Article
Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables
Author/s | Castro García, Juan Antonio
![]() ![]() ![]() ![]() ![]() ![]() ![]() Molina Cantero, Alberto Jesús ![]() ![]() ![]() ![]() ![]() ![]() ![]() Gómez González, Isabel María ![]() ![]() ![]() ![]() ![]() ![]() ![]() Lafuente Arroyo, Sergio Merino Monge, Manuel ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Department | Universidad de Sevilla. Departamento de Tecnología Electrónica |
Publication Date | 2022-01-02 |
Deposit Date | 2022-02-07 |
Published in |
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Abstract | Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive ... Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest |
Funding agencies | Ministerio de Ciencia, Innovación y Universidades (MICINN). España Agencia Estatal de Investigación. España Ministerio de Ciencia e Innovación (MICIN). España |
Project ID. | PID2019-104323RB-C32
![]() 10.13039/501100011033 ![]() PID2019-104323RB-C31 ![]() |
Citation | Castro García, J.A., Molina Cantero, A.J., Gómez González, I.M., Lafuente Arroyo, S. y Merino Monge, M. (2022). Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables. Electronics, 11 (1) |
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