SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWB

Recognizing movements during sleep is crucial for the monitoring of patients with sleep disorders, and the utilization of ultra-wideband (UWB) radar for the classification of human sleep postures has not been explored widely. This study investigates the performance of an off-the-shelf single antenna...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2021-04, Vol.25 (4), p.1305-1314
Hauptverfasser:	Piriyajitakonkij, Maytus, Warin, Patchanon, Lakhan, Payongkit, Leelaarporn, Pitshaporn, Kumchaiseemak, Nakorn, Suwajanakorn, Supasorn, Pianpanit, Theerasarn, Niparnan, Nattee, Mukhopadhyay, Subhas Chandra, Wilaiprasitporn, Theerawit
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Biomedical monitoring Classification contactless sensing Convolution Data augmentation Deep learning Doppler radar Heart rate Human activity recognition Learning Monitoring Moving object recognition Neural networks Posture Sleep Sleep disorders Sleep monitoring sleep posture Time series Ultra wideband radar Ultrawideband radar UWB radar
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