Next Article in Journal
Sensor Systems for FRP Lightweight Structures: Automotive Features Based on Serial Sensor Products
Next Article in Special Issue
Turning Analysis during Standardized Test Using On-Shoe Wearable Sensors in Parkinson’s Disease
Previous Article in Journal
Beacon-Related Parameters of Bluetooth Low Energy: Development of a Semi-Automatic System to Study Their Impact on Indoor Positioning Systems
Open AccessArticle

Comparing Gait Trials with Greedy Template Matching

COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France
L2TI, University Paris 13, 93430 Villetaneuse, France
CMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, France
ORPEA Group, 92813 Puteaux, France
Hangzhou Dianzi University, 310005 Hangzhou, China
Service de Neurologie, Hôpital d’Instruction des Armées Percy, Service de Santé des Armées, 92190 Clamart, France
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;
Received: 9 May 2019 / Revised: 9 July 2019 / Accepted: 11 July 2019 / Published: 12 July 2019
PDF [3467 KB, uploaded 15 July 2019]


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

Figure 1

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).

Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top