Wavelet transforms based noise reduction for body vibration signals in wireless sensor networks

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2 Citations (Scopus)

Abstract

In this paper we present a novel model of noise removal for the human body vibration signals in wireless sensor networks, which assumes which assumes that the noise appears not continuously or periodically but sparsely and it is the summary of some transient signals at discrete time. Furthermore, on the base of the model a new algorithm is developed which takes advantages of wavelet transforms to remove the noise by the method of processing scale functions coefficients at each level. A wavelet block is designed to implement the function of the proposed method. The results of the simulation and experiments indicate that the new algorithm has removed the noise of the signals successfully in the case of both human's one discrete action and continuous activities.

Original languageEnglish
JournalIEEJ Transactions on Electronics, Information and Systems
Volume127
Issue number6
Publication statusPublished - 2007

Fingerprint

Noise abatement
Wavelet transforms
Wireless sensor networks
Processing
Experiments

Keywords

  • Architecture
  • Body vibration signals
  • Noise reduction

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

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abstract = "In this paper we present a novel model of noise removal for the human body vibration signals in wireless sensor networks, which assumes which assumes that the noise appears not continuously or periodically but sparsely and it is the summary of some transient signals at discrete time. Furthermore, on the base of the model a new algorithm is developed which takes advantages of wavelet transforms to remove the noise by the method of processing scale functions coefficients at each level. A wavelet block is designed to implement the function of the proposed method. The results of the simulation and experiments indicate that the new algorithm has removed the noise of the signals successfully in the case of both human's one discrete action and continuous activities.",
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AB - In this paper we present a novel model of noise removal for the human body vibration signals in wireless sensor networks, which assumes which assumes that the noise appears not continuously or periodically but sparsely and it is the summary of some transient signals at discrete time. Furthermore, on the base of the model a new algorithm is developed which takes advantages of wavelet transforms to remove the noise by the method of processing scale functions coefficients at each level. A wavelet block is designed to implement the function of the proposed method. The results of the simulation and experiments indicate that the new algorithm has removed the noise of the signals successfully in the case of both human's one discrete action and continuous activities.

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