Gait phenotypes in paediatric hereditary spastic paraplegia revealed by dynamic time warping analysis and random forests

The Hereditary Spastic Paraplegias (HSP) are a group of heterogeneous disorders with a wide spectrum of underlying neural pathology, and hence HSP patients express a variety of gait abnormalities. Classification of these phenotypes May help in monitoring disease progression and personalizing therapies. This is currently managed by measuring values of some kinematic and spatio-temporal parameters at certain moments during the gait cycle, either in the doctor´s surgery room or after very precise measurements produced by instrumental gait analysis (IGA). These methods, however, do not provide information about the whole structure of the gait cycle. Classification of the similarities among time series of IGA measured values of sagittal joint positions throughout the whole gait cycle can be achieved by hierarchical clustering analysis based on multivariate dynamic time warping (DTW). Random forests can estimate which are the most important isolated parameters to predict the classification revealed by DTW, since clinicians need to refer to them in their daily practice. We acquired time series of pelvic, hip, knee, ankle and forefoot sagittal angular positions from 26 HSP and 33 healthy children with an optokinetic IGA system. DTW revealed six gait patterns with different degrees of impairment of walking speed, cadence and gait cycle distribution and related with patient’s age, sex, GMFCS stage, concurrence of polyneuropathy and abnormal visual evoked potentials or corpus callosum. The most important parameters to differentiate patterns were mean pelvic tilt and hip flexion at initial contact. Longer time of support, decreased values of hip extension and increased knee flexion at initial contact can differentiate the mildest, near to normal HSP gait phenotype and the normal healthy one. Increased values of knee flexion at initial contact and delayed peak of knee flexion are important factors to distinguish GMFCS stages I from II- III and concurrence of polyneuropathyDGA was in receipt of a grant from Sociedad Española de Neurología Pediátrica (SENEP). Publication fee was supported by EUF-ONCE-UAM and Asociación Española de Paraparesia Espástica Familiar (AEPEF)

Integración : revista digital sobre discapacidad visual

Resumen basado en el de la publicaciónTítulo, resumen y palabras clave en español e inglésTras constatar las dificultades para el aprendizaje de los plexos nerviosos por parte de los alumnos de la asignatura Anatomía Humana I, del Grado en Fisioterapia impartido en la Escuela de Fisioterapia de la ONCE, se elaboraron sus propios modelos, ante la falta de disponibilidad de materiales específicos de apoyo. Se describen las distintas fases de elaboración de las maquetas, los materiales empleados y su utilización en el aula. Se han dedicado 60 horas a la fabricación de seis plexos, tres de los cuales se presentan en este artículo, y el coste de los materiales no ha superado los 200 euros. A pesar de las limitaciones que han podido observarse (idoneidad de algunos materiales, tiempo de trabajo, número de plexos confeccionados), los alumnos se han implicado más profundamente en las explicaciones, han participado más y, en definitiva, han optimizado su conocimiento de estas complejas estructuras.ES

Distribution of sagittal patterns in left and right cycles and clinical features of each patient.

<p>Patients were ordered according to the type of gait patterns they use (left) and clinical features were represented with colour scales (right). Notice that clinical features are partially related to the gait phenotype.</p

Cumulated kinematic plots of five joints grouped according to seven sagittal patterns yielded by dendrogram in Fig 1.

<p>Each column represents a pattern and each row, a joint. The x-axis of each graph corresponds to the percentage of gait cycle. The y-axis represents the joint range in degrees (zero is the neutral position, positive values indicate flexion and negative values, extension). The healthy children’s cycles are depicted in grey lines, their average healthy patterns in black, and the overall healthy average is shown with a thick black line. Patterns I and II (red and blue, respectively) are the most similar to normal. The outlier (pink) corresponds to an “outlier” cycle.</p

Importance of gait parameters in the classification of gait cycles in sagittal patterns generated by the random forest.

<p>It is measured by the mean decrease in accuracy when the variable is out of the bag. The most important are <i>mean pelvic tilt</i> and <i>hip flexion at initial contact</i>.</p

Spatiotemporal parameters that were extracted from each gait cycle.

<p>Spatiotemporal parameters that were extracted from each gait cycle.</p

Goodness of fit of random forests used for the prediction of clinical features based on gait parameters.

<p>Goodness of fit of random forests used for the prediction of clinical features based on gait parameters.</p

Importance of gait parameters for the random forest model to distinguish between cycles from HSP sagittal Pattern I and healthy controls.

<p>It is measured by Breiman-Cutler permutation variable importance (VIMP). <i>Stance time</i> and <i>time to peak knee flexion in stance</i> are the most important parameters to distinguish patients with sagittal Pattern I from healthy controls.</p

Relationships of the four most important gait parameters to predict age in HSP according to random forest model.

<p>Age is shown in the x-axis and each gait parameter in the y-axis. We represent healthy and HSP children data (blue and red points) and the adjusted linear mixed model for each group (blue and red lines). In the case of cadence (upper right), age and cadence are similarly related in both groups. In the case of normalized walking speed (upper left), the decrease of normalized walking speed with age tends to be higher in children with HSP, although it is not statistically significant (see text). Range of pelvic rotation in terminal swing (lower left) increases only with age in children with HSP, while it seems to remain stable in healthy subjects along the age spectrum. Maximum knee flexion (lower right) decreases with age both in HSP children and healthy children, but in the case of disabled children, it seems to decrease significantly faster.</p

<i>Heatmap</i> showing the Z-scores (standardized measure of the distance to healthy average value) of the 12 most important gait parameters to classify cycles into gait patterns according to random forest models.

<p>Cycles are represented in columns and ordered following the dendrogram shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192345#pone.0192345.g001" target="_blank">Fig 1</a>. Gait parameters are shown in rows and ordered according to the relationships between relationships with each other (dendrogram on the left). The Z-scores are represented following the colour legend in the top left corner.</p