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Detecting age groups using touch interaction based on neuromotor characteristics

Detecting age groups using touch interaction based on neuromotor characteristics

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A new parental control method to prevent unauthorised usage of touch devices by kids is proposed. The impact of rapidly advancing technology on the developing child has seen an increase exposition to new forms of danger. Studies reveal that 97% of US children under the age of four use mobile devices. A reliable and efficient method to prevent the use of touch devices by preschool children is proposed. The proposed method is based on the analysis of the neuromotor characteristics of the users according to the decomposition of simple drag and drop tasks using the kinematic theory of rapid human movements. The experimentation is conducted on a publicly available database with samples obtained from 89 children between 3 and 6 years old and 30 adults. The results are compared with an existent system based only on task time and accuracy. Finally, both systems are combined at score level to achieve better performances. The results, with correct classification rates over 96% in the combined system, show the discriminative ability of the proposed neuromotor-inspired features and the possibility of combining this system with others to improve their final performance.


    1. 1)
      • 2. ‘Parental controls product guide, 2010 edition’, Available at, accessed November 2016.
    2. 2)
    3. 3)
      • 5. Piaget, J., Inhelder, B.: ‘The psychology of the child’ (Basic books, 1966).
    4. 4)
    5. 5)
      • 4. Vatavu, R.D., Anthony, L., Brown, Q.: ‘Child or adult? inferring smartphone users’ age group from touch measurements alone’. Human-Computer Interaction, 2015, pp. 19, doi: 10.1007/978-3-319-22723-8_1.
    6. 6)
    7. 7)
      • 8. Fischer, A., Plamondon, R.: ‘A dissimilarity measure for on-line signature verification based on the Sigma-Lognormal model’. 17th Conf. of the Int. Graphonomics Society, Guadeloupe, June 2015.
    8. 8)
    9. 9)
      • 3. Aziz, N.A.A., Batmaz, F., Stone, R., et al: ‘Selection of touch gestures for children's applications’. Science and Information Conf., London, October 2013, pp. 721726.
    10. 10)

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