Findings from a new study indicate that analyzing the unique signature of children's pre-speech vocalization can help in identifying autism.
This article originally appeared at Medgadget.com, part of the HCPLive network.
Identifying autistic kids as early as possible is very important, so that appropriate clinical interventions and upbringing can have the most beneficial effect. Now a new study in the Proceedings of The National Academy of Sciences has shown that analyzing the unique signature of children's pre-speech vocalizations can be a pretty good way to identify potential cases of autism.
This is done using a fairly simple voice recorder called LENA that kids wear in their clothing for all day recording. The data is then uploaded to a central server where it is analyzed for specific vocal signatures. Interestingly, although the study was conducted on American kids, the same software should be able to work with kids from other languages and cultures.
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