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With the emphasis on healthcare, early childhood education, and fitness,non-invasive measurement and recognition methods have received more attention.Pressure sensing has been extensively studied due to its advantages of simplestructure, easy access, visualization application, and harmlessness. This paperintroduces a smart pressure e-mat (SPeM) system based on a piezoresistivematerial Velostat for human monitoring applications, including sleepingpostures, sports, and yoga recognition. After a subsystem scans e-mat readingsand processes the signal, it generates a pressure image stream. Deep neuralnetworks (DNNs) are used to fit and train the pressure image stream andrecognize the corresponding human behavior. Four sleeping postures and fivedynamic activities inspired by Nintendo Switch Ring Fit Adventure (RFA) areused as a preliminary validation of the proposed SPeM system. The SPeM systemachieves high accuracies on both applications, which demonstrates the highaccuracy and generalization ability of the models. Compared with other pressuresensor-based systems, SPeM possesses more flexible applications and commercialapplication prospects, with reliable, robust, and repeatable properties.

Smart Pressure e-Mat for Human Sleeping Posture and Dynamic Activity Recognition