Sleep-wake identification in infants: heart rate variability compared to actigraphy

Heart rate variability and actigraphy offer alternative techniques for sleep-wake identification compared to manual sleep scoring from a polysomnograph. The advantages include high accuracy, simplicity of use, and low intrusiveness. These advantages are valuable for determining sleep-wake states in such highly sensitive groups as infants. A learning vector quantization neural network was tested as a predictor. The accuracy of the neural network was compared to "gold standard" hand-scored polysomnographs. The prediction results are in agreement with other studies, thus validating the suggested methodology.