EA-based smartwatch application for training and assistance in cardiopulmonary resuscitation

Lins, Christian; Berwald, Erik; Klausen, Andreas; Hein, Andreas; Fudickar, Sebastian

doi:10.1145/3583133.3590752

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