Abstract: Methods and apparatuses for automatically identifying sleep apnea in a subject based on load cell signal data obtained from load cells coupled with one or more supports of a bed are disclosed. In one example approach, a method comprises continuously collecting load cell signal data from one or more load cells positioned below one or more supports of a bed, processing the signal data to obtain processed signal data, extracting features from the processed signal data, calculating a sleep apnea severity parameter based on the extracted features via a model, and identifying sleep apnea in the subject based on the sleep apnea severity parameter.

Abstract: Embodiments provide systems, methods and apparatuses for monitoring the sleep of a subject in a home environment. In embodiments, load cells placed under bed supports may be coupled to a computing device that may process the load cell data to detect disordered breathing. In some embodiments, a computing device may apply a pattern recognition algorithm to load cell data to distinguish between normal movements and movements associated with a sleep disorder. In an embodiment, apparatuses and methods for monitoring sleep may perform functions associated with detection of sleep disturbances and/or identify a sleep disorder.