Automatic classification of gait in children with Early-Onset Ataxia or Developmental Coordination Disorder and controls using inertial sensors

Andrea Mannini, Octavio Martinez-Manzanera, Tjitske F. Lawerman, Diana Trojaniello, Ugo Della Croce, Deborah A. Sival, Natasha M. Maurits, Angelo Maria Sabatini; Gait & Posture, Available online 2 December 2016, ISSN 0966-6362, doi:10.1016/j.gaitpost.2016.12.002.

Early-Onset Ataxia (EOA) and Developmental Coordination Disorder (DCD) are two conditions that affect coordination in children. Phenotypic identification of impaired coordination plays an important role in their diagnosis. Gait is one of the tests included in rating scales that can be used to assess motor coordination. A practical problem is that the resemblance between EOA and DCD symptoms can hamper their diagnosis. In this study we employed inertial sensors and a supervised classifier to obtain an automatic classification of the condition of participants.
In absence of reliable distinctive biomarkers, the Scale for Assessment and Rating of Ataxia (SARA), is often used as an additional, supportive biomarker to indicate ataxia severity. Despite the high reliability of the scale, we have shown that pediatric SARA is confounded by other factors than ataxia, as well. Nevertheless, we have shown that the relative SARA gait subscore can support the recognition of an indisputable EOA phenotype in mildly affected participants. Presently available quantitative gait parameters [14] are still not ubiquitously implemented as a clinical tool. Based on the remarks reported above, we reasoned that clinically simple and reproducible quantitative gait analysis could be worthwhile for reliable EOA and DCD recognition.
In the present paper, we evaluate a method for the automatic and objective assessment of pediatric gait as compared to a clinical diagnosis in a similar way to what was previously done for other pathological conditions. Additionally, the accuracy of phenotypic assessments is estimated. Both methods classify patients into three groups (EOA, DCD and CTRL). To be effective, the automatic assessment is expected to guarantee both a limited increase of the complexity of the evaluation and a minimal impact on the gait patterns under evaluation. Hopefully, this study provides a first step towards incorporating a clinically objective and viable biomarker for uniform identification of EOA and DCD.




Automatic classification of gait in children with Early-Onset Ataxia or Developmental Coordination Disorder and controls using inertial sensors