Instrumented finger-to-nose test classification in children with ataxia or developmental coordination disorder and controls. (December 2018) - Martinez-Manzanera, O.; Lawerman, T.F.; Blok, H.J.; Lunsing, R.J.; Brandsma, R.; Sival, D.A.; Maurits, N.M.
Abstract: Background: During childhood, many conditions may impact coordination. Examples are physiological age-related development and pathological conditions, such as early onset ataxia and developmental coordination disorder. These conditions are generally diagnosed by clinical specialists. However, in absence of a gold phenotypic standard, objective reproducibility among specialists appears limited. Methods: We investigated whether quantitative analysis of an upper limb coordination task (the finger-to-nose test) could discriminate between physiological and pathological conditions impacting coordination. We used inertial measurement units to estimate movement trajectories of the participants while they executed the finger-to-nose test. We employed random forests to classify each participant in one category. Findings: On average, 87.4% of controls, 74.4% of early onset ataxia and 24.8% of developmental coordination disorder patients were correctly classified. The relatively good classification of early onset ataxia patients and controls contrasts with the poor classification of developmental coordination disorder patients. Interpretation: In absence of a gold phenotypic standard for developmental coordination disorder recognition, it remains elusive whether the finger-to-nose test in these patients represents a sufficiently accurate entity to reflect symptoms distinctive of this disorder. Based on the relatively good results in early onset ataxia patients and controls, we conclude that quantitative analysis of the finger-to-nose test can provide a reliable support tool during the assessment of phenotypic early onset ataxia. Highlights: Finger-to-nose automatic analysis identified 80% of the patients with ataxia. Developmental coordination disorder identification was more challenging than ataxia. Automatic analysis of coordination can help to support phenotypic assessment.