Electromyography-based Gesture Recognition

Electromyography-Based Gesture Recognition is a pattern recognition methodology that decodes neuromuscular activity captured through surface electromyography signals to infer and classify specific hand or arm gestures through machine learning or signal processing techniques.

436

Publications

23.5K

Citations

1.3K

Authors

434

Institutions

Publications per year

2017–2026

340

Authors

1.3K

  1. SB
    Simone Benatti

    University of Bologna, Italy

    14 publications · 877 citations

    13

    h-index

  2. LB
    Luca Benini

    University of Bologna, Italy

    13 publications · 840 citations

    12

    h-index

  3. ME
    Marco E. Benalcázar

    National Polytechnic School, Ecuador

    13 publications · 634 citations

    12

    h-index

  4. AM
    Arash Mohammadi

    Concordia University, Canada

    10 publications · 422 citations

    10

    h-index

  5. ER
    Elahe Rahimian

    Concordia University, Canada

    10 publications · 422 citations

    10

    h-index

1–5 of 1.3K

Venues

  1. Sensors

    37 publications · 2.4K citations

    28

    h-index

  2. Biomedical Signal Processing and Control

    16 publications · 1.2K citations

    16

    h-index

  3. 16

    h-index

  4. IEEE Access

    10 publications · 492 citations

    11

    h-index

  5. 6

    h-index

1–5