Clues From Crying: New Tool Could Shed Light on Babies' Health
Researchers say a new cry analyzer is a noninvasive way to catch early signs of certain medical conditions in infants.
Parents can often decipher from the nature of a baby’s cry whether he’s hungry or sleepy, but a new tool from researchers in Rhode Island promises to take crying assessment to a whole new level.
A team from Brown University and Women & Infants Hospital of Rhode Island has developed a computer-based tool to analyze babies’ cries—analysis that could provide important clues about a baby’s health and signal possible neurological problems or developmental disorders.
“There are lots of conditions that might manifest in differences in cry acoustics,” Stephen Sheinkopf, assistant professor of psychiatry and human behavior at Brown, said in a written statement. “…Cry analysis can be a noninvasive way to get a measurement of these disruptions in the neurobiological and neurobehavioral systems in very young babies.”
The analyzer evaluates 80 different parameters, including volume and frequency. The developers of the analyzer plan to make it available for use by researchers around the world.
Sheinkopf plans to use the tool to study crying and autism.
“We’ve known for a long time that older individuals with autism produce sounds or vocalizations that are unusual or atypical,” he said. “So vocalizations in babies have been discussed as being useful in developing early identification tools for autism. That’s been a major challenge. How do you find signs of autism in infancy?”
If the cry analyzer became a standard tool for doctors, some parents say they would support its use.
It’s “a huge window into the future of our child’s health,” she wrote in a Babble post on the subject. “I would absolutely use this tool to analyze my child’s cry if the situation were to arise.”
Others said they’d hold off, citing concerns about false positives and “labeling” children too early.
“According to all of these tests we’re constantly bombarded with, every kid needs to be classified. If they had been around when we were young, they would have found something wrong with every one of us,” said suburban New York mom and school teacher Stephanie X. DiLeonardo.
“If something were wrong with my kid, I would feel a lot more equipped to understand and deal with it after seeing her have difficulties (and watching how she tries to solve problems) than being told that a machine found something,” she said.
A paper describing the tool has been published in the “Journal of Speech, Language and Hearing Research.”
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