ニューラルネットワークを用いた起床検知システムの開発

概要

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We have developed a behavior detection system using a neural network (NN). The system detects dangerous behaviors that are almost falling from a bed and having fallen from the bed. The system uses captured pictures with a WEB camera for detection. The system classifies their behavior into five states using the NN. Five states are lying in the bed, being sitting up in the bed, sitting in the bed, almost falling from the bed and having fallen from the bed. Then, we define almost falling and having fallen from the bed as dangerous behavior. Moreover, we define lying in the bed, being sitting up in the bed, sitting in the bed as safety behavior. We proposed a final detection rule by which the system classifies their behavior into two states. Finally, a detection ability of the system is evaluated. From the experiment results, the detection rate of dangerous behavior is shown 81.7% using the proposed system.
社団法人電気学会の論文
2008-11-01