Abstract
The aim was to analyze independent child gait in children 20 to 48 months with typical motor development to establish a valid set of angular position data. A total of five children were recruited for this research. Five Xsens MTw Awinda wearable inertial movement sensors located at the pelvis, between L4/L5 OR S1/S2, the quadriceps and anterior tibialis were used to quantify the gait cycle on rigid floors. Five measurements were taken from each child and only the four bests were taken. Data analysis was performed using polynomial regression by least squares and statical methods: Pearson’s correlation and coefficient of determination R2. The patterns of the movement curves resulting from the data sets of the evaluated joints exhibit similarities between children of different ages. To corroborate the information obtained, a comparison was made with an already established database for the same measurement parameters, achieving similarity percentages of 78% for pelvic rotation as well as 53 and 79% for pelvic obliquity. Results suggest that is essential to extend the age range of the children, as well as to increase the numbers of participants evaluated to establish a follow-up in the complete maturation of the infantile gait.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mangalindan, D.M.J., Schmuckler, M.A., Li, S.-A.: The impact of object carriage on independent locomotion. Infant Behav Dev. 37(1), 76–85 (2014). https://doi.org/10.1016/j.infbeh.2013.12.008
Adolph, K.E., Rachwani, J., Hoch, J.E.: Motor and physical development: locomotion. In: Encyclopedia of Infant and Early Childhood Development, pp. 347–363. Elsevier (2020). https://doi.org/10.1016/B978-0-12-809324-5.05848-X
Hsu, W.-H., Miranda, D.L., Chistolini, T.L., Goldfield, E.C.: Toddlers actively reorganize their whole-body coordination to maintain walking stability while carrying an object. Gait Posture 50, 75–81 (2016). https://doi.org/10.1016/j.gaitpost.2016.08.023
Looper, J., Chandler, L.S.: How do toddlers increase their gait velocity? Gait Posture 37(4), 631–633 (2013). https://doi.org/10.1016/j.gaitpost.2012.09.009
Adolph, K.E., Franchak, J.M.: The development of motor behavior. Wiley Interdiscip. Rev. Cogn. Sci. 8(1–2), e1430 (2017). https://doi.org/10.1002/wcs.1430
Fang, X., Liu, C., Jiang, Z.: Reference values of gait using APDM movement monitoring inertial sensor system. R. Soc. Open Sci. 5(1), 170818 (2018). https://doi.org/10.1098/rsos.170818
Bergamini, E., Ligorio, G., Summa, A., Vannozzi, G., Cappozzo, A., Sabatini, A.M.: Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks. Sensors 14(10), 18625–18649 (2014). https://doi.org/10.3390/s141018625
Iosa, M., Picerno, P., Paolucci, S., Morone, G.: Wearable inertial sensors for human movement analysis. Expert Rev. Med. Devices 13(7), 641–659 (2016). https://doi.org/10.1080/17434440.2016.1198694
Al-Amri, M., Nicholas, K., Button, K., Sparkes, V., Sheeran, L., Davies, J.: Inertial measurement units for clinical movement analysis: Reliability and concurrent validity. Sensors 18(3), 719 (2018). https://doi.org/10.3390/s18030719
Hardware, M., Manager, M.T., Protocol, A:. MTw Awinda User Manual. Xsens.com. [cited 2021 Apr 1]. Available from: https://documentation.xsens.com/mtw_user_manual
Belluscio, V., et al.: Dynamic balance assessment during gait in children with down and Prader-Willi syndromes using inertial sensors. Hum. Mov. Sci. 63, 53–61 (2019). https://doi.org/10.1016/j.humov.2018.11.010
Zhou, Lin, et al.: How we found our IMU: guidelines to IMU selection and a comparison of seven IMUs for pervasive healthcare applications. Sensors 20(15), 4090 (2020). https://doi.org/10.3390/s20154090
Auepanwiriyakul, C., Waibel, S., Songa, J., Bentley, A.P., Faisal, A.: Accuracy and acceptability of wearable motion tracking for inpatient monitoring using smartwatches. Sensors 20(24), 7313 (2020). https://doi.org/10.3390/s20247313
Paulich, M., Schepers, M., Rudigkeit, N., Bellusci ,G.: Xsens MTw awinda: miniature wireless inertial-magnetic motion tracker for highly accurate 3D kinematic applications. Xsens Technologies B.V, Enschede, The Netherlands (2018). https://doi.org/10.13140/RG.2.2.23576.49929
Jouybari, A., Amiri, H., Ardalan, A.A., Zahraee, N.K.: Methods comparison for attitude determination of a lightweight buoy by raw data of IMU. Measurement 135, 348–354 (2019). https://doi.org/10.1016/j.measurement.2018.11.061
Garza-Ulloa, J.: Experiment design, data acquisition and signal processing. In: Applied Biomechatronics using Mathematical Models, pp. 179–237. Elsevier (2018). https://doi.org/10.1016/B978-0-12-812594-6.00004-4
Calderón, D.M.J., Ulloa, J.R.A.: Cambios asociados al envejecimiento normal en los parámetros angulares de la marcha a una velocidad controlada. Rev. Med. Chil. 144(1), 74–82 (2016). https://doi.org/10.4067/S0034-98872016000100010
Acknowledgements
The authors would like to thank the volunteers who participated as study subjects, and the parents who gave their consent for their children to participate in this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Armas, Y.M., Cabrera, V.H., López, A. (2023). Evaluation of Biomechanical Conditions in Infants from 20 to 48 Months of Age in Gait. In: Robles-Bykbaev, V., Mula, J., Reynoso-Meza, G. (eds) Intelligent Technologies: Design and Applications for Society. CITIS 2022. Lecture Notes in Networks and Systems, vol 607. Springer, Cham. https://doi.org/10.1007/978-3-031-24327-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-24327-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24326-4
Online ISBN: 978-3-031-24327-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)