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research-article

Classification of Acute Stress-Induced Response Patterns

Authors:

Bjoern M. Eskofier,

Nicolas RohlederAuthors Info & Claims

PervasiveHealth'19: Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare

Pages 366 - 370

https://doi.org/10.1145/3329189.3329231

Published: 20 May 2019 Publication History

Abstract

Modern machine learning techniques enable new possibilities for the analysis of psychological data. In the field of health psychology, it is of interest to explore the biological processes triggered by acute stress. This work introduces a method to automatically classify individuals into distinct stress responder groups based on these biological processes. Two important stress-sensitive markers were used: Salivary cortisol and Interleukin-6 (IL-6) in blood plasma. Controlled stress was induced using the Trier Social Stress Test on two consecutive days. Results show that Support Vector Machines performed best on the given dataset. We distinguished four different cortisol and three different IL-6 responder types with high mean accuracies (92.2 % ± 9.7 % and 91.2 % ± 6.3 %, respectively). Classification results were mainly limited by class imbalances and high intra-class standard deviations. Whereas promising as a first application of machine learning on such datasets, generalizability and real-world applicability of our results need to be proven by further research.

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Christine M. McInnis, Myriam V. Thoma, Danielle Gianferante, Luke Hanlin, Xuejie Chen, Juliana G. Breines, Suzi Hong, and Nicolas Rohleder. 2014. Measures of adiposity predict interleukin-6 responses to repeated psychosocial stress. Brain, Behavior, and Immunity 42 (2014), 33--40.

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Cited By

Vorberg LPflueger SRicher RJaeger KKüderle ARohleder NEskofier B(2023)Prediction of Stress Coping Capabilities from Nightly Heart Rate Patterns using Machine Learning2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)10.1109/BHI58575.2023.10313401(1-4)Online publication date: 15-Oct-2023
https://doi.org/10.1109/BHI58575.2023.10313401
Oppelt MFoltyn ADeuschel JLang NHolzer NEskofier BYang S(2022)ADABase: A Multimodal Dataset for Cognitive Load EstimationSensors10.3390/s2301034023:1(340)Online publication date: 28-Dec-2022
https://doi.org/10.3390/s23010340
Mueller VRicher RHenrich LBerger LGelardi AJaeger KEskofier BRohleder N(2022)The Stroop Competition: A Social-Evaluative Stroop Test for Acute Stress Induction2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)10.1109/BHI56158.2022.9926835(1-4)Online publication date: 27-Sep-2022
https://doi.org/10.1109/BHI56158.2022.9926835
Show More Cited By

Index Terms

Classification of Acute Stress-Induced Response Patterns
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health informatics
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning

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Published In

cover image ACM Other conferences

PervasiveHealth'19: Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare

May 2019

475 pages

ISBN:9781450361262

DOI:10.1145/3329189

General Chairs:
Oscar Mayora
Fondazione Bruno Kessler, Italy
,
Stefano Forti
Fondazione Bruno Kessler, Italy
,
Program Chairs:
Jochen Meyer,
Lena Mamykina

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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EAI: The European Alliance for Innovation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 May 2019

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Deutsche Forschungsgemeinschaft

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PervasiveHealth'19

PervasiveHealth'19: The 13th International Conference on Pervasive Computing Technologies for Healthcare

May 20 - 23, 2019

Trento, Italy

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Overall Acceptance Rate 55 of 116 submissions, 47%

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Cited By

Vorberg LPflueger SRicher RJaeger KKüderle ARohleder NEskofier B(2023)Prediction of Stress Coping Capabilities from Nightly Heart Rate Patterns using Machine Learning2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)10.1109/BHI58575.2023.10313401(1-4)Online publication date: 15-Oct-2023
https://doi.org/10.1109/BHI58575.2023.10313401
Oppelt MFoltyn ADeuschel JLang NHolzer NEskofier BYang S(2022)ADABase: A Multimodal Dataset for Cognitive Load EstimationSensors10.3390/s2301034023:1(340)Online publication date: 28-Dec-2022
https://doi.org/10.3390/s23010340
Mueller VRicher RHenrich LBerger LGelardi AJaeger KEskofier BRohleder N(2022)The Stroop Competition: A Social-Evaluative Stroop Test for Acute Stress Induction2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)10.1109/BHI56158.2022.9926835(1-4)Online publication date: 27-Sep-2022
https://doi.org/10.1109/BHI56158.2022.9926835
Ullrich MKuderle AReggi LCereatti AEskofier BKluge F(2021)Machine learning-based distinction of left and right foot contacts in lower back inertial sensor gait data2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)10.1109/EMBC46164.2021.9630653(5958-5961)Online publication date: 1-Nov-2021
https://doi.org/10.1109/EMBC46164.2021.9630653
Richer RKuderle ADorr JRohleder NEskofier B(2021)Assessing the Influence of the Inner Clock on the Cortisol Awakening Response and Pre-Awakening Movement2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)10.1109/BHI50953.2021.9508529(1-4)Online publication date: 27-Jul-2021
https://doi.org/10.1109/BHI50953.2021.9508529

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