ArticleResuscitation plus2025
Design of the DETECT project: automated cardiac arrest detection and activation of the emergency medical chain integrated into a wristband.
Article in Resuscitation plus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Automated cardiac arrest detection using wrist-derived photoplethysmography during withdrawal of life-sustaining treatment: a prospective clinical validation study.The Lancet regional health. Europe · 2026Article
- Beyond the algorithm: health technology assessment frameworks for AI in cardiology under the European Union Health Technology Assessment Regulation: a systematic review.Annals of translational medicine · 2026Review
- Latest in Resuscitation Research: Highlights from the 2025 American Heart Association's Resuscitation Science Symposium.Journal of the American Heart Association · 2026Article
- Automated Cardiac Arrest Detection Using Wrist-Worn Photoplethysmography: External Validation in Patients With Induced Shockable Cardiac Arrest (DETECT-1b).Circulation. Arrhythmia and electrophysiology · 2026Article
- A machine learning model to detect falls mimicking cardiac arrest-related collapse based on wrist-derived accelerometry: the DETECT-2 study.European heart journal. Digital health · 2026Article
- Out-of-hospital cardiac arrest detection by a wearable: the first real-life case.Resuscitation plus · 2026Article
- Wolf Creek XVIII Part 8: Wolf Creek Innovator in Cardiac Arrest and Resuscitation Science Award.Resuscitation plus · 2026Article
- A digital witness for cardiac arrest: are wearables ready for real-world use?Resuscitation plus · 2026Article
- Patient and physician perspectives on smartwatch-based out-of-hospital cardiac arrest detection.European heart journal. Digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: While survival rates for witnessed out-of-hospital cardiac arrest have improved, assistance for unwitnessed cases often arrives too late. Automated cardiac arrest detection and alerting through wearable biosensor technology could catalyse early assistance and improve survival. Recently, an algorithm for automated detection of induced cardiac arrest was developed using wrist-derived photoplethysmography (DETECT-1a study). This paper outlines the next steps in the DETECT program, aimed at developing, validating, and preparing for the future implementation of automated cardiac arrest detection technology. Methods: External validation (sensitivity; false positives) of the PPG-algorithm developed in DETECT-1a will be performed in patients with induced shockable cardiac arrest (DETECT-1b; Discussion: The DETECT project aims to develop and validate a wristband-integrated technology for automated cardiac arrest detection and alerting in daily life settings. To support future implementation, early health technology assessment is incorporated from the outset. By providing immediate alerts, this technology has the potential to enhance rescuer response and improve cardiac arrest survival.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.