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M-Health Solutions to Support the National Health Service in the Diagnosis and Monitoring of Autism Spectrum Disorders in Young Children

Tryfona, C., Oatley, G., Calderon, A. and Thorne, S. (2016) M-Health Solutions to Support the National Health Service in the Diagnosis and Monitoring of Autism Spectrum Disorders in Young Children. Lecture Notes in Computer Science, 9739 . pp. 249-256.

Link to Published Version: http://dx.doi.org/10.1007/978-3-319-40238-3_24
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Abstract

With estimates of prevalence between 1 in 68 and 1 in 88 children [11], accurate and early identification of autism spectrum disorders (ASDs) in young children remains a pressing public health issue. In the absence of a single biomarker for ASD, however, a diagnosis is currently reached on the basis of a portfolio of evidence assembled by various health care professionals, parents and educational specialists. Studies have shown that early diagnosis and subsequent intervention are key to a favourable prognosis for children with autism. Many families, however, experience long periods of time between appointments with health care professionals, thus delaying the diagnosis and subsequent access to support and interventions. In this paper, we consider the potential role of m-health software solutions in supporting the diagnosis and ongoing monitoring of ASDs in young children. We consider their application particularly within the context of the UK’s National Health Service. This paper also presents a review of some of the current literature on user-behaviour analysis software on mobile computing devices such as tablet computers and smartphones, along with some of the emerging m-health solutions for supporting the diagnosis of ASD in children.

Publication Type: Journal Article
Publisher: Springer Verlag
Copyright: © 2016 Springer International Publishing Switzerland
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Other Information: Conference title: Universal Access in Human-Computer Interaction. Users and Context Diversity. 10th International Conference UAHCI 2016 Toronto, ON, Canada, July 17-22, 2016
URI: http://researchrepository.murdoch.edu.au/id/eprint/36052
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