Intention Detection

Intention Detection is a computational framework within rehabilitation robotics that identifies the user's desired movement or action by distinguishing neural, muscular, or behavioral signals indicative of motor intent from background noise or extraneous inputs.

384

Publications

19.1K

Citations

1.2K

Authors

476

Institutions

Publications per year

2017–2026

212

Authors

1.2K

  1. CB
    Cristina Becchio

    University of Turin, Italy

    8 publications · 467 citations

    8

    h-index

  2. JD
    José del R. Millán

    École Polytechnique Fédérale de Lausanne, Switzerland

    8 publications · 764 citations

    8

    h-index

  3. AC
    Andrea Cavallo

    University of Turin, Italy

    7 publications · 419 citations

    7

    h-index

  4. KD
    Konrad Doll

    Aschaffenburg University of Applied Sciences, Germany

    6 publications · 252 citations

    6

    h-index

  5. IK
    Imran Khan Niazi

    Aalborg University, Denmark

    6 publications · 465 citations

    6

    h-index

1–5 of 1.2K

Venues

  1. Sensors

    14 publications · 369 citations

    14

    h-index

  2. IEEE Access

    10 publications · 365 citations

    11

    h-index

  3. 10

    h-index

  4. Frontiers in Neurorobotics

    6 publications · 210 citations

    6

    h-index

  5. Journal of Neural Engineering

    6 publications · 565 citations

    6

    h-index

1–5