Linking clinical measurements and kinematic gait patterns of toe-walking using fuzzy decision trees.

Toe-walking is one of the most prevalent gait deviations and has been linked to many diseases. Three major ankle kinematic patterns have been identified in toe-walkers, but the relationships between the causes of toe-walking and these patterns remain unknown. This study aims to identify these relationships. Clearly, such knowledge would increase our understanding of this gait deviation, and could help clinicians plan treatment. The large quantity of data provided by gait analysis often makes interpretation a difficult task. Artificial intelligence techniques were used in this study to facilitate interpretation as well as to decrease subjective interpretation. Of the 716 limbs evaluated, 240 showed signs of toe-walking and met inclusion criteria. The ankle kinematic pattern of the evaluated limbs during gait was assigned to one of three toe-walking pattern groups to build the training data set. Toe-walker clinical measurements (range of movement, muscle spasticity and muscle strength) were coded in fuzzy modalities, and fuzzy decision trees were induced to create intelligible rules allowing toe-walkers to be assigned to one of the three groups. A stratified 10-fold cross validation situated the classification accuracy at 81%. Twelve rules depicting the causes of toe-walking were selected, discussed and characterized using kinematic, kinetic and EMG charts. This study proposes an original approach to linking the possible causes of toe-walking with gait patterns.

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

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.

A comparison of gait in spinal muscular atrophy, type II and Duchenne muscular dystrophy.

This study investigated and compared the gait of two patients with spinal muscular atrophy, type II (SMA II) and two patients with Duchenne muscular dystrophy (DMD). These diseases cause a progressive and proximal to distal muscular weakness resulting in the loss of ambulation. The DMD cases had comparable muscle weakness with the SMA II cases on manual muscle testing and patients were assessed using kinematics, kinetics, electromyography and video analysis. SMA II and DMD patients employed different gait strategies for forward movement. SMA II patients used pelvic rotation initiated by the upper body to propel the leg forward and produce the necessary step-length whereas the DMD patients tended to use hip flexion and plantar flexion. Management of SMA II patients would include preservation of hip abductor and flexor strength to maintain mobility.