ChatterBaby, a mobile app developed at UCLA that analyzes the acoustics of a baby’s cry to identify it as fussy, hungry or painful, has been used in new research exploring the ‘mystery’ crying of colic.
The cause of colic – episodes when an otherwise healthy infant cries for three to four hours a day for weeks at a time -- is unknown. While few colicky infants are ultimately diagnosed with serious underlying disease, that’s of little comfort to the crying babies or their weary parents trying to soothe them.
, assistant professor at the UCLA Semel Institute for Neuroscience and Human Behavior, and a team of researchers originally developed the ChatterBaby app to help deaf parents recognize and understand their baby’s cries so they could respond appropriately.
The app – useful for those with or without hearing impairment – was created by uploading audio samples of more than 2,000 infant cries, then building and testing algorithms that translated the cries into three categories: pain, hunger and fussiness. The algorithms correctly flagged pain cries more than 90% of the time when babies received vaccinations or had their ears pierced.
In this study, published in , the scientists, using the ChatterBaby app, found that cries from babies with parent-described colic had a 73% chance of being characterized as painful by the algorithm. These colicky cries were acoustically similar to those of babies receiving vaccines or other painful stimuli, but different from fussy or hungry cries, suggesting that pain and colic may be related.
Colic crying peaks at night, so parents dealing with unrelenting wails often feel isolated and ineffective at soothing what they believe is just a fussy baby. The similarity of colic and pain cries validates the distress parents can feel when hearing this crying, and suggests that parents may be unconsciously attuned to pain signatures in their baby's cry.
The fact that these distinctions are now recognized by scientific data – and that colicky babies may be more than “just fussy” – may offer some consolation to exhausted parents.
Crying-pattern studies like these can provide insight into whether certain patterns can later be associated with specific infant developmental issues or conditions. Currently, the ChatterBaby research group is building algorithms to distinguish the cries of babies with major medical diagnoses such as stroke or seizures, and then identifying how these cries may differ from those of children who develop disorders such as autism.
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