Literature DB >> 17442321

Adaptive usage of the Butterworth digital filter.

Koray S Erer1.   

Abstract

The Butterworth lowpass filter is a conventional tool that has been commonly used in gait analysis applications. Its operation mainly depends on the selection of the cut-off frequency, which must be done based on the condition of the raw signal assuming that it is stationary. This tool is unable to deal with nonstationary signals especially if impact is involved. In this paper, a modified version of the Butterworth filter that can handle nonstationary signals is presented. The new filter has a variable cut-off frequency distribution defined for each data point, which is determined by local signal characteristics. Because of its adaptive nature, it is possible for the filter to accommodate changes in the frequency content of the signal.

Mesh:

Year:  2007        PMID: 17442321     DOI: 10.1016/j.jbiomech.2007.02.019

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  6 in total

1.  Effects of low-pass filtering on acoustic analysis of voice.

Authors:  Julia K MacCallum; Aleksandra E Olszewski; Yu Zhang; Jack J Jiang
Journal:  J Voice       Date:  2010-03-25       Impact factor: 2.009

2.  Functional and evolutionary anatomy of the African suckermouth catfishes (Siluriformes: Mochokidae): convergent evolution in Afrotropical and Neotropical faunas.

Authors:  Tom Geerinckx; Barbara De Kegel
Journal:  J Anat       Date:  2014-05-20       Impact factor: 2.610

3.  The extensibility of the plantar fascia influences the windlass mechanism during human running.

Authors:  Lauren Welte; Luke A Kelly; Sarah E Kessler; Daniel E Lieberman; Susan E D'Andrea; Glen A Lichtwark; Michael J Rainbow
Journal:  Proc Biol Sci       Date:  2021-01-20       Impact factor: 5.349

4.  A novel approach to solve the "missing marker problem" in marker-based motion analysis that exploits the segment coordination patterns in multi-limb motion data.

Authors:  Peter Andreas Federolf
Journal:  PLoS One       Date:  2013-10-30       Impact factor: 3.240

5.  Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures.

Authors:  Rhys Hunt; Tim Blackmore; Chris Mills; Matt Dicks
Journal:  Iperception       Date:  2022-09-26

6.  Study on Tripping Risks in Fast Walking through Cadence-Controlled Gait Analysis.

Authors:  Wen-Fong Wang; Wei-Chih Lien; Che-Yu Liu; Ching-Yu Yang
Journal:  J Healthc Eng       Date:  2018-05-24       Impact factor: 2.682

  6 in total

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