Automatic detection of sleep macrostructure based on a sensorized T-shirt Conference Paper uri icon


  • In the present work we apply a fully automatic procedure to the analysis of signal coming from a sensorized Tshit, worn during the night, for sleep evaluation. The goodness and reliability of the signals recorded trough the T-shirt was previously tested, while the employed algorithms for feature extraction and sleep classification were previously developed on standard ECG recordings and the obtained classification was compared to the standard clinical practice based on polysomnography (PSG). In the present work we combined Tshirt recordings and automatic classification and could obtain reliable sleep profiles, i.e. the sleep classification in WAKE, REM (rapid eye movement) and NREM stages, based on heart rate variability (HRV), respiration and movement signals. © 2010 IEEE.

publication date

  • 2010-01-01