Literature DB >> 11955509

Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes.

Kamiar Aminian1, B Najafi, C Büla, P-F Leyvraz, Ph Robert.   

Abstract

In this study we describe an ambulatory system for estimation of spatio-temporal parameters during long periods of walking. This original method based on wavelet analysis is proposed to compute the values of temporal gait parameters from the angular velocity of lower limbs. Based on a mechanical model, the medio-lateral rotation of the lower limbs during stance and swing, the stride length and velocity are estimated by integration of the angular velocity. Measurement's accuracy was assessed using as a criterion standard the information provided by foot pressure sensors. To assess the accuracy of the method on a broad range of performance for each gait parameter, we gathered data from young and elderly subjects. No significant error was observed for toe-off detection, while a slight systematic delay (10 ms on average) existed between heelstrike obtained from gyroscopes and footswitch. There was no significant difference between actual spatial parameters (stride length and velocity) and their estimated values. Errors for velocity and stride length estimations were 0.06 m/s and 0.07 m, respectively. This system is light, portable, inexpensive and does not provoke any discomfort to subjects. It can be carried for long periods of time, thus providing new longitudinal information such as stride-to-stride variability of gait. Several clinical applications can be proposed such as outcome evaluation after total knee or hip replacement, external prosthesis adjustment for amputees, monitoring of rehabilitation progress, gait analysis in neurological diseases, and fall risk estimation in elderly.

Entities:  

Mesh:

Year:  2002        PMID: 11955509     DOI: 10.1016/s0021-9290(02)00008-8

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


  168 in total

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Authors:  Shuozhi Yang; Annemarie Laudanski; Qingguo Li
Journal:  Med Biol Eng Comput       Date:  2012-03-15       Impact factor: 2.602

2.  An adaptive gyroscope-based algorithm for temporal gait analysis.

Authors:  Barry R Greene; Denise McGrath; Ross O'Neill; Karol J O'Donovan; Adrian Burns; Brian Caulfield
Journal:  Med Biol Eng Comput       Date:  2010-11-02       Impact factor: 2.602

3.  BioKin: an ambulatory platform for gait kinematic and feature assessment.

Authors:  Samitha W Ekanayake; Andrew J Morris; Mike Forrester; Pubudu N Pathirana
Journal:  Healthc Technol Lett       Date:  2015-02-25

4.  Gait Cycle Validation and Segmentation Using Inertial Sensors.

Authors:  G V Prateek; Pietro Mazzoni; Gammon M Earhart; Arye Nehorai
Journal:  IEEE Trans Biomed Eng       Date:  2019-11-25       Impact factor: 4.538

5.  Quaternion-based strap-down integration method for applications of inertial sensing to gait analysis.

Authors:  A M Sabatini
Journal:  Med Biol Eng Comput       Date:  2005-01       Impact factor: 2.602

Review 6.  Assessing the interplay between cognition and gait in the clinical setting.

Authors:  A H Snijders; C C Verstappen; M Munneke; B R Bloem
Journal:  J Neural Transm (Vienna)       Date:  2007-07-06       Impact factor: 3.575

7.  Statistical prediction of load carriage mode and magnitude from inertial sensor derived gait kinematics.

Authors:  Sol Lim; Clive D'Souza
Journal:  Appl Ergon       Date:  2018-11-29       Impact factor: 3.661

8.  Validity and repeatability of inertial measurement units for measuring gait parameters.

Authors:  Edward P Washabaugh; Tarun Kalyanaraman; Peter G Adamczyk; Edward S Claflin; Chandramouli Krishnan
Journal:  Gait Posture       Date:  2017-04-12       Impact factor: 2.840

9.  Analyzing 180 degrees turns using an inertial system reveals early signs of progression of Parkinson's disease.

Authors:  Arash Salarian; Cris Zampieri; Fay B Horak; Patricia Carlson-Kuhta; John G Nutt; Kamiar Aminian
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

10.  Quantifying varus thrust in knee osteoarthritis using wearable inertial sensors: A proof of concept.

Authors:  Kerry E Costello; Samantha Eigenbrot; Alex Geronimo; Ali Guermazi; David T Felson; Jim Richards; Deepak Kumar
Journal:  Clin Biomech (Bristol, Avon)       Date:  2020-11-11       Impact factor: 2.063

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