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An automatic data mining method to detect abnormal human behaviour using physical activity measurements

delete2014-12-01
delete35
PRE
AI
J
Juan Luís Carús *
V
Víctor Peláez
G
Gloria López
M
Miguel Ángel Fernández
E
Eduardo Álvarez-Álvarez
G
Gabriel Díaz
DOI:10.1016/j.pmcj.2014.09.007delete
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摘要

摘要

En 中文
Abnormal human behaviour detection under free-living conditions is a reliable method to detect disorders and diseases in healthcare applications. The problem with current methods to detect human behaviour changes is the use of supervised techniques that require human intervention. This work proposes an automatic data mining method based on physical activity measurements. Abnormal human behaviour is detected as an increase or decrease of the physical activity according to the historical data. Human behaviour is evaluated in real time grading its abnormality. The method has been validated involving users with a precision of 100% and a recall of 92%. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Automatic method
Abnormal human behaviour
Data mining method
Real time analysis
Physical activity measurement
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期刊

Pervasive and Mobile Computing 封面图
Pervasive and Mobile Computing
IF:
3.5
论文数:
1.5K
被引数:
2.2K

机构

U
universidad nacional de educacion a distancia (uned)
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被引数: 7
U
University of Oviedo
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被引数: 15
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