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A Comprehensive Survey on Multimodal Medical Signals Fusion for Smart Healthcare Systems
Information Fusion (2021)
  • Ghulam Muhammad, King Saud University
  • Fatima Alshehri, King Saud University
  • Fakhri Karray, University of Waterloo
  • Dr. Fakhreddine (Fakhri) Karray, Mohamed bin Zayed University of Artificial Intelligence
  • Abdulmotaleb El Saddik, University of Ottawa
  • Mansour Alsulaiman, King Saud University
  • Tiago H. Falk, Institut National de la Recherche Scientifique
Smart healthcare is a framework that utilizes technologies such as wearable devices, the Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless communication technology to seamlessly access health records, link individuals, resources, and organizations, and then effectively handle and react to health environment demands intelligently. One of the main ingredients of smart healthcare is medical sensors or IoMT. Due to the complex nature of diseases, in many cases, there is a need for multimodal medical signals for their diagnoses. While using multimodal signals, the most important issue is how to fuse them – an area of burgeoning interest within the research community. This paper presents a comprehensive survey of multimodal medical signals fusion schemes that have been proposed for smart healthcare applications. Research works included in major repositories, such as IEEE Xplore, Science Direct, Springer Link, and ACM digital library have been surveyed to address several related research questions. Focus is placed on recent developments, thus only works published between 2014-2020 are considered. Finally, key research challenges and possible future directions are also provided.
  • Internet of medical things (IoMT),
  • Medical images,
  • Signals fusion,
  • Smart healthcare
Publication Date
December 1, 2021
Citation Information
Ghulam Muhammad, Fatima Alshehri, Fakhri Karray, Fakhreddine (Fakhri) Karray, et al.. "A Comprehensive Survey on Multimodal Medical Signals Fusion for Smart Healthcare Systems" Information Fusion Vol. 76 (2021) p. 355 - 375
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