Assessment of Postural Control in Children with Movement Disorders by Means of a New Technological Tool: A Pilot Study

Author:

Menici Valentina12ORCID,Scalise Roberta1ORCID,Fasano Alessio345ORCID,Falotico Egidio34ORCID,Dubbini Nevio6ORCID,Prencipe Giuseppe7ORCID,Sgandurra Giuseppina18,Filogna Silvia1ORCID,Battini Roberta18ORCID

Affiliation:

1. Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, 56128 Pisa, Italy

2. Ph.D. Programme in Clinical and Translational Sciences, University of Pisa, 56126 Pisa, Italy

3. The BioRobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy

4. Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy

5. IRCCS Fondazione Don Carlo Gnocchi ONLUS, 50143 Florence, Italy

6. Miningful srls, 56121 Pisa, Italy

7. Department of Computer Science, University of Pisa, 56127 Pisa, Italy

8. Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy

Abstract

Considering the variability and heterogeneity of motor impairment in children with Movement Disorders (MDs), the assessment of postural control becomes essential. For its assessment, only a few tools objectively quantify and recognize the difference among children with MDs. In this study, we use the Virtual Reality Rehabilitation System (VRRS) for assessing the postural control in children with MD. Furthermore, 16 children (mean age 10.68 ± 3.62 years, range 4.29–18.22 years) were tested with VRRS by using a stabilometric balance platform. Postural parameters, related to the movements of the Centre of Pressure (COP), were collected and analyzed. Three different MD groups were identified according to the prevalent MD: dystonia, chorea and chorea–dystonia. Statistical analyses tested the differences among MD groups in the VRRS-derived COP variables. The mean distance, root mean square, excursion, velocity and frequency values of the dystonia group showed significant differences (p < 0.05) between the chorea group and the chorea–dystonia group. Technology provides quantitative data to support clinical assessment: in this case, the VRRS detected differences among the MD patterns, identifying specific group features. This tool could be useful also for monitoring the longitudinal trajectories and detecting post-treatment changes.

Funder

Italian Ministry of Health

Publisher

MDPI AG

Reference57 articles.

1. Movement Disorders Presenting in Childhood;Kurian;CONTINUUM Lifelong Learn. Neurol.,2016

2. Singer, H.S., Mink, J.W., Gilbert, D.L., and Jankovic, J. (2016). Movement Disorders in Childhood, Academic Press. [2nd ed.].

3. Definition and Classification of Hyperkinetic Movements in Childhood;Sanger;Mov. Disord.,2010

4. Parkinsonism and Inborn Errors of Metabolism;Duarte;J. Inherit. Metab. Dis.,2014

5. Clinical Presentation and Management of Dyskinetic Cerebral Palsy;Monbaliu;Lancet Neurol.,2017

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