Clinical validation of five direct-to-consumer smartwatches to detect atrial fibrillation in a real-world cohort of patients

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Clinical validation of five direct-to-consumer smartwatches to detect atrial fibrillation in a real-world cohort of patients

Session: e-Cardiology award session

Topic: Remote Patient Monitoring and Telehealth

Speaker: Associate Professor P. Badertscher (Basel, CH)

Event: EHRA 2022

Congress Presentation

About the speaker

Associate Professor Patrick Badertscher

University Hospital Basel, Basel (Switzerland)

1 presentation

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4 more presentations in this session

The impact of a structured polygraphy screening incorporated in a novel remote mobile health pathway on sleep apnoea prevalence in patients with atrial fibrillation

Speaker: Miss D. Verhaert (Nijmegen, NL)

Classification of organised atrial arrythmias using explainable artificial intelligence

Speaker: Doctor A. Sau (London, GB)

Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals

Speaker: Doctor P. Pantelidis (Athens, GR)

Artificial intelligence algorithms for the recognition of Brugada type 1 pattern on standard 12-leads ECG

Speaker: Mr F. Vozzi (Pisa, IT)

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e-Cardiology award session

Speakers: Associate Professor P. Badertscher, Miss D. Verhaert, Doctor A. Sau, Doctor P. Pantelidis, Mr F. Vozzi

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About the event

EHRA 2022

3 April - 5 April 2022

Sessions Presentations

Congress

Clinical validation of five direct-to-consumer smartwatches to detect atrial fibrillation in a real-world cohort of patients

About the speaker

Associate Professor Patrick Badertscher

4 more presentations in this session

The impact of a structured polygraphy screening incorporated in a novel remote mobile health pathway on sleep apnoea prevalence in patients with atrial fibrillation

Classification of organised atrial arrythmias using explainable artificial intelligence

Optimising and validating deep learning approaches for diagnosing atrial fibrillation from few-lead ambulatory electrocardiogram signals

Artificial intelligence algorithms for the recognition of Brugada type 1 pattern on standard 12-leads ECG

Access the full session

e-Cardiology award session

About the event

EHRA 2022

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