Matthew Lynch, Tech Edvocate
For their research, the scientists obtained information from USC’s Infant Neuromotor Control Laboratory. This information included data about the motor movements of infants obtained from sensors strapped to the infants’ ankles. The sensors collected raw movement data from an accelerometer, gyroscope, and magnetometer. An algorithm that is able to classify typical (TD) and delayed development (AR), was then used to further analyze the observable differences in spontaneous movements of infants with TD and AR. Then the researchers came up with a prediction model that was able to do the calculations and make the predictions.
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