance business Computer hardware |
| Zdroj: | International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding ISBN: 9783319671796 SOCO-CISIS-ICEUTE |
| DOI: | 10.1007/978-3-319-67180-2_7 |
| Popis: | 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). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|