Online classifier construction algorithm for human activity detection using a tri-axial accelerometer

Yen Ping Chen, Jhun Ying Yang, Shun Nan Liou, Gwo Yun Lee, Jeen Shing Wang

研究成果: Article同行評審

93 引文 斯高帕斯(Scopus)

摘要

This paper presents an online construction algorithm for constructing fuzzy basis function (FBF) classifiers that are capable of recognizing different types of human daily activities using a tri-axial accelerometer. The activity recognition is based on the acceleration data collected from a wireless tri-axial accelerometer module mounted on users' dominant wrists. Our objective is to enable users to: (1) online add new training samples to the existing classes for increasing the recognition accuracy, (2) online add additional classes to be recognized, and (3) online delete an existing class. For this objective we proposed a dynamic linear discriminant analysis (LDA) which can dynamically update the scatter matrices for online constructing FBF classifiers without storing all the training samples in memory. Our experimental results have successfully validated the integration of the FBF classifier with the proposed dynamic LDA can reduce computational burden and achieve satisfactory recognition accuracy.

原文English
頁(從 - 到)849-860
頁數12
期刊Applied Mathematics and Computation
205
發行號2
DOIs
出版狀態Published - 2008 11月 15

All Science Journal Classification (ASJC) codes

  • 計算數學
  • 應用數學

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