Atypical motor patterns are potential early markers and predictors of later diagnosis of Autism Spectrum Disorder (ASD). This study aimed to investigate the early motor trajectories of infants at high-risk (HR) of ASD through MOVIDEA, a semi-automatic software developed to analyze 2D and 3D videos and provide objective kinematic features of their movements. MOVIDEA was developed within the Italian Network for early detection of Autism Spectrum Disorder (NIDA Network), which is currently coordinating the most extensive surveillance program for infants at risk for neurodevelopmental disorders (NDDs). MOVIDEA was applied to video recordings of 53 low-risk (LR; siblings of typically developing children) and 50 HR infants’ spontaneous movements collected at 10 days and 6, 12, 18, and 24 weeks. Participants were grouped based on their clinical outcome (18 HR received an NDD diagnosis, 32 HR and 53 LR were typically developing). Results revealed that early developmental trajectories of specific motor parameters were different in HR infants later diagnosed with NDDs from those of infants developing typically. Since MOVIDEA was useful in the association of quantitative measures with specific early motor patterns, it should be applied to the early detection of ASD/NDD markers.
Early detecting the presence of neurodevelopmental disorders plays an important role in the effectiveness of the treatment. In this paper, we present a novel tool to extract motion features using single camera video recordings of infants. The Movidea software was developed to allow the operator to track the movement of end-effectors of infants in free moving conditions and extract movement features automatically. Movidea was used by different operators to analyze a set of video recordings and its performance was evaluated. The results showed that Movidea performance did not vary with the operator, and the tracking was also stable in home-video recordings. Even if the setup allowed for a two-dimensional analysis, most of the informative content of the movement was maintained. The reliability of the measures and features extracted, as well as the easiness of use, may boost the uptake of the proposed solution in clinical settings. Movidea overcomes the current limitation in the clinical practice in early detection of neurodevelopmental disorders by providing objective measures based on reliable data, and adds a new tool for the motor analysis of infants through unobtrusive technology.
Personal budgets (PBs) may improve the lives of people with mental health conditions and people with intellectual disability (ID). However, a clear definition of PB, benefits, and challenges is still faded. This work aims to systematically review evidence on PB use in mental health and ID contexts, from both a qualitative and quantitative perspective, and summarize the recent research on interventions, outcomes, and cost-effectiveness of PBs in beneficiaries with mental health conditions and/or ID. The present systematic review is an update of the existing literature analyzed since 2013. We performed a systematic search strategy of articles using the bibliographic databases PubMed and PsycINFO. Six blinded authors screened the works for inclusion/exclusion criteria, and two blinded authors extracted the data. We performed a formal narrative synthesis of the findings from the selected works. A total of 9,800 publications were screened, and 29 were included. Improvement in responsibility and awareness, quality of life, independent living, paid work, clinical, psychological, and social domains, and everyday aspects of the users’ and their carers’ life have been observed in people with mental health conditions and/or ID. However, the PBs need to be less stressful and burdensome in their management for users, carers, and professionals. In addition, more quantitative research is needed to inform PBs’ policymakers.Systematic Review Registration[www.crd.york.ac.uk/prospero/], identifier [CRD42020172607].
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