| Autor: |
Patrick Schober, Wisse M.F. van den Beuken, Beat Nideröst, Tom A. Kooy, Steve Thijssen, Carolien S.E. Bulte, Bregje A.A. Huisman, Pieter R. Tuinman, Alexander Nap, Hanno L. Tan, Stephan A. Loer, Gaby Franschman, Roelof G. Lettinga, Derya Demirtas, Susanne Eberl, Hans van Schuppen, Lothar A. Schwarte |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Resuscitation Plus, Vol 12, Iss , Pp 100324- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2666-5204 |
| DOI: |
10.1016/j.resplu.2022.100324 |
| Popis: |
Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality. Immediate detection and treatment are of paramount importance for survival and good quality of life. The first link in the ‘chain of survival’ after OHCA – the early recognition and alerting of emergency medical services – is at the same time the weakest link as it entirely depends on witnesses. About one half of OHCA cases are unwitnessed, and victims of unwitnessed OHCA have virtually no chance of survival with good neurologic outcome. Also in case of a witnessed cardiac arrest, alerting of emergency medical services is often delayed for several minutes. Therefore, a technological solution to automatically detect cardiac arrests and to instantly trigger an emergency response has the potential to save thousands of lives per year and to greatly improve neurologic recovery and quality of life in survivors.The HEART-SAFE consortium, consisting of two academic centres and three companies in the Netherlands, collaborates to develop and implement a technical solution to reliably detect OHCA based on sensor signals derived from commercially available smartwatches using artificial intelligence. In this manuscript, we describe the rationale, the envisioned solution, as well as a protocol outline of the work packages involved in the development of the technology. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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