Rocha, Sinead and Addyman, Caspar. 2022. Assessing Sensorimotor Synchronisation in Toddlers Using the Lookit Online Experiment Platform and Automated Movement Extraction. Frontiers in Psychology, 13, 897230. ISSN 1664-1078 [Article]

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Abstract or Description

Adapting gross motor movement to match the tempo of auditory rhythmic stimulation (sensorimotor synchronisation; SMS) is a complex skill with a long developmental trajectory. Drumming tasks have previously been employed with infants and young children to measure the emergence of rhythmic entrainment, and may provide a tool for identification of those with atypical rhythm perception and production. Here we describe a new protocol for measuring infant rhythmic movement that can be employed at scale. In the current study, 50 two-year-olds drummed along with the audiovisual presentation of four steady rhythms, using videos of isochronous drumming at 400, 500, 600, and 700 ms IOI, and provided their spontaneous motor tempo (SMT) by drumming in silence. Toddlers’ drumming is observed from video recordings made in participants’ own homes, obtained via the Lookit platform for online infant studies. We use OpenPose deep-learning model to generate wireframe estimates of hand and body location for each video. The vertical displacement of the hand was extracted, and the power and frequency of infants’ rhythmic entrainment quantified using Fast Fourier Transforms. We find evidence for age-appropriate tempo-flexibility in our sample. Our results demonstrate the feasibility of a fully digital approach to measuring rhythmic entrainment from within the participant’s home, from early in development.

Item Type:	Article
Identification Number (DOI):	https://doi.org/10.3389/fpsyg.2022.897230
Additional Information:	Funding: This project was supported by the Royal Academy of Engineering Global Challenges Research Fund Grant: Frontiers of Development - Tranche 2 - FoDSF\1920\2\100020, awarded to CA.
Data Access Statement:	The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Keywords:	sensorimotor synchronisation, infancy, development, machine learning, OpenPose, Lookit, automated movement analysis
Departments, Centres and Research Units:	Psychology
Dates:	Date Event 6 June 2022 Accepted 30 June 2022 Published
Item ID:	38001
Date Deposited:	17 Dec 2024 10:51
Last Modified:	17 Dec 2024 10:56
Peer Reviewed:	Yes, this version has been peer-reviewed.
URI:	https://research.gold.ac.uk/id/eprint/38001

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