Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36259
Title: Assessment of heart rate agreement on continuous photoplethysmography monitoring using a smartwatch versus beat-to-beat synchronized ECG monitoring
Authors: GRUWEZ, Henri 
Evens, S.
DESTEGHE, Lien 
DREESEN, Pauline 
KNAEPEN, Lieselotte 
WOUTERS, Femke 
DAUW, Jeroen 
DEFERM, Sebastien 
SMEETS, Christophe 
PISON, Laurent 
Haemers, P.
HEIDBUCHEL, Hein 
VANDERVOORT, Pieter 
Issue Date: 2021
Publisher: OXFORD UNIV PRESS
Source: EUROPEAN HEART JOURNAL, 42 , p. 319 -319
Abstract: Background: In the awakening era of mobile health, wearables equipped with photoplethysmography (PPG) technology to monitor the heart rate (HR) and rhythm are on the rise. Smartwatches and wristbands enable HR monitoring for consumers at massive scale. Unfortunately, once consumers become patients, physicians are limited by insufficient evidence to support the clinical use of PPG based wearables. Accurate identification of heartbeats is the first step in the interpretation of PPG traces and should be validated. Purpose: To assess the agreement between continuous PPG monitoring using a smartwatch and continuous ECG Holter monitoring in the identification of heartbeats and calculation of the HR. Methods: One hundred patients (≥18 years) without a pacemaker-dependent heart rhythm who were referred to a university hospital and a large tertiary hospital for elective 24-hour ECG Holter monitoring were asked to wear a continuous PPG monitoring smartwatch (i.e. Samsung GWA2 or Empatica E4) simultaneously with the 24-hour Holter monitor. All activities of daily life were allowed. The ECG trace and PPG waveform were synchronised and fragmented in one-minute fragments. The one-minute ECG fragments were labelled as AF, non-AF, or insufficient quality based on the routine clinical interpretation (i.e. software + physician overread-ing), and the average HR during each fragment was calculated by Holter algorithm. The PPG fragments were analysed by an artificial intelligence (AI) algorithm (i.e. FibriCheck) that labelled fragments as sufficient or in
Document URI: http://hdl.handle.net/1942/36259
ISSN: 0195-668X
e-ISSN: 1522-9645
ISI #: WOS:000720456900274
Category: M
Type: Journal Contribution
Appears in Collections:Research publications

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