Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24237, first published .
Assessing Children’s Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach

Assessing Children’s Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach

Assessing Children’s Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach

Journals

  1. Nucci L, Miraglia F, Alù F, Pappalettera C, Judica E, Manenti R, Rossini P, Vecchio F. Reaction time and cognitive strategies: The role of education in task performance. Learning and Motivation 2023;82:101884 View
  2. Huang Y, Xie C, Chou C, Jin Y, Li W, Wang M, Lu Y, Liu Z. Subtyping intractable functional constipation in children using clinical and laboratory data in a classification model. Frontiers in Pediatrics 2023;11 View
  3. Bošnjaković N, Đurđević Babić I. Systematic Review on Educational Data Mining in Educational Gamification. Technology, Knowledge and Learning 2023 View
  4. Chun S, Jang S, Kim J, Ko C, Lee J, Hong J, Park Y. Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks–Based Deep Learning: Development and Validation Study. JMIR Formative Research 2024;8:e51996 View
  5. Gkintoni E, Vantaraki F, Skoulidi C, Anastassopoulos P, Vantarakis A. Promoting Physical and Mental Health among Children and Adolescents via Gamification—A Conceptual Systematic Review. Behavioral Sciences 2024;14(2):102 View
  6. Bisi M, Stagni R. Sensor-Based Quantitative Assessment of Children’s Fine Motor Competence: An Instrumented Version of the Placing Bricks Test. Sensors 2024;24(7):2192 View