Abstract
AbstractSleep is an indispensable part of people’s daily life, so it is particularly important to monitor their sleep state. Based on this, this paper proposes a respiratory monitoring method based on a knowledge graph to monitor the sleep state. Firstly, the data collected by the sensor terminal and related disease information are identified by named entity recognition and relationship extraction, and the knowledge graph of respiratory monitoring data is constructed, and then it is visualized through the graph database Neo4j. Finally, on the basis of the existing knowledge graph, the relationship model between respiratory monitoring index and disease is established to realize the perceptual analysis of human health state, so as to achieve the purpose of disease prediction.KeywordsKnowledge graphRespiratory monitoringApriori algorithmData discretizationSmart bracelet
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