Smartphone-based Transport Mode Detection for Elderly Care

被引：0
|
作者：
Cardoso, Nuno [1 ,2 ]
Madureira, Joao [1 ]
Pereira, Nuno [2 ]
机构：
[1] Fraunhofer Portugal AICOS, Oporto, Portugal
[2] Polytech Porto, Sch Engn, Dept Comp Engn, Oporto, Portugal
来源：
2016 IEEE 18TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM) | 2016年
关键词：
Inertial Sensors; Accelerometer; Classification Algorithms; Transport Detection; Smartphones;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Smartphones are everywhere, and they are a very attractive platform to perform unobtrusive monitoring of users. In this work, we use common features of modern smartphones to build a human activity recognition (HAR) system for elderly care. We have built a classifier that detects the transport mode of the user including whether an individual is inactive, walking, in bus, in car, in train or in metro. We evaluated our approach using over 24 hours of transportation data from a group of 15 individuals. Our tests show that our classifier can detect the transportation mode with over 90% accuracy.
引用
收藏
页码：261 / 266
页数：6
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