Early and Automated Diagnosis of Dysgraphia Using Machine Learning Approach

Author:

Agarwal Basant,Jain Sonal,Beladiya Kishan,Gupta Yash,Yadav Avijit Singh,Ahuja Neelu Jyothi

Funder

DST

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Reference30 articles.

1. Peverly ST, Garner JK, Vekaria PC. Both handwriting speed and selective attention are important to lecture note-taking. Read Writ. 2014;27(1):1–30.

2. Muktamath Vinutha U, Hegde Priya R, Chand Samreen. Types of specific learning disability.

3. Rocha Cabrero F, De Jesus O. Dysgraphia. 2022 Sep 30. In: StatPearls. Treasure Island (FL): StatPearls Publishing; Jan-. PMID: 32644727 2023.

4. Zvoncak V et al. Fractional order derivatives evaluation in computerized assessment of handwriting difficulties in school-aged children. In 2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) 2019:1–6.

5. US Department of Education. Topic: Identification of specific learning disabilities. Office of Special Education Programs 2006. http://idea.ed.gov/ explore/view/p/,root,dynamic,TopicalBrief,23.

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