Adaptive Gait Generation

Adaptive Gait Generation is a gait generation method that dynamically adjusts locomotion patterns in response to real-time environmental or physiological variations, thereby distinguishing itself from static or pre-programmed gait models through its capacity for online modification and context-aware adaptation.

44

Publications

1.4K

Citations

136

Authors

67

Institutions

Publications per year

2017–2026

10

Authors

136

  1. JG
    John G. Buckley

    University of Bradford, United Kingdom

    4 publications · 143 citations

    4

    h-index

  2. WR
    William R. Young

    Brunel University of London, United Kingdom

    3 publications · 189 citations

    3

    h-index

  3. DB
    David B. Elliott

    University of Bradford, United Kingdom

    3 publications · 131 citations

    3

    h-index

  4. MA
    Matthew A. Timmis

    Anglia Ruskin University, United Kingdom

    2 publications · 82 citations

    2

    h-index

  5. DO
    Dai Owaki

    Tohoku University, Japan

    2 publications · 45 citations

    2

    h-index

1–5 of 136

Venues

  1. Gait & Posture

    4 publications · 142 citations

    4

    h-index

  2. Optometry and Vision Science

    2 publications · 92 citations

    2

    h-index

  3. Experimental Brain Research

    2 publications · 98 citations

    2

    h-index

  4. Robotica

    2 publications · 31 citations

    2

    h-index

  5. Journal of Intelligent & Robotic Systems

    2 publications · 29 citations

    2

    h-index

1–5