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It’s possible that research on autism just had a breakthrough. Professor Steven Warren of Kansas University (KU) said in a new study that autism may be diagnosed through new technology involving vocal analysis. It could lead to much earlier diagnosis and more effective therapies for children with Autism Spectrum Disorders (ASD).
The median age for diagnosis of ASD in the United States is 5.7 years, but it could be lowered to 18 months, Warren said in a statement from KU.
The technology is called Language Environment Analysis, or LENA, a system consisting of a digital language processor and language analysis software. It records and separates infant vocalizations from other noises, allowing researchers to analyze the acoustics, according to a press release issued by KU.
“This technology could help pediatricians screen children for ASD to determine if a referral to a specialist for a full diagnosis is required and get those children into earlier and more effective treatments,” said Warren, who was among the first to see the technology’s potential for ASD screening.
The research team, led by D. Kimbrough Oller, professor and chair of excellence in audiology and speech language pathology at the University of Memphis, discovered that preverbal vocalizations of infants with autism are different from normal infants. The discovery allowed the team to predict which infants would develop ASD with 86 percent accuracy.
Starting in 2006, 232 children, with the cooperation of their parents, participated in the research and produced a total of 1,486 all-day recordings.
The difference in vocalizations of children with ASD has been noticed before by parents and scientists, but massive experiments were unable to be conducted due to the lack of technology. LENA is portable and simple to use.
“A small number of studies had previously suggested that children with autism have a markedly different vocal signature, but until now, we have been held back from using this knowledge in clinical applications by the lack of measurement technology,” Warren said.
He added that the technology could be used to screen autism in any language since the analysis is based on sound patterns and not words.
The report appeared in the July 19 online issue of Proceedings of the National Academy of Sciences.
