Toward robust AI-based ECG R-peak detection for real-time physiological monitoring in operational environments.

Boström M, Jonsäll E, Allenmark F, Amoignon O, Persson E, Elcadi GH

Open source

DOI: 10.3389/fpsyg.2026.1892662
Published: 2026
Container: Frontiers in psychology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fpsyg.2026.1892662,
  title = {Toward robust AI-based ECG R-peak detection for real-time physiological monitoring in operational environments.},
  author = {Boström M and Jonsäll E and Allenmark F and Amoignon O and Persson E and Elcadi GH},
  year = {2026},
  journal = {Frontiers in psychology},
  doi = {10.3389/fpsyg.2026.1892662},
  url = {https://doi.org/10.3389/fpsyg.2026.1892662}
}

RIS

TY  - JOUR
TI  - Toward robust AI-based ECG R-peak detection for real-time physiological monitoring in operational environments.
AU  - Boström M
AU  - Jonsäll E
AU  - Allenmark F
AU  - Amoignon O
AU  - Persson E
AU  - Elcadi GH
PY  - 2026
JO  - Frontiers in psychology
DO  - 10.3389/fpsyg.2026.1892662
UR  - https://doi.org/10.3389/fpsyg.2026.1892662
ER  -

APA

M, B., E, J., F, A., O, A., E, P., & GH, E. (2026). Toward robust AI-based ECG R-peak detection for real-time physiological monitoring in operational environments.. Frontiers in psychology. https://doi.org/10.3389/fpsyg.2026.1892662

Source records

pubmed · retrieved 2026-09-25T11:13:05.148Z
europe-pmc · retrieved 2026-09-25T11:13:05.145Z
doaj · retrieved 2026-09-25T11:13:05.132Z