Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • News & Views
  • Published:

Bioelectronics

Stress monitoring with wearable technology and AI

Nature Electronics volume 7, pages 98–99 (2024)Cite this article

Subjects

Physicochemical-sensing electronic skins — combined with artificial intelligence — could be used to develop personalized stress management systems.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The future of stress monitoring with wearable technology.

References

  1. Fink, G. in Reference Module in Neuroscience and Biobehavioral Psychology 549–555 (Elsevier, 2017).

  2. Kim, H. G., Cheon, E. J., Bai, D. S., Lee, Y. H. & Koo, B. H. Psychiatry Investig. 15, 235–245 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Ernst, H. et al. PLoS ONE 18, e0294069 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Dalmeida, K. M. & Masala, G. L. Sensors 21, 2873 (2021).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  5. Samson, C. & Koh, A. Front. Bioeng. Biotechnol. 8, 1037 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Torrente-Rodríguez, R. M. et al. Matter 2, 921–937 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ates, H. C. et al. Nat. Rev. Mater. 7, 887–907 (2022).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  8. Mukasa, D. et al. Adv. Mater. 35, 2212161 (2023).

    Article  CAS  Google Scholar 

  9. Xu, C. et al. Nat. Electron. https://doi.org/10.1038/s41928-023-01116-6 (2024).

    Article  Google Scholar 

  10. Ates, H. C. et al. Preprint at medRxiv https://doi.org/10.1101/2023.10.23.23297424 (2023).

Download references

Author information

Authors and Affiliations

  1. FIT Freiburg Centre for Interactive Materials and Bioinspired Technology, University of Freiburg, Freiburg, Germany

    H. Ceren Ates & Can Dincer

  2. Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany

    H. Ceren Ates & Can Dincer

  3. Machine Intelligence in Energy Systems, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Cihan Ates

  4. Center of Health Technologies, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Cihan Ates

Authors
  1. H. Ceren Ates
    View author publications

    Search author on:PubMed Google Scholar

  2. Cihan Ates
    View author publications

    Search author on:PubMed Google Scholar

  3. Can Dincer
    View author publications

    Search author on:PubMed Google Scholar

Corresponding authors

Correspondence to Cihan Ates or Can Dincer.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ates, H.C., Ates, C. & Dincer, C. Stress monitoring with wearable technology and AI. Nat Electron 7, 98–99 (2024). https://doi.org/10.1038/s41928-024-01128-w

Download citation

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41928-024-01128-w

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing