Wavelet packet modelling of infant sleep state using heart rate data

We show how a recently developed wavelet packet modelling methodology could be useful for infant sleep state classification using heart rate data. The suggested approach produces adequate classification rates when applied to recordings from an infant who was placed to bed at night at different ages. As well as classification, this approach gives us valuable information about the relationship between sleep state and heart rate. The statistical model tells us which sorts of wavelet packets of heart rate are most important for classifying sleep state.