Characterization of movements during restless sleep in children: a pilot study

Abstract

Actigraphy is effective at monitoring circadian rhythms, but often misidentifies periods of restless sleep (defined here as sleep periods with movement) as wake, and periods of quiet wake as sleep. This limitation restricts the effectiveness of actigraphy for investigating sleep disorders. Our objective in this study was to investigate a time-frequency representation of movement during sleep and wake which could ultimately aid in improving classification performance by reducing false wake detections. As a pilot study, we investigate the characteristics of manually labelled movements from six patients (aged 6-12 years, 3 male) during sleep and wake using the over complete discrete wavelet decomposition. The difference between the median wavelet coefficients were analyzed for 30 movement segments from six movement categories during sleep and wake. We found that, in general, the temporal location of high energy coefficients and the energy of the high frequency bands differed between movements during sleep and wake. This indicates that we are able to differentiate movement during sleep and wake with a time-frequency representation. This representation may improve the sleep and wake classification performance by identifying movements specific to sleep and wake. This will likely improve the poor specificity inherent in conventional actigraphy.