Motion Artifact Modeling

Motion Artifact Modeling is a computational framework that characterizes and compensates for distortions in biomedical signals caused by physical movement, distinguishing itself from other signal processing models by specifically addressing motion-induced noise as the primary source of signal degradation.

86

Publications

4.4K

Citations

404

Authors

157

Institutions

Publications per year

2017–2026

29

Authors

404

  1. SA
    Samuel A. Talbot

    Johns Hopkins University, United States

    3 publications · 96 citations

    3

    h-index

  2. WK
    Walter K. Harrison

    University of California San Diego Medical Center, United States

    3 publications · 96 citations

    3

    h-index

  3. US
    Ulugbek S. Kamilov

    Washington University in St. Louis, United States

    2 publications · 57 citations

    2

    h-index

  4. XL
    Xiaohua Li

    Zhejiang University of Technology, China

    2 publications · 50 citations

    2

    h-index

  5. DA
    Daniel A. Low

    University of California, Los Angeles, United States

    2 publications · 79 citations

    2

    h-index

1–5 of 404

Venues

  1. Medical Physics

    7 publications · 163 citations

    7

    h-index

  2. Magnetic Resonance in Medicine

    MRM · 5 publications · 267 citations

    5

    h-index

  3. NeuroImage

    5 publications · 883 citations

    5

    h-index

  4. Physics in Medicine and Biology

    4 publications · 107 citations

    4

    h-index

  5. Biomedical Signal Processing and Control

    3 publications · 77 citations

    3

    h-index

1–5