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Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment

Wearable sensors are widely used to gather psychophysiological data in the laboratory and real-world applications. However, the accuracy of these devices should be carefully assessed. The study focused on testing the accuracy of the Empatica 4 (E4) wristband for the detection of heart rate variabili...

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Autores principales: Costantini, Simone, Chiappini, Mattia, Malerba, Giorgia, Dei, Carla, Falivene, Anna, Arlati, Sara, Colombo, Vera, Biffi, Emilia, Storm, Fabio Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611310/
https://www.ncbi.nlm.nih.gov/pubmed/37896517
http://dx.doi.org/10.3390/s23208423
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author Costantini, Simone
Chiappini, Mattia
Malerba, Giorgia
Dei, Carla
Falivene, Anna
Arlati, Sara
Colombo, Vera
Biffi, Emilia
Storm, Fabio Alexander
author_facet Costantini, Simone
Chiappini, Mattia
Malerba, Giorgia
Dei, Carla
Falivene, Anna
Arlati, Sara
Colombo, Vera
Biffi, Emilia
Storm, Fabio Alexander
author_sort Costantini, Simone
collection PubMed
description Wearable sensors are widely used to gather psychophysiological data in the laboratory and real-world applications. However, the accuracy of these devices should be carefully assessed. The study focused on testing the accuracy of the Empatica 4 (E4) wristband for the detection of heart rate variability (HRV) and electrodermal activity (EDA) metrics in stress-inducing conditions and growing-risk driving scenarios. Fourteen healthy subjects were recruited for the experimental campaign, where HRV and EDA were recorded over six experimental conditions (Baseline, Video Clip, Scream, No-Risk Driving, Low-Risk Driving, and High-Risk Driving) and by means of two measurement systems: the E4 device and a gold standard system. The overall quality of the E4 data was investigated; agreement and reliability were assessed by performing a Bland–Altman analysis and by computing the Spearman’s correlation coefficient. HRV time-domain parameters reported high reliability levels in Baseline (r > 0.72), Video Clip (r > 0.71), and No-Risk Driving (r > 0.67), while HRV frequency domain parameters were sufficient in Baseline (r > 0.58), Video Clip (r > 0.59), No-Risk (r > 0.51), and Low-Risk Driving (r > 0.52). As for the EDA parameters, no correlation was found. Further studies could enhance the HRV and EDA quality through further optimizations of the acquisition protocol and improvement of the processing algorithms.
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spelling pubmed-106113102023-10-28 Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment Costantini, Simone Chiappini, Mattia Malerba, Giorgia Dei, Carla Falivene, Anna Arlati, Sara Colombo, Vera Biffi, Emilia Storm, Fabio Alexander Sensors (Basel) Article Wearable sensors are widely used to gather psychophysiological data in the laboratory and real-world applications. However, the accuracy of these devices should be carefully assessed. The study focused on testing the accuracy of the Empatica 4 (E4) wristband for the detection of heart rate variability (HRV) and electrodermal activity (EDA) metrics in stress-inducing conditions and growing-risk driving scenarios. Fourteen healthy subjects were recruited for the experimental campaign, where HRV and EDA were recorded over six experimental conditions (Baseline, Video Clip, Scream, No-Risk Driving, Low-Risk Driving, and High-Risk Driving) and by means of two measurement systems: the E4 device and a gold standard system. The overall quality of the E4 data was investigated; agreement and reliability were assessed by performing a Bland–Altman analysis and by computing the Spearman’s correlation coefficient. HRV time-domain parameters reported high reliability levels in Baseline (r > 0.72), Video Clip (r > 0.71), and No-Risk Driving (r > 0.67), while HRV frequency domain parameters were sufficient in Baseline (r > 0.58), Video Clip (r > 0.59), No-Risk (r > 0.51), and Low-Risk Driving (r > 0.52). As for the EDA parameters, no correlation was found. Further studies could enhance the HRV and EDA quality through further optimizations of the acquisition protocol and improvement of the processing algorithms. MDPI 2023-10-12 /pmc/articles/PMC10611310/ /pubmed/37896517 http://dx.doi.org/10.3390/s23208423 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Costantini, Simone
Chiappini, Mattia
Malerba, Giorgia
Dei, Carla
Falivene, Anna
Arlati, Sara
Colombo, Vera
Biffi, Emilia
Storm, Fabio Alexander
Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title_full Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title_fullStr Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title_full_unstemmed Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title_short Wrist-Worn Sensor Validation for Heart Rate Variability and Electrodermal Activity Detection in a Stressful Driving Environment
title_sort wrist-worn sensor validation for heart rate variability and electrodermal activity detection in a stressful driving environment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611310/
https://www.ncbi.nlm.nih.gov/pubmed/37896517
http://dx.doi.org/10.3390/s23208423
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