IDEAS home Printed from
   My bibliography  Save this article

Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices


  • Stephanie Balters

    () (Norwegian University of Science and Technology (NTNU))

  • Martin Steinert

    () (Norwegian University of Science and Technology (NTNU))


Abstract This paper presents the theoretical and practical fundamentals of using physiology sensors to capture human emotion reactivity in a products or systems engineering context. We aim to underline the complexity of regulating (internal and external) effects on the human body and highly individual physiological (emotion) responses and provide a starting point for engineering researchers entering the field. Although great advances have been made in scenarios involving human-machine interactions, the critical elements—the actions and responses of the human—remain far beyond automatic control, because of the irrational behavior of human subjects. These (re)actions, which cannot be satisfactorily modeled, stem mostly from the fact that human behavior is regulated by emotions. The physiological measurement of the latter can thus be a potential door to future advances for the community. In this paper, following a brief overview of the foundations and ongoing discussions in psychology and neuroscience, various emotion-related physiological responses are explained on the basis of a systematic review of the autonomic nervous system and its regulation of the human body. Based on sympathetic and parasympathetic nervous system responses, various sensor measurements that are relevant in an engineering context, such as electrocardiography, electroencephalography, electromyography, pulse oximetry, blood pressure measurements, respiratory transducer, body temperature measurements, galvanic skin response measurements, and others, are explained. After providing an overview of ongoing engineering and human-computer interaction projects, we discuss engineering-specific challenges and experiment setups in terms of their usability and appropriateness for data analysis. We identify current limitations associated with the use of physiology sensors and discuss developments in this area, such as software-based facial affect coding and near-infrared spectroscopy. The key to truly understanding user experience and designing systems and products that integrate emotional states dynamically lies in understanding and measuring physiology. This paper serves as a call for the advancement of affective engineering research.

Suggested Citation

  • Stephanie Balters & Martin Steinert, 0. "Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-23.
  • Handle: RePEc:spr:joinma:v::y::i::d:10.1007_s10845-015-1145-2
    DOI: 10.1007/s10845-015-1145-2

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. XuYi & Bas van Leeuwen & Jan Luiten van Zanden, 2015. "Urbanization in China, ca. 1100–1900," Working Papers 0063, Utrecht University, Centre for Global Economic History.
    2. Lei, Lei, 2015. "A closer look at the diffusion of ChinaGAP," IDE Discussion Papers 501, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    3. Jean-Pierre Laffargue & Eden S. H. Yu, 2015. "The Chinese Savings Puzzles," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01450935, HAL.
    4. Cheng, Yahao & Gao, Zhifeng & Seale, James L. Jr., 2015. "Changing Structure of China's Meat Imports," 2015 Conference, August 9-14, 2015, Milan, Italy 212717, International Association of Agricultural Economists.
    5. Oecd, 2015. "Teaching beliefs and practice," Teaching in Focus 13, OECD Publishing.
    6. Yi Xu & Zhihong Shi & Bas Leeuwen & Yuping Ni & Zipeng Zhang & Ye Ma, 2017. "Chinese National Income, ca. 1661–1933," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 57(3), pages 368-393, November.
    7. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    8. Oecd, 2015. "Teaching with technology," Teaching in Focus 12, OECD Publishing.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v::y::i::d:10.1007_s10845-015-1145-2. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Mallaigh Nolan). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.