The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19236381

Blok, Janneke; Poggensee, Katie; Lemus Perez, Daniel; Kok, Manon; Pangalila, Robert et. al. (2022): Data underlying: Quantification of the development of trunk control in healthy infants using inertial measurement units. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19236381.v1

Dataset

• Mechanical Engineering
• Biomedical Engineering

balance, Inertial Measurement Unit (IMU), infant data, jerk, motor control, trunk control

CC0

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by Janneke Blok , Katie Poggensee , Daniel Lemus Perez , Manon Kok , Robert Pangalila , Heike Vallery , Jolien Deferme , Leontien Toussaint-Duyster , Herwin Horemans

Trunk motor control is essential for the proper functioning of the upper extremities and is an important predictor of gait capacity in children with delayed development. Early diagnosis and intervention could increase the trunk motor capabilities in later life, but current tools used to assess the level of trunk motor control are largely subjective and many lack the sensitivity to accurately monitor development and the effects of therapy. Inertial measurement units could yield an objective quantitative assessment that is inexpensive and easy-to-implement. We performed an experiment with six young children, each wearing a trunk-attached sensor, to determine if the root mean square of jerk, a proxy for smoothness of movement, can distinguish age. Root mean square of jerk decreases with age, up to 24 months, and is correlated to a more established method, i.e., center-of-pressure velocity, as well as other standard inertial measurement unit outputs. This metric therefore shows potential as a method to differentiate trunk motor control levels.

• 2022-05-11 first online, published, posted

4TU.ResearchData

Data file (.zip of .mat files), .m functions

TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Department of Biomechatronics & Human-Machine Control