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首页> 外文期刊>International journal of telemedicine and applications >Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources
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Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources

机译：用于数据 - 科学型预防健康管理系统的多传感器融合方法：异构数据源分散数据收集方法的概念和开发

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Investigations in preventive and occupational medicine are often based on the acquisition of data in the customer’s daily routine. This requires convenient measurement solutions including physiological, psychological, physical, and sometimes emotional parameters. In this paper, the introduction of a decentralized multi-sensor-fusion approach for a preventive health-management system is described. The aim is the provision of a flexible mobile data-collection platform, which can be used in many different health-care related applications. Different heterogeneous data sources can be integrated and measured data are prepared and transferred to a superordinated data-science-oriented cloud-solution. The presented novel approach focuses on the integration and fusion of different mobile data sources on a mobile data collection system (mDCS). This includes directly coupled wireless sensor devices, indirectly coupled devices offering the datasets via vendor-specific cloud solutions (as e.g., Fitbit, San Francisco, USA and Nokia, Espoo, Finland) and questionnaires to acquire subjective and objective parameters. The mDCS functions as a user-specific interface adapter and data concentrator decentralized from a data-science-oriented processing cloud. A low-level data fusion in the mDCS includes the synchronization of the data sources, the individual selection of required data sets and the execution of pre-processing procedures. Thus, the mDCS increases the availability of the processing cloud and in consequence also of the higher level data-fusion procedures. The developed system can be easily adapted to changing health-care applications by using different sensor combinations. The complex processing for data analysis can be supported and intervention measures can be provided.
机译：预防性和职业医学的调查往往基于收购客户日常常规的数据。这需要方便的测量解决方案，包括生理，心理，物理，有时情绪参数。在本文中，描述了用于预防健康管理系统的分散多传感器融合方法的引入。目的是提供一种灵活的移动数据集合平台，可用于许多不同的医疗保健相关应用。可以集成不同的异构数据源，并将测量数据准备并转移到超级数据 - 科学为导向的云解决方案。呈现的新方法侧重于在移动数据收集系统（MDC）上的不同移动数据源的集成和融合。这包括直接耦合的无线传感器设备，间接耦合的设备通过供应商特定的云解决方案提供数据集（例如，例如，Fitbit，San Francisco，USA和诺基亚，埃斯科，芬兰）和问卷，以获得主观和客观参数。 MDCS用作特定于用户的接口适配器和数据集中器，从数据 - 科学导向的处理云分散。 MDC中的低级数据融合包括数据源的同步，所需数据集的各个选择以及预处理过程的执行。因此，MDC增加了处理云的可用性，并因此也是更高级别的数据融合程序的可用性。通过使用不同的传感器组合，开发系统可以很容易地适应改变医疗保健应用。可以支持数据分析的复杂处理，并且可以提供干预措施。

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