Kinematic patterns during walking in children: Application of principal component analysis

The relative displacements of body segments during walking can be reduced to a small number of multi-joint kinematic patterns, pmk, through Principal Component Analysis (PCA). These patterns were extracted from two groups of children (n = 8, aged 6–9 years, 4 males, and n = 8, aged 10–13 years, 4 males) and 7 adults (21–29 years, 1 male), walking on a treadmill at various velocities, normalized to body stature (adimensional Froude number, Fr). The three-dimensional coordinates of body markers were captured by an optoelectronic system. Five components (pm1 to pm5) explained 99.1% of the original dataset variance. The relationship between the variance explained (“size”) of each pmk and the Fr velocity varied across movement components and age groups. Only pm1 and pm2, which described kinematic patterns in the sagittal plane, showed significant differences (at p < 0.05) across pairs of age groups. The time course of the size of all the five components matched various mechanical events of the step cycle at the level of both body system and lower limb joints. Such movement components appeared clinically interpretable and lend themselves as potential markers of neural development of walking.