Universität zu Köln

Jacobsen, Malte, Dembek, Till A., Ziakos, Athanasios-Panagiotis, Gholamipoor, Rahil, Kobbe, Guido, Kollmann, Markus, Blum, Christopher, Mueller-Wieland, Dirk, Napp, Andreas, Heinemann, Lutz, Deubner, Nikolas, Marx, Nikolaus, Isenmann, Stefan and Seyfarth, Melchior (2020). Reliable Detection of Atrial Fibrillation with a Medical Wearable during Inpatient Conditions. Sensors, 20 (19). BASEL: MDPI. ISSN 1424-8220

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Abstract

Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study aims to evaluate the sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Jacobsen, Malte UNSPECIFIED UNSPECIFIED UNSPECIFIED Dembek, Till A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Ziakos, Athanasios-Panagiotis UNSPECIFIED UNSPECIFIED UNSPECIFIED Gholamipoor, Rahil UNSPECIFIED UNSPECIFIED UNSPECIFIED Kobbe, Guido UNSPECIFIED UNSPECIFIED UNSPECIFIED Kollmann, Markus UNSPECIFIED UNSPECIFIED UNSPECIFIED Blum, Christopher UNSPECIFIED UNSPECIFIED UNSPECIFIED Mueller-Wieland, Dirk UNSPECIFIED UNSPECIFIED UNSPECIFIED Napp, Andreas UNSPECIFIED UNSPECIFIED UNSPECIFIED Heinemann, Lutz UNSPECIFIED UNSPECIFIED UNSPECIFIED Deubner, Nikolas UNSPECIFIED UNSPECIFIED UNSPECIFIED Marx, Nikolaus UNSPECIFIED UNSPECIFIED UNSPECIFIED Isenmann, Stefan UNSPECIFIED UNSPECIFIED UNSPECIFIED Seyfarth, Melchior UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-316337
DOI:	10.3390/s20195517
Journal or Publication Title:	Sensors
Volume:	20
Number:	19
Date:	2020
Publisher:	MDPI
Place of Publication:	BASEL
ISSN:	1424-8220
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language HEART-RATE Multiple languages Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/31633