Electronic Devices for Stress Detection in Academic Contexts during Confinement Because of the COVID-19 Pandemic

Author:

Durán-Acevedo Cristhian ManuelORCID,Carrillo-Gómez Jeniffer Katerine,Albarracín-Rojas Camilo AndrésORCID

Abstract

This article studies the development and implementation of different electronic devices for measuring signals during stress situations, specifically in academic contexts in a student group of the Engineering Department at the University of Pamplona (Colombia). For the research’s development, devices for measuring physiological signals were used through a Galvanic Skin Response (GSR), the electrical response of the heart by using an electrocardiogram (ECG), the electrical activity produced by the upper trapezius muscle (EMG), and the development of an electronic nose system (E-nose) as a pilot study for the detection and identification of the Volatile Organic Compounds profiles emitted by the skin. The data gathering was taken during an online test (during the COVID-19 Pandemic), in which the aim was to measure the student’s stress state and then during the relaxation state after the exam period. Two algorithms were used for the data process, such as Linear Discriminant Analysis and Support Vector Machine through the Python software for the classification and differentiation of the assessment, achieving 100% of classification through GSR, 90% with the E-nose system proposed, 90% with the EMG system, and 88% success by using ECG, respectively.

Funder

Departamento Administrativo de Ciencia, Tecnología e Innovación

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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1. Mental stress recognition based on electrocardiogram;Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023);2023-08-28

2. Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI;Computers, Materials & Continua;2023

3. Student’s Stress Detection in Online Learning During the Outbreak;Computational Methods in Psychiatry;2023

4. Predicting Undergraduates Stress Level Using Eye Tracking;2022 6th SLAAI International Conference on Artificial Intelligence (SLAAI-ICAI);2022-12-01

5. Advances and challenges in the detection of academic stress and anxiety in the classroom: A literature review and recommendations;Education and Information Technologies;2022-09-28

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