Stress data analysis with EEG using machine learning

• Grant number: 17/12213-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2018
• End date: January 31, 2019
• Field of knowledge: Engineering - Biomedical Engineering - Bioengineering
• Principal Investigator: Carlos Dias Maciel
• Grantee: Rafael Augusto Caracciolo Arone
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The electroencephalogram is a device that allows obtaining brain signals of the specific skull region, one of these informations that can be taken from it is the stress level of anyone. in that can be done by signal filtrage and clustering with machine learning algorithms, more specifically using Neural Networks with multilayer Perceptrons. Besides, this research uses the Montreal Imaging Stress Task for create in one person a situation that can get signal with can get the signals, and the created algorithm, be capable of measure various stress levels. (AU)