According to the US scientists, by listening to sounds your baby makes, it can be possible to identify autism.
Researchers from the University of Kansas, US, when kids with autism and without the disorder are compared, a difference is seen in the babbling of infants.
Language Environment Analysis or LENA has been developed, which is a new automated vocal analysis technology. It can differentiate the pre-verbal vocalisations of very young children with autism from those of typically developing children. The accuracy is as close as 86 per cent.
Professor Steven Warren, an expert in autism spectrum disorders at the University of Kansas who took part in the study, said, "This technology could help paediatricians screen children for ASD, autism spectrum disorder, to determine if a referral to a specialist for a full diagnosis is required and get those children into earlier and more effective treatments."
Keith Lovett, director of Autism Independent UK, said the technique sounded interesting but said that data can be skewed.
Lovett added, "Until other people can replicate it from other places around the world or other universities, I wouldn't take the data as read."
Before LENA, doctors were unable to use the information in the diagnosis due to the inability to measure it but they could figure out the difference in vocalization between kids without autism and with autism.
- Helen Flanagan at the launch of her PEATA ad; reveals more than she wanted
- Scientists may use Vitamin C in TB Treatment to Kill Tuberculosis Bacteria
- Jolie’s Revelation of Undergoing Double Mastectomy Creates Needless Panic among Women
- India and UK Sign MOU on Cooperation in the Field Of Health Sector
- Examining Exoplanets, their Surfaces and their Atmosphere