Comparison of Data-Driven Models for Cleaning eHealth Sensor Data: Use Case on ECG Signal

被引：4

作者：

Koren, Ana ^{[1
]}

Jurcevic, Marko ^{[1
]}

Prasad, Ramjee ^{[2
]}

机构：

[1] Univ Zagreb, Fac Elect Engn & Comp, Unska 3, Zagreb 10000, Croatia

[2] Aarhus Univ, Dept Business Dev & Technol, CTIF GLOBAL CAPSULE, Herning, Denmark

来源：

WIRELESS PERSONAL COMMUNICATIONS | 2020年 / 114卷 / 02期

关键词：

Wireless sensor networks; Data cleaning; Data quality; Wearable sensors; eHealth; Healthcare; PHYSICAL-ACTIVITY; DECISION TREES;

D O I：

10.1007/s11277-020-07435-7

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Electronic Health Records (EHRs) enabled to store and process data recorded by sensors would mean standard-based personalization of medical services and would be a step further to guaranteeing a seamless care access. However, sensor data is subject to several sources of faults and errors which may further lead to imprecise or even incorrect and misleading answers. Thus, it is pivotal to ensure the quality of data collected from e.g. wearable sensors in wireless sensor networks for it to be used in a formal EHR. This article gives comparison of different data-driven models in cleaning eHealth sensor data from wireless sensor networks in order to make sure the data collected is precise and relevant and as such, may be included into a formal EHR. Furthermore, it then suggests optimization of the selected models with the goal of improving their results.

引用

页码：1501 / 1517

页数：17

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