EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload
<italic>Objective:</italic> The growth of autonomous systems interacting with humans leads to assessing operators' stress and mental workload (MWL), especially in safety-critical situations. Therefore, a system providing information about the psychophysiological workers&#x...
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| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
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| Online Access: | https://ieeexplore.ieee.org/document/10791858/ |
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| author | G. Luzzani I. Buraioli G. Guglieri D. Demarchi |
| author_facet | G. Luzzani I. Buraioli G. Guglieri D. Demarchi |
| author_sort | G. Luzzani |
| collection | DOAJ |
| description | <italic>Objective:</italic> The growth of autonomous systems interacting with humans leads to assessing operators' stress and mental workload (MWL), especially in safety-critical situations. Therefore, a system providing information about the psychophysiological workers' condition is fundamental and still missing. This paper aims to study the statistical relationship between the variation of Photoplethysmogram signal (PPG), Electrodermal Activity (EDA), and skin temperature with respect to stress and MWL levels, assessed through an ad-hoc developed subjective questionnaire. <italic>Results:</italic> 43 features were calculated from these signals during the execution of two cognitive tests and processed through a statistical analysis based on Kruskal-Wallis and Mann-Whitney U tests. This analysis proved that about 50% of them offered statistical evidence in differentiating relaxed and altered emotional conditions. Moreover, fifteen features were found to provide sufficient information to detect at the same time stress and MWL. <italic>Conclusions:</italic> These results demonstrate the feasibility of this approach and push to continue this research about the relationship between physiological signals and the variation of stress and MWL by enhancing the population and considering more biosignals. |
| format | Article |
| id | doaj-art-d3bf06e395614a28968cfbd4b6a5767c |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-d3bf06e395614a28968cfbd4b6a5767c2025-01-21T00:02:38ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762025-01-01624825510.1109/OJEMB.2024.351547310791858EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental WorkloadG. Luzzani0https://orcid.org/0000-0002-6000-7816I. Buraioli1https://orcid.org/0000-0002-5419-7772G. Guglieri2D. Demarchi3https://orcid.org/0000-0001-5374-1679Department of Mechanical, Aerospace Engineer, Politecnico di Torino, Turin, ItalyDepartment of Electronics, Telecommunication, Politecnico di Torino, Turin, ItalyDepartment of Mechanical, Aerospace Engineer, Politecnico di Torino, Turin, ItalyDepartment of Electronics, Telecommunication, Politecnico di Torino, Turin, Italy<italic>Objective:</italic> The growth of autonomous systems interacting with humans leads to assessing operators' stress and mental workload (MWL), especially in safety-critical situations. Therefore, a system providing information about the psychophysiological workers' condition is fundamental and still missing. This paper aims to study the statistical relationship between the variation of Photoplethysmogram signal (PPG), Electrodermal Activity (EDA), and skin temperature with respect to stress and MWL levels, assessed through an ad-hoc developed subjective questionnaire. <italic>Results:</italic> 43 features were calculated from these signals during the execution of two cognitive tests and processed through a statistical analysis based on Kruskal-Wallis and Mann-Whitney U tests. This analysis proved that about 50% of them offered statistical evidence in differentiating relaxed and altered emotional conditions. Moreover, fifteen features were found to provide sufficient information to detect at the same time stress and MWL. <italic>Conclusions:</italic> These results demonstrate the feasibility of this approach and push to continue this research about the relationship between physiological signals and the variation of stress and MWL by enhancing the population and considering more biosignals.https://ieeexplore.ieee.org/document/10791858/Biosignalshuman factorsmental workloadstatistical analysisstress |
| spellingShingle | G. Luzzani I. Buraioli G. Guglieri D. Demarchi EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload IEEE Open Journal of Engineering in Medicine and Biology Biosignals human factors mental workload statistical analysis stress |
| title | EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload |
| title_full | EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload |
| title_fullStr | EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload |
| title_full_unstemmed | EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload |
| title_short | EDA, PPG and Skin Temperature as Predictive Signals for Mental Failure by a Statistical Analysis on Stress and Mental Workload |
| title_sort | eda ppg and skin temperature as predictive signals for mental failure by a statistical analysis on stress and mental workload |
| topic | Biosignals human factors mental workload statistical analysis stress |
| url | https://ieeexplore.ieee.org/document/10791858/ |
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