Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/165599
Title: | The design and development of instrumented toys for the assessment of infant cognitive flexibility | Authors: | Ramanathan, Vishal Mohammad Zaidi Ariffin Goh, Guo Dong Goh, Guo Liang Mohammad Adhimas Rikat Tan, Xing Xi Yeong, Wai Yee Ortega, Juan-Pablo Leong, Victoria Campolo, Domenico |
Keywords: | Engineering::Mechanical engineering Social sciences::Psychology |
Issue Date: | 2023 | Source: | Ramanathan, V., Mohammad Zaidi Ariffin, Goh, G. D., Goh, G. L., Mohammad Adhimas Rikat, Tan, X. X., Yeong, W. Y., Ortega, J., Leong, V. & Campolo, D. (2023). The design and development of instrumented toys for the assessment of infant cognitive flexibility. Sensors, 23(5), 2709-. https://dx.doi.org/10.3390/s23052709 | Journal: | Sensors | Abstract: | The first years of an infant's life represent a sensitive period for neurodevelopment where one can see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction. Besides being extremely time-consuming, video annotation is known to be rater-dependent and subjective. To address these issues, starting from existing cognitive flexibility research protocols, we developed a set of instrumented toys to serve as a new type of task instrumentation and data collection tool suitable for infant use. A commercially available device comprising a barometer and an inertial measurement unit (IMU) embedded in a 3D-printed lattice structure was used to detect when and how the infant interacts with the toy. The data collected using the instrumented toys provided a rich dataset that described the sequence of toy interaction and individual toy interaction patterns, from which EF-relevant aspects of infant cognition can be inferred. Such a tool could provide an objective, reliable, and scalable method of collecting early developmental data in socially interactive contexts. | URI: | https://hdl.handle.net/10356/165599 | ISSN: | 1424-8220 | DOI: | 10.3390/s23052709 | Schools: | School of Mechanical and Aerospace Engineering School of Physical and Mathematical Sciences School of Social Sciences |
Research Centres: | Robotics Research Center Singapore Centre for 3D Printing |
Rights: | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | MAE Journal Articles SC3DP Journal Articles SPMS Journal Articles SSS Journal Articles |
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