In-Bed Posture Classification

Abstract

The growing trend of the population age contributes to the accumulation of patients insocial facilities and in-home care, which leads to growing chronic diseases. Modern systems try toimprove the effectiveness of health care interventions. Our work aims to create a widely applicableplatform that combines the measurement of in-bed position with another’s negative states. All thesephysical influences are mainly the cause of chronic tissue damage (pressure ulcers). Processing ofthe pressure distribution on the bed is a more dimension problem. The mentioned data are multimodal.Therefore, we used the machine learning (ML) method to obtain the properties.