標題: Personalized Smartphone Wearing Behavior Analysis
作者: Lin, Yen-Hsuan
Chuang, Yi-Ta
資訊工程學系
Department of Computer Science
關鍵字: Mobility;Next generation smartphone;User context;Wearing position;Wearing behavior
公開日期: 1-一月-2014
摘要: Next generation smartphones have the ability to sense user contexts such as mobility, device wearing position, location, activity, emotion, health condition. Many apps utilize user contexts to provide innovative services, e.g., pedometer, advanced navigation and location based services. Two of the most important user contexts are mobility patterns (still and walk) and device wearing positions (hand, arm, chest, waist and thigh). We call these two user contexts "wearing behavior". In this paper, we propose a 3-stage framework to recognize smartphone wearing behaviors by utilizing sensor data from smartphones. The framework starts with data preprocessing to extract sensor features and generate ground truths. After the data preprocessing, a threshold based finite state machine utilizes the sensor features to determine whether the smartphone is attached or not. Finally, a decision tree model is built based on the ground truth to determine the wearing behaviors. The experiment results show that our approach can achieve 94 % accuracy in average.
URI: http://dx.doi.org/10.1007/978-3-319-13186-3_30
http://hdl.handle.net/11536/125148
ISBN: 978-3-319-13186-3; 978-3-319-13185-6
ISSN: 0302-9743
DOI: 10.1007/978-3-319-13186-3_30
期刊: TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING
Volume: 8643
起始頁: 318
結束頁: 328
顯示於類別:會議論文


文件中的檔案:

  1. 000354705300030.pdf