Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
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DOI：
10.1016/j.inffus.2016.09.005
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发表时间：
2017-05-01
影响因子：
18.6
通讯作者：
Fortino, Giancarlo
中科院分区：
文献类型：
--
作者：
Gravina, Raffaele;Alinia, Parastoo;Fortino, Giancarlo
身体传感器网络（BSN）已经成为医疗保健、健身、智慧城市和许多其他引人注目的物联网（IoT）应用中的许多应用领域的革命性技术。大多数商业可用的系统假设单个设备监视过多的用户信息。实际上，BSN技术正在向多设备同步测量环境过渡;因此，来自多个潜在异构传感器源的数据融合正在成为一项基本而重要的任务，直接影响应用程序性能。然而，直到最近，研究人员才开始开发有效融合BSN数据的技术解决方案。据我们所知，社区目前缺乏一个全面的审查国家的最先进的多传感器融合技术在该地区的BSN。本调查讨论了明确的动机和多传感器数据融合的优势，特别是侧重于身体活动识别，旨在提供一个系统的分类和共同的比较框架的文献，通过识别不同层次（数据，功能和决策）的数据融合设计选择的独特属性和参数。该调查还涵盖了情感识别和一般健康领域的数据融合，并介绍了未来在BSN领域多传感器融合研究的相关方向和挑战。(C)2016爱思唯尔B. V.保留所有权利。
Body Sensor Networks (BSNs) have emerged as a revolutionary technology in many application domains in health-care, fitness, smart cities, and many other compelling Internet of Things (loT) applications. Most commercially available systems assume that a single device monitors a plethora of user information. In reality, BSN technology is transitioning to multi-device synchronous measurement environments; fusion of the data from multiple, potentially heterogeneous, sensor sources is therefore becoming a fundamental yet non-trivial task that directly impacts application performance. Nevertheless, only recently researchers have started developing technical solutions for effective fusion of BSN data. To the best of our knowledge, the community is currently lacking a comprehensive review of the state-of-the-art techniques on multi-sensor fusion in the area of BSN. This survey discusses clear motivations and advantages of multi-sensor data fusion and particularly focuses on physical activity recognition, aiming at providing a systematic categorization and common comparison framework of the literature, by identifying distinctive properties and parameters affecting data fusion design choices at different levels (data, feature, and decision). The survey also covers data fusion in the domains of emotion recognition and general-health and introduce relevant directions and challenges of future research on multi-sensor fusion in the BSN domain. (C) 2016 Elsevier B.V. All rights reserved.