A System for Activity Recognition Using Multi-Sensor Fusion

被引：0

作者：

Gao, Lei ^{[1
]}

Bourke, Alan K. ^{[1
]}

Nelson, John ^{[1
]}

机构：

[1] Univ Limerick, Dept Elect & Comp Engn, Fac Sci & Engn, Limerick, Ireland

来源：

2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2011年

关键词：

TRIAXIAL ACCELEROMETER;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper proposes a system for activity recognition using multi-sensor fusion. In this system, four sensors are attached to the waist, chest, thigh, and side of the body. In the study we present two solutions for factors that affect the activity recognition accuracy: the calibration drift and the sensor orientation changing. The datasets used to evaluate this system were collected from 8 subjects who were asked to perform 8 scripted normal activities of daily living (ADL), three times each. The Naive Bayes classifier using multi-sensor fusion is adopted and achieves 70.88%-97.66% recognition accuracies for 1-4 sensors.

引用

页码：7869 / 7872

页数：4

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