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We present a new methodology to detect and characterize sleep spindles (SSs), based on the nonlinear algorithms, empirical-mode decomposition, and Hilbert-Huang transform, which provide adequate temporal and frequency resolutions in the electroencephalographic analysis. In addition, the application of fuzzy logic allows to emulate expert's procedures.(More)
OBJECTIVE Epidemiological evidence shows an inverse relationship between sleep duration and overweight/obesity risk. However, there are few polysomnographic studies that relate the organization of sleep stages to pediatric overweight (OW). We compared sleep organization in otherwise healthy OW and normal-weight (NW) 10-year-old children. SUBJECTS(More)
We present an automated multiple-step tool to identify Rapid Eye Movements (REMs) in the polysomnogram, based on modeling expert criteria. It begins by identifying the polysomnogram segments compatible with REMs presence. On these segments, high-energy REMs are identified. Then, vicinity zones around those REMs are defined, and lesser-energy REMs are sought(More)
  • Karla A. Bascuñán, Rodrigo Valenzuela, Rodrigo Chamorro, Alejandra Valencia, Cynthia Barrera, Claudia Puigrredon +2 others
  • 2014
Chilean diets are characterized by a low supply of n-3 polyunsaturated fatty acids (n-3 PUFA), which are critical nutrients during pregnancy and lactation, because of their role in brain and visual development. DHA is the most relevant n-3 PUFA in this period. We evaluated the dietary n-3 PUFA intake and erythrocyte phospholipids n-3 PUFA in Chilean(More)
A methodology to detect sleep apnea/hypopnea events in the respiratory signals of polysomnographic recordings is presented. It applies empirical mode decomposition (EMD), Hilbert-Huang transform (HHT), fuzzy logic and signal preprocessing techniques for feature extraction, expert criteria and context analysis. EMD, HHT and fuzzy logic are used for artifact(More)
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