Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 6, 2018
Date Accepted: Jul 19, 2019
(closed for review but you can still tweet)
Improving dexterity testing by means of a sensor-based IoT smart pegboard
ABSTRACT
Background:
Pegboard tests are a powerful technique used by health and education professionals, to evaluate manual dexterity and fine motor speed both in children and adults. These tests involve the use of a “toy” consisting of a perforated board and a set of cylindrical pegs which are used by a partaker in different activities.
Objective:
The aim of this work was to improve the accuracy in dexterity testing by: i. designing a smart pegboard provided with sensors, a microcontroller and wireless communication possibilities, to be managed with a friendly application; and ii. to test the smart pegboard with children.
Methods:
A total of 39 children 25-to-41 months old were observed while performing a task in a smart 10-holes pegboard prototype developed for the study. Each hole in the smart pegboard has a sensor to detect when a peg has been inserted or removed. So, we can check the state of all holes, full or empty, and send it to system to analyses the results.
Results:
The smart pegboard worked properly in providing new and more precise information of single movement times of each peg. Significant effects were found of the hand used (Right hand faster than Left hand); of the movement (Removal faster than Placement), and of peg order (last pegs faster than first pegs).
Conclusions:
The data provided by the smart pegboard is more accurate and precise than information as obtained manually. Future studies could further explore with this new type of data, e.g. the development of intraindividual variability at different ages.
Citation
