{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:48:17Z","timestamp":1760237297476,"version":"build-2065373602"},"reference-count":84,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,3,30]],"date-time":"2020-03-30T00:00:00Z","timestamp":1585526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines the use of a dictionary of templates and a Dynamic Time Warping (DTW) measure of fit to retrieve these templates into input signals. Several strategies for choosing and learning the adequate templates from annotated data are also described. The method is tested on thirteen healthy subjects and compared to gold standard. Depending of the template choice, the proposed algorithm achieves average errors from 0.01 to 0.03 s for the detection of IC, FC and step duration. Results demonstrate that the use of DTW allows achieving these performances with only one single template. DTW is a convenient tool to perform pattern recognition on gait gyrometer signals. This study paves the way for new step detection methods: it shows that using one single template associated with non-linear deformations may be sufficient to model the gait of healthy subjects.<\/jats:p>","DOI":"10.3390\/s20071939","type":"journal-article","created":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T03:44:13Z","timestamp":1585712653000},"page":"1939","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Non-Linear Template-Based Approach for the Study of Locomotion"],"prefix":"10.3390","volume":"20","author":[{"given":"Tristan","family":"Dot","sequence":"first","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"}]},{"given":"Flavien","family":"Quijoux","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"},{"name":"ORPEA Group, F-92813 Puteaux, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4750-2265","authenticated-orcid":false,"given":"Laurent","family":"Oudre","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, L2TI, UR 3043, F-93430 Villetaneuse, France"}]},{"given":"Ali\u00e9nor","family":"Vienne-Jumeau","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"}]},{"given":"Albane","family":"Moreau","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"},{"name":"Service de Neurologie, Service de Sant\u00e9 des Arm\u00e9es, H\u00f4pital d\u2019Instruction des Arm\u00e9es Percy, F-92190 Clamart, France"}]},{"given":"Pierre-Paul","family":"Vidal","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"},{"name":"Hangzhou Dianzi University, Hangzhou C-310005, China"}]},{"given":"Damien","family":"Ricard","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-94235 Cachan, France"},{"name":"Universit\u00e9 de Paris, CNRS, Centre Borelli, F-75005 Paris, France"},{"name":"Service de Neurologie, Service de Sant\u00e9 des Arm\u00e9es, H\u00f4pital d\u2019Instruction des Arm\u00e9es Percy, F-92190 Clamart, France"},{"name":"Ecole du Val-de-Gr\u00e2ce, Ecole de Sant\u00e9 des Arm\u00e9es, F-75005 Paris, France"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1186\/1743-0003-11-152","article-title":"Estimation of step-by-step spatio-temporal parameters of normal and impaired gait using shank-mounted magneto-inertial sensors: Application to elderly, hemiparetic, parkinsonian and choreic gait","volume":"11","author":"Trojaniello","year":"2014","journal-title":"J. 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