Night-time cardiac autonomic modulation as a function of sleep-wake stages is modified in otherwise healthy overweight adolescents.

Objective: Even though sympathetic dominance during the daytime period is well known, currently, scarce data exist on autonomic nervous system (ANS) regulation during sleep in pediatric obesity. We aimed to evaluate sleep cardiac ANS regulation in normal-weight (NW) and overweight and obese (OW) adolescents.

Patients/methods: In this study, 60 healthy adolescents (15.

Automated detection of apnea/hypopnea events in healthy children polysomnograms: preliminary results.

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 detection and preliminary detection of respiration signal zones with significant variations in the amplitude of the signal; feature extraction, expert criteria and context analysis are used to characterize and validate the respiratory events.

Automated sleep-spindle detection in healthy children polysomnograms.

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. Additionally, we built a database of 56 all-night polysomnographic recordings from children for training and testing, which is among the largest annotated databases published on the subject.

Dual approach for automated sleep spindles detection within EEG background activity in infant polysomnograms.

An automated system for sleep spindles detection within EEG background activity, combining two different approaches, is presented. The first approach applies detection criteria on the sigma-band filtered EEG signal, including fuzzy thresholds. The second approach mimics an expert's procedure.