Kinematic handwriting features from the sigma-lognormal model predict children's grade, gender, and academic performance on a large Japanese student dataset using regression and random forest models.
PLOS ONE 11(12), e0166868 (Dec 2016)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.HC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Prediction of Grade, Gender, and Academic Performance of Children and Teenagers from Handwriting Using the Sigma-Lognormal Model
Kinematic handwriting features from the sigma-lognormal model predict children's grade, gender, and academic performance on a large Japanese student dataset using regression and random forest models.