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Sound patterns help identify autism, finds study

Researchers have developed a new automated vocal analysis system that automatically detects speech abnormalities linked with autism. Researchers theorize that since the analysis is not based on words but on sound patterns, the technique could be used with children speaking any language.

Researchers have developed a new automated vocal analysis system that automatically detects speech abnormalities linked with autism.

The device called LENA (Language Environment Analysis) raises hopes of an accurate diagnose and early intervention.

Steven Warren, professor of applied behavioral science at the University of Kansas, who was involved in the research, said, "This technology could help pediatricians to screen children for autism spectrum disorders to determine if a referral to a specialist for a full diagnosis is required and get those children into earlier and more effective treatments.”

A comparison in the speech patterns between typically developing kids and those previously diagnosed with autism or those with language delays helped the researchers track autism.

The working of the device
The method involves recording speech sounds made by young kids and then analyzing them with a computer program to distinguish speech patterns.

For the purpose of the study, experts tested the device on 232 kids aged 10 months to four years.

About half of the children were considered to be typically developing, while in the remaining half, about 50 had been diagnosed as language-delayed and about 75 had been diagnosed with autism.

Battery-operated tape recorders were strapped on the kids clothing which they carried through out the day.

The researchers collected nearly 1,500 full-day soundtracks and then plugged them into the analytical voice machine for analysis.

Findings of the study
After separating the sounds made by the children and by their environment, the data was fed into a special computer program.

A comparison in the sound patterns between typically developing kids and those previously diagnosed with autism or those with language delays helped the researchers track autism.

The test apart from being 86 percent accurate was also able to pick out children who had impaired language development.

This was possible because autistic children and those exhibiting language delays are known to have similar, overlapping deficits.

Researchers theorize that since the analysis is not based on words but on sound patterns, the technique could be used with children speaking any language.

"This automated application makes it possible to monitor development in a completely objective way," said lead researcher Dr. D. Kimbrough Oller, a professor at the University of Memphis.

The research is published in the July online edition of the 'Proceedings of the National Academy of Sciences.'

Autism Spectrum Disorders
Autism is a neurobiological disorder that causes severe and pervasive impairment in the ability to communicate and relate to others.

The disorder is usually first diagnosed in early childhood. The causes for the condition are unclear though researchers believe environmental, biologic and genetic factors play a role.

There is no medical test for this complex biological condition. Parents and doctors work together to analyze a child's behavior and development to make a diagnosis.

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