Publication: Data-driven resuscitation training using pose estimation
Data-driven resuscitation training using pose estimation
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Weiss, K. E., Kolbe, M., Nef, A., Grande, B., Kalirajan, B., Meboldt, M., & Lohmeyer, Q. (2023). Data-driven resuscitation training using pose estimation. Advances in Simulation, 8(1), 12. https://doi.org/10.1186/s41077-023-00251-6
Abstract
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Abstract
Background Cardiopulmonary resuscitation (CPR) training improves CPR skills while heavily relying on feedback. The quality of feedback can vary between experts, indicating a need for data-driven feedback to support experts. The goal of this study was to investigate pose estimation, a motion detection technology, to assess individual and team CPR quality with the arm angle and chest-to-chest distance metrics.
Methods After mandatory basic life support training, 91 healthcare providers perf
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Creators (Authors)
- Weiss, Kerrin E
- Kolbe, Michaela
- Nef, Andrina
- Grande, Bastian
- Kalirajan, Bravin
- Meboldt, Mirko
- Lohmeyer, Quentin
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Citations
Weiss, K. E., Kolbe, M., Nef, A., Grande, B., Kalirajan, B., Meboldt, M., & Lohmeyer, Q. (2023). Data-driven resuscitation training using pose estimation. Advances in Simulation, 8(1), 12. https://doi.org/10.1186/s41077-023-00251-6
