[sensORder Dataset] Taxonomy and Real-Time Classification of Artifacts during Biosignal Acquisition: A Starter Study and Dataset of ECG
Date:2025-05-17 Hits:
Impact Factor:4.3
DOI Number:10.1109/JSEN.2024.3356651
Affiliation of Author(s):University of Bremen; Nanjing University of Information Science and Technology
Journal:IEEE Sensors Journal
Place of Publication:UNITED STATES
Key Words:artifact; biosignal; electrocardiogram; ECG; electrocardiography; pattern recognition; real-time system; signal quality
Abstract:This article investigates electrocardiogram (ECG) acquisition artifacts often occurring in experiments due to human negligence or environmental influences, such as electrode detachment, misuse of electrodes, and unanticipated magnetic field interference, which are not easily noticeable by humans or software during acquisition. Such artifacts usually result in useless and irreparable signals; therefore, it would be a great help to research if the problems are detected during the acquisition process to alert experimenters instantly. We put forward a taxonomy of real-time artifacts during ECG acquisition, provide the simulation methods of each category, collect and share a 10-subject data corpus, and investigate machine learning (ML) solutions with a proposal of appropriate handcrafted features that reach an offline recognition rate of 90.89% in a five-best-output person-independent (PI) leave-one-out cross-validation (LOOCV). We also preliminarily validate the real-time applicability of our approach.
Note:ESI Hot Paper (top 0.1%) and Highly-Cited Paper (top 1%).
Dataset: https://www.uni-bremen.de/en/csl/research/sensorder-artifact-classification-during-biosignal-acquisition.
All the Authors:Hui Liu*, Shiyao Zhang, Hugo Gamboa, Tingting Xue, Congcong Zhou, Tanja Schultz
Indexed by:Journal paper
Discipline:Engineering
Document Type:J
Volume:24
Issue:6
Page Number:9162-9171
ISSN No.:1530-437X
Translation or Not:no
Date of Publication:2024-01-16
Included Journals:SCI
Publication links:https://ieeexplore.ieee.org/document/10415350