Instrumented toys for studying power and precision grasp forces in infants

S. M. Serio, F. Cecchi, E. Boldrini, C. Laschi, G. Sgandurra, G. Cioni, P. Dario

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Currently the study of infants grasping development is purely clinical, based on functional scales or on the observation of the infant while playing; no quantitative variables are measured or known for diagnosis of eventually disturbed development. The aim of this work is to show the results of a longitudinal study achieved by using a baby gym composed by a set of instrumented toys, as a tool to measure and stimulate grasping actions, in infants from 4 to 9 months of life. The study has been carried out with 7 healthy infants and it was observed, during infants development, an increase of precision grasp and a reduction of power grasp with age. Moreover the forces applied for performing both precision and power grasp increase with age. The proposed devices represent a valid tool for continuous and quantitative measuring infants manual function and motor development, without being distressful for the infant and consequently it could be suitable for early intervention training during the first year of life. The same system, in fact, could be used with infants at high risk for developmental motor disorder in order to evaluate any potential difference from control healthy infants.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages2017-2020
Number of pages4
DOIs
Publication statusPublished - 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/TerritoryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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