A transformer-based model predicts lower-limb joint angles and moments from sEMG and IMU signals, but the headline accuracy and benchmark gains are undermined by unit inconsistencies and single-subject testing.
Concurrent assessment of gait kinematics using marker-based and markerless motion capture,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A Novel Transformer-Based Method for Full Lower-Limb Joint Angles and Moments Prediction in Gait Using sEMG and IMU data
A transformer-based model predicts lower-limb joint angles and moments from sEMG and IMU signals, but the headline accuracy and benchmark gains are undermined by unit inconsistencies and single-subject testing.