Time Bias Awareness in ECG-Based Multiple Source Data Matching.


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
29 Jun 2022
Historique:
entrez: 1 7 2022
pubmed: 2 7 2022
medline: 6 7 2022
Statut: ppublish

Résumé

For cardiological datasets acquired via different methodologies, ECG signals that are recorded in parallel allow for relatively accurate matching. Some research issues, e.g., the identification of timings of the cardiac cycle in seismocardiography, require higher temporal resolutions. Therefore, we introduce a method derived from a feasibility study to determine deviations and factors influencing the merging of signals simultaneously recorded with different modalities.

Identifiants

pubmed: 35773814
pii: SHTI220668
doi: 10.3233/SHTI220668
doi:

Types de publication

Journal Article

Langues

eng

Pagination

91-94

Auteurs

Urs-Vito Albrecht (UV)

Department of Digital Medicine, Medical Faculty OWL, University of Bielefeld, Germany.

Dennis Lawin (D)

Department of Digital Medicine, Medical Faculty OWL, University of Bielefeld, Germany.
Department of Cardiology and Intensive Care Medicine, University Hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Germany.

Sebastian Kuhn (S)

Department of Digital Medicine, Medical Faculty OWL, University of Bielefeld, Germany.

Ulf Kulau (U)

Smart Sensors Group, Hamburg University of Technology (TUHH), Hamburg, Germany.

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Classifications MeSH