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论文类型：期刊论文

发表时间：2020-05-01

发表刊物：INFORMATION FUSION

收录刊物：EI、SCIE

卷号：57

页面范围：15-26

ISSN号：1566-2535

关键字：Body sensor network; Multi-sensor fusion; Medical human-robot interaction; Neural network; Fusion decision

摘要：With the development of sensor and communication technologies, body sensor networks(BSNs) have become an indispensable part of smart medical services by monitoring the real-time state of users. Due to introducing of smart medical robots, BSNs are not related to users, but also responsible for data acquisition and mull-sensor fusion in medical human-robot interaction scenarios. In this paper, a hybrid body sensor network architecture based on mull-sensor fusion(HBMF) is designed to support the most advanced smart medical services, which combines various sensor, communication, robot, and data processing technologies. The infrastructure and system functions are described in detail and compared with other architectures. Especially, A mull-sensor fusion method based on interpretable neural network(MFIN) for BSNs in medical human-robot interaction scenario is designed and analyzed to improve the performance of fusion decision-making. Compared with the current mull-sensor fusion methods, our design guarantees both the flexibility and reliability of the service in the medical human-robot interaction scenario.