| Verlagslink DOI: | 10.1145/3583133.3590752 | Titel: | EA-based smartwatch application for training and assistance in cardiopulmonary resuscitation | Sprache: | Englisch | Autorenschaft: | Lins, Christian  Berwald, Erik Klausen, Andreas Hein, Andreas Fudickar, Sebastian |
Schlagwörter: | Computing methodologies; Genetic algorithms; Applied computing; Health informatics | Erscheinungsdatum: | 24-Jul-2023 | Verlag: | Association for Computing Machinery | Buchtitel: | Proceedings of the Companion Conference on Genetic and Evolutionary Computation | Teil der Schriftenreihe: | ACM Conferences | Anfangsseite: | 735 | Endseite: | 738 | Konferenz: | Companion Conference on Genetic and Evolutionary Computation 2023 | Zusammenfassung: | Cardiopulmonary resuscitation (CPR) is critical to the prevention of death from cardiac arrest. Smartwatches can help first responders perform CPR correctly by collecting real-time acceleration data to determine compression rate and depth. We present an approach for a smartwatch application that uses motion data from the inertial sensors and an evolutionary algorithm ((μ + λ)-ES) to compute compression depth and frequency and provide corrective feedback. The application was optimized for out-of-hospital CPR and evaluated in a pilot study using a CPR training manikin as a reference system and an existing smartphone app for comparison. |
URI: | http://hdl.handle.net/20.500.12738/14370 | ISBN: | 9798400701207 | Begutachtungsstatus: | Diese Version hat ein Peer-Review-Verfahren durchlaufen (Peer Review) | Einrichtung: | Department Informatik Fakultät Technik und Informatik |
Dokumenttyp: | Konferenzveröffentlichung |
| Enthalten in den Sammlungen: | Publications without full text |
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