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      Exploring physiological stress response evoked by passive translational acceleration in healthy adults: a pilot study utilizing electrodermal activity and heart rate variability measurements

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          Abstract

          Passive translational acceleration (PTA) has been demonstrated to induce the stress response and regulation of autonomic balance in healthy individuals. Electrodermal activity (EDA) and heart rate variability (HRV) measurements are reliable indicators of the autonomic nervous system (ANS) and can be used to assess stress levels. The objective of this study was to investigate the potential of combining EDA and HRV measurements in assessing the physiological stress response induced by PTA. Fourteen healthy subjects were randomly assigned to two groups of equal size. The experimental group underwent five trials of elevator rides, while the control group received a sham treatment. EDA and HRV indices were obtained via ultra-short-term analysis and compared between the two groups to track changes in the ANS. In addition, the complexity of the EDA time series was compared between the 4 s before and the 2–6 s after the onset of PTA to assess changes in the subjects' stress levels in the experimental group. The results revealed a significant increase in the skin conductance response (SCR) frequency and a decrease in the root mean square of successive differences (RMSSD) and high frequency (HF) components of HRV. In terms of stress assessment, the results showed an increase in the complexity of the EDA time series 2–6 s after the onset of PTA. These results indicate an elevation in sympathetic tone when healthy subjects were exposed to a translational transport scenario. Furthermore, evidence was provided for the ability of EDA complexity to differentiate stress states in individual trials of translational acceleration.

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          A circumplex model of affect.

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            A Review of Emotion Recognition Using Physiological Signals

            Emotion recognition based on physiological signals has been a hot topic and applied in many areas such as safe driving, health care and social security. In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods, the published emotional physiological datasets, features, classifiers, and the whole framework for emotion recognition based on the physiological signals. A summary and comparation among the recent studies has been conducted, which reveals the current existing problems and the future work has been discussed.
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              Publication Recommendations for Electrodermal Measurements

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                Author and article information

                Contributors
                954313195@qq.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 May 2024
                18 May 2024
                2024
                : 14
                : 11349
                Affiliations
                [1 ]College of Metrology and Measurement Engineering, China Jiliang University, ( https://ror.org/05v1y0t93) Hangzhou, Zhejiang China
                [2 ]GRID grid.411485.d, ISNI 0000 0004 1755 1108, College of Mechanical and Electrical Engineering, , China Jiliang University, ; Hangzhou, Zhejiang China
                [3 ]Xizi Elevator Co., Ltd., Hangzhou, Zhejiang China
                [4 ]GRID grid.469325.f, ISNI 0000 0004 1761 325X, Zhejiang University of Technology, ; Hangzhou, Zhejiang China
                Article
                61656
                10.1038/s41598-024-61656-5
                11102551
                38762532
                1750a35b-b32c-48ff-a6ec-63e29861258e
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 February 2024
                : 8 May 2024
                Funding
                Funded by: the "Pioneer" and "Leading Goose" R&D Program of Zhejiang Province China
                Award ID: 2023C01022
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                translational acceleration,heart rate variability,electrodermal activity,acceleration perception,stress,biomedical engineering,perception,autonomic nervous system,stress and resilience

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