Personalized Sleep Spindle Detection in Whole Night Polysomnography.

The present study proposes a new personalized sleep spindle detection algorithm, suggesting the importance of an individualized approach. We identify an optimal set of features that characterize the spindle and exploit a support vector machine to distinguish between spindle and nonspindle patterns. The algorithm is assessed on the open source DREAMS database, that contains only selected part of the polysomnography, and on whole night polysomnography recordings from the SPASH database. We show that on the former database the personalization can boost sensitivity, from 84.2% to 89.8%, with a slight increase in specificity, from 97.6% to 98.1%. On a whole night polysomnography instead, the algorithm reaches a sensitivity of 98.6% and a specificity of 98.1%, thanks to the personalization approach. Future work will address the integration of the spindle detection algorithm within a sleep scoring automated procedure.

Self-organization of star-shaped columnar liquid crystals with a coaxial nanophase segregation revealed by a combined experimental and simulation approach.

Fully consistent X-ray data and molecular dynamics simulations on new star-shaped liquid crystals yield two nanosegregated architectures with a coaxial stacking of two functional discotic units: tris(triazolyl)triazine and triphenylene. Analysis of lattice order along the principal axes reveals preferential staggered arrangement of the stacked molecules in the columnar assembly.