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In the present work we apply a fully automatic procedure to the analysis of signal coming from a sensorized T-shit, 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...
Extreme environments such as high altitude represent a challenging testbed for both people and instruments. During a recent expedition to the slopes of Mt. Everest, (Highcare Expedition), we monitored ECG, respiration, oxygen saturation and posture in five climbers during sleep. Data were collected by using a recently developed textile-based wearable system (the MagIC system). The polysomnographic...
In this paper, we discuss the possibility of performing a sleep evaluation from signals, which are not usually used for this purpose. In particular, we take into consideration the heart rate variability (HRV) and respiratory signals for automatic sleep staging, arousals detection, and apnea recognition. This is particularly useful for wearable or textile devices that could be employed for home monitoring...
Sleep disorders affect over 40 million patients and represent a significant a significant risk factor for many, often life threatening diseases. Technologies available for diagnostics and treatment typically involve the recording of key biomedical signals including ECG, EEG, EMG, SpO2, and respiration. Overnight measurement of such parameters is often compromised by the discomfort imposed by conventional...
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