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Structure · dataset · 2022

Can developmental trajectories in movement gait variability provide prognostic clues in motor adaptation among children with mild cerebral palsy? - Dataset

Listed in ETH Zürich Research Collection

Data was collected during routine clinical gait analysis sessions at the Univeristy Children's Hospital Basel (UKBB).

Description

All participants performed at least 6 trials over a 12 meter instrumented walk-way, equipped with 12 cameras (sampling frequency 150Hz, MTX20, Vicon, Oxford Metrics Ltd., UK). A total of 64 markers were attached to the subject according to the conventional gait model (CGM 2.2, 9.5mm diameter markers).

Pre-processing of the data included filtering of the data using the built-in Woltering filter (mean squared error set to 10 mm2, performed in Vicon-Nexus v2.8.2., Oxford Metrics Ltd., UK). Afterward data was exported as c3d files, read into matlab using the biomechanical tool kit for matlab (v2019a). Gait events were set using the sagittal velocity approach (github.com/Roosje95/AGED_gait-event-detection).

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These gait events were afterwards used to estimate stride length, stride time, single support time, walking speed, cadence. Values more then 3SD away from the mean were removed. Coefficient of variation (CV, SD/mean*100%) for all above mentioned spatio-temporal parameters and asymmetry (Asym, short/long*100%) for step length, step time, and single limb support were calculated.

As were the meanSD for the sagittal joint angles of hip flexion, knee flexion, and ankle dorsiflexion which were derived from the CGM 2.2. Attached you find the *Rdata frames MDC_TDCP and MDC_GMFCS containing these Age, group (typically developing or cerebral palsy, GMFMCS I or GMFCS II), CV, Asym, and meanSD data. *Matlab files containing mean, SD, CV, Asym, meanSD, Age, group Corresponding codes are available on: github.com/Roosje95/MDC_gait_variablity

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