Background: Developmental Coordination Disorder (DCD) causes difficulties in postural control which are crucial to assess due to their impact on everyday life. There is a lack of suitable tools to acquire quantitative data and deeply analyze postural control, especially during the developmental age. The aim of this study is to investigate postural control skills in children with DCD and typically developing children (TD) using the Virtual Reality Rehabilitation System (VRRS). Methods: 18 children with DCD and 30 TD children (mean age 9.12 ± 2.65 and 7.12 ± 2.77 years, respectively) were tested by using the Movement Assessment Battery for Children Second Edition (MABC-2) and a VRRS stabilometric balance platform. A t-test was performed to identify differences in the VRRS parameters between the two groups. Furthermore, we investigated whether a correlation exists between the VRRS data and the MABC-2. Results: Significant differences (p < 0.05) in mean distance and frequency of the COP are found in the two groups. These parameters also correlate with the MABC-2 total score (p ≤ 0.05) and balance subscales (p ≤ 0.05). Conclusions: This study opens a new frontier for the assessment of postural skills in children with DCD and represents a potential basis for a tailored rehabilitation program, from which their postural stability and, consequently, their everyday life will benefit.

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Infant massage (IM) can be considered an early intervention program that leads to the environmental enrichment framework. The effectiveness of IM to promote neurodevelopment in preterm infants has been proved, but studies on infants with early brain damage are still lacking. The main aim of this study was to assess the feasibility, acceptability and usability of IM, carried out by parents at home, on infants at high risk for Cerebral Palsy. An IM daily diary and an ad hoc questionnaire, called Infant Massage Questionnaire Parent-Infant Experiences (IMQPE), were developed. IMQPE consisted of a total of 30 questions, divided into 5 areas. The parents were trained to carry out the IM with a home-based course, conducted by an expert therapist. The intensive IM program was set according to a defined daily length of at least 20 min, with a frequency of at least 5 days per week for a total of 8 weeks. Data collection consisted in the selection of the variables around the characteristics, both of the infants and the mothers, IM dosage and frequency, different body parts of the infants involved and IMQPE scores. Variable selection was carried out by minimizing the Bayesian Information Criteria (BIC) over all possible variable subsets. Nineteen high-risk infants, aged 4.83 ± 1.22 months, received IM at home for 8 weeks. The massage was given by the infants' mothers with a mean daily session dose of 27.79 ± 7.88 min and a total of 21.04 ± 8.49 h. 89.74% and 100% of mothers performed the IM for the minimum daily dosage and the frequency recommended, respectively. All the families filled in the IMQPE, with a Total mean score of 79.59% and of 82.22% in General Information on IM, 76.30% in Infant's intervention-related changes, 76.85% in IM Suitability, 79.07% in Infant's acceptance and 83.52% in Time required for the training. Different best predictors in mothers and in infants have been found. These data provide evidence of the feasibility of performing IM at home on infants at high risk for CP. Study registration: www.clinicaltrial.com (NCT03211533 and NCT03234959).

Background Nowadays, wearable sensors are widely used to quantify physical and motor activity during daily life, and they also represent innovative solutions for healthcare. In the clinical framework, the assessment of motor behaviour is entrusted to clinical scales, but they are dependent on operator experience. Thanks to their intrinsic objectivity, sensor data are extremely useful to provide support to clinicians. Moreover, wearable sensors are user-friendly and compliant to be used in an ecological environment (i.e., at home). This paper aims to propose an innovative approach useful to predict clinical assessment scores of infants’ motor activity. Materials and methods Starting from data acquired by accelerometers placed on infants’ wrists and trunk during playtime, we exploit the method of functional data analysis to implement new models combining quantitative data and clinical scales. In particular, acceleration data, transformed into activity indexes and combined with baseline clinical data, represent the input dataset for functional linear models. Conclusions Despite the small number of data samples available, results show correlation between clinical outcome and quantitative predictors, indicating that functional linear models could be able to predict the clinical evaluation. Future works will focus on a more refined and robust application of the proposed method, based on the acquisition of more data for validating the presented models. Trial registration number: ClincalTrials.gov; NCT03211533. Registered: July, 7th 2017. ClincalTrials.gov; NCT03234959. Registered: August, 1st 2017.

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