<p>Principal components (PC) and mean PC score (SD) for condition T1 (1–3 gait trials), condition T2 (4–6 gait trials) and condition T3 (7–9 gait trials).</p>†<p>Significant difference between T1 and T2 (p<0.05).</p>*<p>Significant difference between T1 and T3 (p<0.05).</p
Interpreting gait data is challenging due to intersubject variability observed in the gait pattern o...
<p>Principal components analysis of the 4 categories of interest show distinct clusters that corresp...
<p>The three populations are the combined legs of typically developing children (TD), the more affec...
<p>Mean spatio-temporal parameters (SD) and coefficient of variation (CV) during stance and swing ph...
<p>Figure (A) shows the variance of each of the principal component scores amongst the 90 patients s...
<p>The first 3 principal components which account for most of the variance in the original data set ...
<p>The solid grey line indicates normal values. Loading vectors for the principal components: PC1 (s...
International audienceIn addition to changes in spatio-temporal and kinematic parameters, patients w...
For a successful completion of a movement task the motor control system has to observe a multitude o...
<p>The variance explained by PC1 and PC2 is shown in parentheses along each axis.</p
Principal components analysis is a multivariate statistical method that has been used in gait analys...
The biomechanical analysis investigates variables such as angles, inter-segmental forces and moments...
The mean and ±1 STD waveforms of 30 non-pathological (NP) and 30 osteoarthritic (OA) subjects are pl...
<p>PC1 and PC2 explain 27.7% and 15.7% of the variability in data, respectively (total 43.4%). The p...
<p>Principal component analysis of immune parameters showing the proportion of variation explained b...
Interpreting gait data is challenging due to intersubject variability observed in the gait pattern o...
<p>Principal components analysis of the 4 categories of interest show distinct clusters that corresp...
<p>The three populations are the combined legs of typically developing children (TD), the more affec...
<p>Mean spatio-temporal parameters (SD) and coefficient of variation (CV) during stance and swing ph...
<p>Figure (A) shows the variance of each of the principal component scores amongst the 90 patients s...
<p>The first 3 principal components which account for most of the variance in the original data set ...
<p>The solid grey line indicates normal values. Loading vectors for the principal components: PC1 (s...
International audienceIn addition to changes in spatio-temporal and kinematic parameters, patients w...
For a successful completion of a movement task the motor control system has to observe a multitude o...
<p>The variance explained by PC1 and PC2 is shown in parentheses along each axis.</p
Principal components analysis is a multivariate statistical method that has been used in gait analys...
The biomechanical analysis investigates variables such as angles, inter-segmental forces and moments...
The mean and ±1 STD waveforms of 30 non-pathological (NP) and 30 osteoarthritic (OA) subjects are pl...
<p>PC1 and PC2 explain 27.7% and 15.7% of the variability in data, respectively (total 43.4%). The p...
<p>Principal component analysis of immune parameters showing the proportion of variation explained b...
Interpreting gait data is challenging due to intersubject variability observed in the gait pattern o...
<p>Principal components analysis of the 4 categories of interest show distinct clusters that corresp...
<p>The three populations are the combined legs of typically developing children (TD), the more affec...