Literature DB >> 12797722

Continuous curve registration as an intertrial gait variability reduction technique.

Heydar Sadeghi1, Pierre A Mathieu, Somayeh Sadeghi, Hubert Labelle.   

Abstract

Timing in peak values shifts slightly between gait trials. When gait data are averaged, part of the standard deviation could be associated with this intertrial variability unless normalization is carried out beforehand. The objective of this study was to determine how continuous curve registration, an alignment technique, can reduce intersubject variability in gait data without altering the original curve characteristics. Gait data were obtained by means of a four-camera high-speed video system synchronized to a force plate. The data for 60 gait trials were collected from 20 young, healthy subjects. Curve registration was applied to hip angular displacement, net moment, and power curves generated in the sagittal plane. Following registration, the peak values increased by an average of 1.2% (0.11 +/- 0.26 degrees) for angular displacement, and by 11.2% (0.11 +/- 0.09 W/kg) for power, while there were no changes for moments. First and second derivatives of the unregistered and registered curves did not display significant differences, and the harmonics were barely affected. Continuous curve registration would thus be an appropriate technique for application prior to any statistical analysis using able-bodied gait patterns.

Mesh:

Year:  2003        PMID: 12797722     DOI: 10.1109/TNSRE.2003.810428

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

1.  Functional Data Analyses of Gait Data Measured Using In-Shoe Sensors.

Authors:  Jihui Lee; Gen Li; William F Christensen; Gavin Collins; Matthew Seeley; Anton E Bowden; David T Fullwood; Jeff Goldsmith
Journal:  Stat Biosci       Date:  2018-12-07

2.  Radial force distribution changes associated with tangential force production in cylindrical grasping, and the importance of anatomical registration.

Authors:  Todd C Pataky; Gregory P Slota; Mark L Latash; Vladimir M Zatsiorsky
Journal:  J Biomech       Date:  2011-11-30       Impact factor: 2.712

3.  Managing variability in the summary and comparison of gait data.

Authors:  Tom Chau; Scott Young; Sue Redekop
Journal:  J Neuroeng Rehabil       Date:  2005-07-29       Impact factor: 4.262

4.  A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets.

Authors:  Hanaa Naouma; Todd C Pataky
Journal:  PeerJ       Date:  2019-12-10       Impact factor: 2.984

5.  Statistical-Shape Prediction of Lower Limb Kinematics During Cycling, Squatting, Lunging, and Stepping-Are Bone Geometry Predictors Helpful?

Authors:  Joris De Roeck; Kate Duquesne; Jan Van Houcke; Emmanuel A Audenaert
Journal:  Front Bioeng Biotechnol       Date:  2021-07-12
  5 in total

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