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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Automatic detection of gait events using kinematic data
Gait and Posture, Volume 25, No. 3, Year 2007
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Description
The timing of heel strike (HS) and toe off (TO), the events that mark the transitions between stance and swing phase of gait, is essential when analysing gait. Force plate recordings are routinely used to identify these events. Additional instrumentation, such as force sensitive resistors, can also been used. These approaches, however, include restrictions on the number of steps that can be analyzed and further encumbrance of the subject. We developed an algorithm which automatically determines these times from kinematic data recorded by a motion capture system, which is routinely used in gait analysis laboratories. The foot velocity algorithm (FVA) uses data from the heel and toe markers and identifies features in the vertical velocity of the foot which correspond to the gait events. We verified the performance of the FVA using a large data set of 54 normal children that contained both force plate recordings and kinematic data and found errors of (mean ± standard deviation) 16 ± 15 ms for HS and 9 ± 15 ms for TO. The algorithm also worked well when tested on a small number of children with spastic diplegia. We compared the performance of the FVA with another kinematic method previously described. Our foot velocity algorithm offered more accurate results and was easier to implement than the previously described one, and should be applicable in a variety of gait analysis settings. © 2006 Elsevier B.V. All rights reserved.
Authors & Co-Authors
O'Connor, Ciara M.
Ireland, Dublin
University College Dublin
Thorpe, Susannah K.S.
United Kingdom, Birmingham
University of Birmingham
South Africa, Cape Town
Mrc/uct Medical Imaging Research Unit
O'Malley, Mark J.
Ireland, Dublin
University College Dublin
Vaughan, Christopher L.
Ireland, Dublin
University College Dublin
South Africa, Cape Town
Mrc/uct Medical Imaging Research Unit
Statistics
Citations: 484
Authors: 4
Affiliations: 3
Identifiers
Doi:
10.1016/j.gaitpost.2006.05.016
ISSN:
09666362
Research Areas
Maternal And Child Health