Cited by 78Advanced Image Fusion TechniquesEEG and Brain-Computer InterfacesECG Monitoring and Analysis

Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: overview, challenges, and novel orientation

Li, Jingjing, Wang, Qiang·2022·Information Fusion

Integrity signals

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Crossref · 10.1016/j.inffus.2021.10.018

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  • Integrating ECG with other bioelectrical data including phonocardiogram data has enabled improved performance of cardiovascular disease diagnosis.

    “Integrating ECG with other bioelectrical data, including phonocardiogram (PCG) data, has enabled improved performance of cardiovascular disease diagnosis and would be promising for other biomedical applications [107,108].”

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Authors
Li, J., & Wang, Q.
Affiliations
  • Yanshan University (CN)
  • Shandong University of Science and Technology (CN)
Corresponding author
Wang, Qiang
Venue
Information Fusion
Publisher
Elsevier BV
Published
2022-03
Volume
79
Pages
229-247
ISSN
1566-2535 (ISSN-L)
OpenAlex
W3213061128
Cited by
77
References
0
Citations by year
2026: 10 · 2025: 19 · 2024: 20 · 2023: 18 · 2022: 10
FWCI
5.39
Type
journal article
Language
en
Open access
closed
Locations
Information Fusion (publishedVersion)
Topics
  • Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
Keywords
bioelectric signals, biometrics, fusion algorithm, fusion strategies

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