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Continuous mobile health patch monitoring for the algorithm-based detection of atrial fibrillation: Feasibility and diagnostic accuracy study
Onni E Santala;
Jukka A Lipponen;
Helena Jäntti;
Tuomas T Rissanen;
Mika P Tarvainen;
Tomi P Laitinen;
Tiina M Laitinen;
Maaret Castrén;
Eemu-Samuli Väliaho;
Olli A Rantula;
Noora S Naukkarinen;
Juha E K Hartikainen;
Jari Halonen;
Tero J Martikainen
ABSTRACT
Background:
The detection of Atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health technologies (mHealth) could provide a cost-effective and reliable solution for AF-screening. However, many of these techniques have not been clinically validated.
Objective:
The purpose of this study was to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with a mHealth patch device designed for personal well-being.
Methods:
Patients (n=178) with an AF (n=79) or sinus rhythm (SR) (n=99) were recruited from the emergency care department. A single-lead 24-hour ECG-based HRV measurement was recorded with the mHealth patch device and analysed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics.
Results:
Of the HRV data produced by the single-lead mHealth patch 81.5% (3099/3802 h) was interpretable and the subject-based median for interpretable HRV data was 99% (25th percentile=77%; 75th percentile=1.00%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in five patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100% and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6% and 98.0%, respectively.
Conclusions:
24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening. Clinical Trial: ClinicalTrials.gov Identifier: NCT03507335