Motion-pattern recognition system using a wavelet-neural network

研究成果: Article同行評審

6 引文 斯高帕斯(Scopus)

摘要

This paper presents a wavelet-neural network recognition system for personal fitness assistance and elderly daily activity monitoring applications. This discrete wavelet transform radial basis neural network (DWT-RBNN) analyzes vibration induced by human motions, and identifies motion status automatically. The 3-D vibration signals are measured by integrated accelerometer chip, and then DWT extracts vibration features. Local energy of extracted feature is calculated and used by RBNN. A multi-channel RBNN is designed and used for recognition. The computation burden is reduced because of the DWT pre-processing. From experiment results, RBNN shows successful recognition capability. This paper also presents flow diagram to determine engineering parameters for the present and future product developments.

原文English
文章編號8625510
頁(從 - 到)170-178
頁數9
期刊IEEE Transactions on Consumer Electronics
65
發行號2
DOIs
出版狀態Published - 2019 五月

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Electrical and Electronic Engineering

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