Detail publikace

Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children

Originální název

Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children

Anglický název

Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children

Jazyk

en

Originální abstrakt

Although graphomotor difficulties (GD) are present in up to 30 % of school-aged children, the field of GD diagnosis and assessment is not fully explored and several research gaps can be identified. This study aims to explore the impact of specific elementary graphomotor tasks analysis on the accuracy of computerised diagnosis and assessment of GD. We analysed seven basic graphomotor tasks from 76 children (assessed by special educational counsellors and using the handwriting proficiency screening questionnaire for children HPSQ–C). Employing a differential analysis, we observed that the most discriminative tasks are based on combined loops, sawtooth and small Archimedean spiral drawings. Features with the highest discrimination power quantify kinematics, especially in the vertical projection. Using a multivariate mathematical model, we were able to identify GD with 50 % sensitivity and 90% specificity, and to estimate the total score of HPSQ–C with 31 % error

Anglický abstrakt

Although graphomotor difficulties (GD) are present in up to 30 % of school-aged children, the field of GD diagnosis and assessment is not fully explored and several research gaps can be identified. This study aims to explore the impact of specific elementary graphomotor tasks analysis on the accuracy of computerised diagnosis and assessment of GD. We analysed seven basic graphomotor tasks from 76 children (assessed by special educational counsellors and using the handwriting proficiency screening questionnaire for children HPSQ–C). Employing a differential analysis, we observed that the most discriminative tasks are based on combined loops, sawtooth and small Archimedean spiral drawings. Features with the highest discrimination power quantify kinematics, especially in the vertical projection. Using a multivariate mathematical model, we were able to identify GD with 50 % sensitivity and 90% specificity, and to estimate the total score of HPSQ–C with 31 % error

BibTex


@inproceedings{BUT159732,
  author="Jiří {Mekyska} and Zoltán {Galáž} and Vojtěch {Zvončák} and Ján {Mucha} and Zdeněk {Smékal}",
  title="Computerised Assessment of Graphomotor Difficulties in a Cohort of School-aged Children",
  annote="Although graphomotor difficulties (GD) are present in up to 30 % of school-aged children, the field of GD diagnosis and assessment is not fully explored and several research gaps can be identified. This study aims to explore the impact of specific elementary graphomotor tasks analysis on the accuracy of computerised diagnosis and assessment of GD. We analysed seven basic graphomotor tasks from 76 children (assessed by special educational counsellors and using the handwriting proficiency screening questionnaire for children HPSQ–C). Employing a differential analysis, we observed that the most discriminative tasks are based on combined loops, sawtooth and small Archimedean spiral drawings. Features with the highest discrimination power quantify kinematics, especially in the vertical projection. Using a multivariate mathematical model, we were able to identify GD with 50 % sensitivity and 90% specificity, and to estimate the total score of HPSQ–C with 31 % error",
  booktitle="2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)",
  chapter="159732",
  howpublished="online",
  year="2019",
  month="october",
  pages="1--6",
  type="conference paper"
}