Author:
Iakovidou Nantia,Lanzarini Evamaria,Singh Jatinder,Fiori Federico,Santosh Paramala
Abstract
This study explored the use of wearable sensor technology to investigate autonomic function in children with autism spectrum disorder (ASD) and Rett syndrome (RTT). We aimed to identify autonomic biomarkers that can correctly differentiate females with ASD and Rett Syndrome using an innovative methodology that applies machine learning approaches. Our findings suggest that we can predict (95%) the status of ASD/Rett. We conclude that physiological biomarkers may be able to assist in the differentiation between patients with RTT and ASD and could allow the development of timely therapeutic strategies.
Reference40 articles.
1. Trends in the Diagnosis of Rett Syndrome in Australia
2. Rett syndrome: Revised diagnostic criteria and nomenclature
3. Rett Syndrome is Caused by Mutations in X-linked MECP2, Encoding Methyl-CpG-Binding Protein 2http://genetics.nature.com
4. Disruption of DNA-methylation-dependent long gene repression in Rett syndrome
5. Characterisation of Breathing and Associated Central Autonomic Dysfunction in the Rett disorderwww.archdischild.com
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