Identification and classification of toe-walkers based on ankle kinematics, using a data-mining method.

Stéphane Armand; Eric Watelain; Moïse Mercier; Ghislaine Lensel; François-Xavier Lepoutre

doi:10.1016/j.gaitpost.2005.02.007

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Identification and classification of toe-walkers based on ankle kinematics, using a data-mining method.

Stéphane Armand·Eric Watelain·Moïse Mercier·Ghislaine Lensel·François-Xavier Lepoutre

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Abstract

A database of 1,736 patients and 2,511 gait analyses was reviewed to identify for trials where the first rocker was absent. A fuzzy c-means algorithm was used to identify sagittal ankle kinematic patterns and three groups were identified. The first showed a progressive dorsiflexion during the stance phase, while the second had a short-lived dorsiflexion, followed by a progressive plantarflexion. The third group exhibited a double bump pattern, moving successively from a short-lived dorsiflexion to a short-lived plantarflexion and then returning to a further short-lived dorsiflexion before ending with plantarflexion until toe-off. The three patterns were linked to different neurological conditions. Myopathy, neuropathy and arthogryposis essentially revealed group 1 patterns, whereas idiopathic toe-walkers mainly displayed group 2 patterns. Cerebral palsy patients, however, were relatively homogeneously distributed amongst the three groups. Able-bodied subjects walking on their toes showed a high proportion of unclassifiable ankle patterns, due to a variable gait whilst toe walking. Despite the variety of neurological conditions included in this meta-analysis repeatable biomechanical patterns appeared that could influence therapeutic management.

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Adolescent Algorithms Biomechanical Phenomena Databases as Topic Electromyography Female Fuzzy Logic Gait Disorders, Neurologic Humans Lower Extremity Male Toes Walking Journal Article

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Stéphane Armand, Eric Watelain, Moïse Mercier, Ghislaine Lensel, François-Xavier Lepoutre. 2006. Identification and classification of toe-walkers based on ankle kinematics, using a data-mining method.. https://doi.org/10.1016/j.gaitpost.2005.02.007

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