Enhancing Cardiopulmonary Resuscitation Quality Using a Smartwatch: Neural Network Approach for Algorithm Development and Validation.

Journal: JMIR mHealth and uHealth
PMID: 40324161

Abstract

BACKGROUND: Sudden cardiac arrest is a major cause of mortality, necessitating immediate and high-quality cardiopulmonary resuscitation (CPR) for improved survival rates. High-quality CPR is defined by chest compressions at a rate of 100-120 per minute and a depth of 50-60 mm. Monitoring and maintaining these parameters in real time during emergencies remain a challenge.

Authors

  • Gaurav Rao
    Department of Mathematics and Computing, Faculty of Science, Saint Mary's University, Halifax, NS, Canada.
  • David W Savage
    Emergency Medicine, Faculty of Family and Emergency Medicine, NOSM University, Thunder Bay, ON, Canada.
  • Gabrielle Erickson
    Emergency Medicine, Faculty of Family and Emergency Medicine, NOSM University, Thunder Bay, ON, Canada.
  • Nathan Kyryluk
    Emergency Medicine, Faculty of Family and Emergency Medicine, NOSM University, Thunder Bay, ON, Canada.
  • Pawan Lingras
    Department of Mathematics and Computing, Faculty of Science, Saint Mary's University, Halifax, NS, Canada.
  • Vijay Mago
    Department of Computer Science, Lakehead University, 955 Oliver Road, Thunder Bay, P7B 5E1, Canada. vmago@lakeheadu.ca.

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