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Validation and reliability testing of a new, fully integrated gait analysis insole

Overview of attention for article published in Journal of Foot and Ankle Research, September 2015
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Title
Validation and reliability testing of a new, fully integrated gait analysis insole
Published in
Journal of Foot and Ankle Research, September 2015
DOI 10.1186/s13047-015-0111-8
Pubmed ID
Authors

Benedikt Johannes Braun, Nils Thomas Veith, Rebecca Hell, Stefan Döbele, Michael Roland, Mika Rollmann, Jörg Holstein, Tim Pohlemann

Abstract

A new tool (OpenGo, Moticon GmbH) was introduced to continuously measure kinetic and temporospatial gait parameters independently through an insole over up to 4 weeks. The goal of this study was to investigate the validity and reliability of this new insole system in a group of healthy individuals. Gait data were collected from 12 healthy individuals on a treadmill at two different speeds. In total, six trials of three minutes each were performed by every participant. Validation was performed with the FDM-S System (Zebris). Complete sensor data were used for a within test reliability analysis of over 10000 steps. Intraclass correlation was calculated for different gait parameters and analysis of variance performed. Intraclass correlation for the validation was >0.796 for temporospatial and kinetic gait parameters. No statistical difference was seen between the insole and force plate measurements (difference between means: 36.3 ± 27.19 N; p = 0.19 and 0.027 ± 0.028 s; p = 0.36). Intraclass correlation for the reliability was >0.994 for all parameters measured. The system is feasible for clinical trials that require step by step as well as grouped analysis of gait over a long period of time. Comparable validity and reliability to a stationary analysis tool has been shown.

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Geographical breakdown

Country Count As %
Malaysia 1 <1%
United States 1 <1%
Germany 1 <1%
Austria 1 <1%
Unknown 186 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 34 18%
Student > Ph. D. Student 31 16%
Student > Bachelor 28 15%
Researcher 20 11%
Student > Doctoral Student 11 6%
Other 25 13%
Unknown 41 22%
Readers by discipline Count As %
Engineering 57 30%
Medicine and Dentistry 33 17%
Sports and Recreations 18 9%
Nursing and Health Professions 11 6%
Biochemistry, Genetics and Molecular Biology 5 3%
Other 15 8%
Unknown 51 27%