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Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Gait performance in toddlers born preterm: A sensor based quantitative characterization
Maria Cristina Bisi1, Manuela Fabbri2, Duccio Maria Cordelli3
1Department of Electrical, Electronic and Information Engineering, "Guglielmo Marconi" - DEI, University of Bologna, Italy; Interdepartmental Center for Industrial Research - Life Sciences and Health Technologies, University of Bologna, Italy.
Insights
Sensor-based gait analysis reveals motor differences in preterm toddlers. Higher risk preterm children show less mature gait patterns, indicating potential for early detection of motor impairments.
Area of Science:
- Pediatric neurology
- Biomedical engineering
- Developmental pediatrics
Background:
- Preterm birth is associated with an increased risk of motor difficulties in children.
- Gait analysis using wearable sensors offers a quantitative method to assess motor performance in toddlers.
- Early identification of deviations in motor development is crucial for timely intervention.
Purpose of the Study:
- To quantitatively compare gait performance between full-term and preterm toddlers using a sensor-based approach.
- To identify gait differences among preterm toddlers stratified by their risk of motor delay.
- To establish gait parameters as potential biomarkers for monitoring locomotor development.
Main Methods:
- Inertial sensors were placed on the lower back and ankles of 2-year-old children (29 preterm, 17 full-term).
- Gait temporal parameters, variability, and nonlinear trunk kinematics metrics were analyzed during walking.
- Preterm children were categorized into high-risk (born ≤28 weeks or ≤1000g) and moderate-risk groups.
Main Results:
- Preterm toddlers exhibited significantly longer stance and double support phases, increased temporal parameter variability, and lower multiscale entropy compared to full-term peers.
- Increasing risk of motor delay in preterm children correlated with longer stride, stance, and double support times, higher temporal variability, and altered entropy/recurrence values.
- Specific gait parameters effectively differentiated between full-term and preterm toddlers, and among preterm subgroups based on motor delay risk.
Conclusions:
- Sensor-based gait analysis successfully distinguished gait patterns between full-term and preterm toddlers, and among preterm children with varying motor delay risk.
- Preterm children, especially those at higher risk, demonstrated less mature motor control during gait, characterized by reduced stability and increased variability.
- Identified gait parameters can serve as valuable biomarkers for monitoring locomotor development and enabling early detection of potential persistent motor impairments.
Background And Objectives:
Preterm children have an increased risk of motor difficulties. Gait analysis and wearable technologies allow the assessment of motor performance in toddlers, identifying early deviations from typical development. Using a sensor-based approach, gait performance of full-term and preterm toddlers at different risk of motor delay was analysed. The aim was to measure quantitative differences among groups.
Methods:
Twenty-nine two-year old children born preterm (≤36 gestational weeks) and 17 full-term controls, matched for age and walking experience, participated in the study. Preterm children were further divided based on risk of motor delay: preterm at high risk (n = 8, born at ≤28 gestational weeks or with ≤1000 g of body weight), and at moderate risk (n = 21). Children were asked to walk along a corridor while wearing 3 inertial sensors on the lower back and on the ankles. Gait temporal parameters, their variability, and nonlinear metrics of trunk kinematics (i.e. recurrence quantification analysis, multiscale entropy) were extracted from the collected data and compared among groups.
Results:
Children born preterm showed significantly longer stance and double support phases, higher variability of temporal parameters, and lower multiscale entropy values than peers born full-term. No difference was found for the other parameters when comparing preterm and full-term children. When comparing children grouped according to risk of delay, with increasing risk, children showed longer stride-, stance- and double-support-time, higher variability of temporal parameters, higher recurrence- and lower multiscale entropy values.
Conclusions:
Sensor-based gait analysis allowed differentiating the gait performance of preterm from full-term toddlers, and of preterm toddlers at different risk of motor delay. When analysing the present results with respect to the expected trajectory of locomotor development, children born preterm, in particular those at higher risk of motor delay, exhibited a less mature motor control performance during gait: lower stability (i.e. longer support phases), and higher variability, although not structured towards the exploration of more complex movements (i.e. higher recurrence- and lower multiscale entropy values). These indexes can serve as biomarkers for monitoring locomotor development and early detecting risk to develop persistent motor impairments.
