Biomedical sensors data fusion algorithm for enhancing the efficiency of fault-tolerant systems in case of wearable electronics device

Aileni Raluca Maria, Pașca Sever, Valderrama Carlos
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引用次数: 8

Abstract

The paper presents multisensor data fusion process and algorithm modeling. The multisensor system consists in a set of heterogeneous medical sensors for biomedical electronics. Multisensor data fusion is based on artificial intelligence, pattern recognition and statistical estimation. The goal of the modeling is to reduce uncertainty of the data values tracked from sensors. The big data collected from sensors can contain also noisy data and repetitive one which can lead to inefficiencies in data storage. In this case is appropriate to reduce the errors by using algorithms and data fusion.
用于提高可穿戴电子设备容错系统效率的生物医学传感器数据融合算法
介绍了多传感器数据融合过程和算法建模。多传感器系统由一组异构医学传感器组成,用于生物医学电子学。多传感器数据融合基于人工智能、模式识别和统计估计。建模的目的是减少从传感器跟踪的数据值的不确定性。从传感器收集的大数据也可能包含噪声数据和重复数据,这可能导致数据存储效率低下。在这种情况下,采用算法和数据融合来减小误差是合适的。
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