Literature DB >> 19163735

Benchmarking of a full-body inertial motion capture system for clinical gait analysis.

Teunis Cloete1, Cornie Scheffer.   

Abstract

In order for gait analysis to be established as part of routine clinical diagnoses, an accurate, flexible and user-friendly motion capture system is required. Commonly used optical, mechanical and acoustic systems offer acceptable accuracy and repeatability, but are often expensive and restricted to laboratory use. Inertial motion capture has seen great innovation in the last few years, but the technology is not yet considered mature enough for clinical gait analysis. In this paper we compare the kinematic reliability of inertial motion capture with optical motion capture during routine gait studies of eight able-bodied subjects. The root mean squared, RMS, and coefficient of correlation, R, was used to compare data sets. Saggital plane joint angles in the knee and hip compared very well. Corresponding transverse and frontal plane values were moderately accurate. The ankle joint angles calculated from the two systems were less accurate. This was believed to be due to the use of different rotation axis orientations used for calculation of angular rotations.

Entities:  

Mesh:

Year:  2008        PMID: 19163735     DOI: 10.1109/IEMBS.2008.4650232

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  17 in total

1.  Joint angle estimation with wavelet neural networks.

Authors:  Saaveethya Sivakumar; Alpha Agape Gopalai; King Hann Lim; Darwin Gouwanda; Sunita Chauhan
Journal:  Sci Rep       Date:  2021-05-13       Impact factor: 4.379

Review 2.  A comprehensive review of sensors and instrumentation methods in devices for musical expression.

Authors:  Carolina Brum Medeiros; Marcelo M Wanderley
Journal:  Sensors (Basel)       Date:  2014-07-25       Impact factor: 3.576

3.  Octopus: A Design Methodology for Motion Capture Wearables.

Authors:  Javier Marin; Teresa Blanco; Jose J Marin
Journal:  Sensors (Basel)       Date:  2017-08-15       Impact factor: 3.576

4.  Human Actions Analysis: Templates Generation, Matching and Visualization Applied to Motion Capture of Highly-Skilled Karate Athletes.

Authors:  Tomasz Hachaj; Marcin Piekarczyk; Marek R Ogiela
Journal:  Sensors (Basel)       Date:  2017-11-10       Impact factor: 3.576

5.  Functional movement assessment by means of inertial sensor technology to discriminate between movement behaviour of healthy controls and persons with knee osteoarthritis.

Authors:  Rob van der Straaten; Mariska Wesseling; Ilse Jonkers; Benedicte Vanwanseele; Amber K B D Bruijnes; Jan Malcorps; Johan Bellemans; Jan Truijen; Liesbet De Baets; Annick Timmermans
Journal:  J Neuroeng Rehabil       Date:  2020-05-19       Impact factor: 4.262

6.  Validation of Spatiotemporal and Kinematic Measures in Functional Exercises Using a Minimal Modeling Inertial Sensor Methodology.

Authors:  Benjamin R Hindle; Justin W L Keogh; Anna V Lorimer
Journal:  Sensors (Basel)       Date:  2020-08-15       Impact factor: 3.576

7.  Activity Recognition Using Wearable Physiological Measurements: Selection of Features from a Comprehensive Literature Study.

Authors:  Inma Mohino-Herranz; Roberto Gil-Pita; Manuel Rosa-Zurera; Fernando Seoane
Journal:  Sensors (Basel)       Date:  2019-12-13       Impact factor: 3.576

8.  Automatic identification of inertial sensor placement on human body segments during walking.

Authors:  Dirk Weenk; Bert-Jan F van Beijnum; Chris T M Baten; Hermie J Hermens; Peter H Veltink
Journal:  J Neuroeng Rehabil       Date:  2013-03-21       Impact factor: 4.262

9.  Accuracy of Base of Support Using an Inertial Sensor Based Motion Capture System.

Authors:  Liangjie Guo; Shuping Xiong
Journal:  Sensors (Basel)       Date:  2017-09-12       Impact factor: 3.576

10.  Integrating a gait analysis test in hospital rehabilitation: A service design approach.

Authors:  Javier Marín; Teresa Blanco; José J Marín; Alejandro Moreno; Elena Martitegui; Juan C Aragüés
Journal:  PLoS One       Date:  2019-10-30       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.