Abstract
Sleep disturbances have been reported as one of the most common symptoms among people living with dementia (PLWD). Few technologies to longitudinally monitor sleep across the 24-h day are available. Here, we develop machine learning models that use multimodal data to accurately monitor sleep across the day and night.