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Comparing Gait Trials with Greedy Template Matching

1
COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
2
L2TI, University Paris 13, 93430 Villetaneuse, France
3
CMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, France
4
ORPEA Group, 92813 Puteaux, France
5
Hangzhou Dianzi University, 310005 Hangzhou, China
6
Service de Neurologie, Hôpital d’Instruction des Armées Percy, Service de Santé des Armées, 92190 Clamart, France
7
Ecole du Val-de-Grâce, Ecole de Santé des Armées, 75005 Paris, France
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3089; https://doi.org/10.3390/s19143089
Received: 9 May 2019 / Revised: 9 July 2019 / Accepted: 11 July 2019 / Published: 12 July 2019
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Abstract

Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as standard gait features may prove to be insufficient in some cases. This article describes a new algorithm for comparing two gait trials recorded with inertial measurement units (IMUs). This algorithm uses a library of step templates extracted from one trial and attempts to detect similar steps in the second trial through a greedy template matching approach. The output of our method is a similarity index (SId) comprised between 0 and 1 that reflects the similarity between the patterns observed in both trials. Results on healthy and multiple sclerosis subjects show that this new comparison tool can be used for both inter-individual comparison and longitudinal follow-up. View Full-Text
Keywords: inertial measurement units; gait analysis; biomedical signal processing; pattern recognition; step detection; physiological signals inertial measurement units; gait analysis; biomedical signal processing; pattern recognition; step detection; physiological signals
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Vienne-Jumeau, A.; Oudre, L.; Moreau, A.; Quijoux, F.; Vidal, P.-P.; Ricard, D. Comparing Gait Trials with Greedy Template Matching. Sensors 2019, 19, 3089.

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