{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T18:35:17Z","timestamp":1772303717582,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,6]],"date-time":"2020-11-06T00:00:00Z","timestamp":1604620800000},"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>Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize\/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published between 1 January 2000 to 31 July 2020. This systematic review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and is registered on Prospero (CRD42020149352). Study characteristics, sensors and algorithms used, accuracy and robustness were also summarized. In total, 1343 records were identified and 58 studies were included in this review. The experimental condition which was most often investigated was level ground walking along with stair and ramp ascent\/descent activities. The machine learning algorithms implemented in the included studies reached global mean accuracies of around 90%. However, the robustness of those algorithms seems to be more broadly evaluated, notably, in everyday life. We also propose some guidelines for homogenizing future reports.<\/jats:p>","DOI":"10.3390\/s20216345","type":"journal-article","created":{"date-parts":[[2020,11,6]],"date-time":"2020-11-06T09:09:30Z","timestamp":1604653770000},"page":"6345","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["Machine Learning Approaches for Activity Recognition and\/or Activity Prediction in Locomotion Assistive Devices\u2014A Systematic Review"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5405-3923","authenticated-orcid":false,"given":"Floriant","family":"Labarri\u00e8re","sequence":"first","affiliation":[{"name":"INSERM, UMR1093-CAPS, Universit\u00e9 de Bourgogne Franche Comt\u00e9, UFR des Sciences du Sport, F-21000 Dijon, France"}]},{"given":"Elizabeth","family":"Thomas","sequence":"additional","affiliation":[{"name":"INSERM, UMR1093-CAPS, Universit\u00e9 de Bourgogne Franche Comt\u00e9, UFR des Sciences du Sport, F-21000 Dijon, France"}]},{"given":"Laurine","family":"Calistri","sequence":"additional","affiliation":[{"name":"PROTEOR, 6 rue de la Redoute, CS 37833, CEDEX 21078 Dijon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7869-6528","authenticated-orcid":false,"given":"Virgil","family":"Optasanu","sequence":"additional","affiliation":[{"name":"ICB, UMR 6303 CNRS, Universit\u00e9 de Bourgogne Franche Comt\u00e9 9 Av. Alain Savary, CEDEX 21078 Dijon, France"}]},{"given":"Mathieu","family":"Gueugnon","sequence":"additional","affiliation":[{"name":"INSERM, CIC 1432, Module Plurithematique, Plateforme d\u2019Investigation Technologique, CHU Dijon-Bourgogne, Centre d\u2019Investigation Clinique, Module Plurith\u00e9matique, Plateforme d\u2019Investigation Technologique, 21079 Dijon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4959-2348","authenticated-orcid":false,"given":"Paul","family":"Ornetti","sequence":"additional","affiliation":[{"name":"INSERM, UMR1093-CAPS, Universit\u00e9 de Bourgogne Franche Comt\u00e9, UFR des Sciences du Sport, F-21000 Dijon, France"},{"name":"INSERM, CIC 1432, Module Plurithematique, Plateforme d\u2019Investigation Technologique, CHU Dijon-Bourgogne, Centre d\u2019Investigation Clinique, Module Plurith\u00e9matique, Plateforme d\u2019Investigation Technologique, 21079 Dijon, France"},{"name":"Department of Rheumatology, Dijon University Hospital, 21079 Dijon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1599-4258","authenticated-orcid":false,"given":"Davy","family":"Laroche","sequence":"additional","affiliation":[{"name":"INSERM, UMR1093-CAPS, Universit\u00e9 de Bourgogne Franche Comt\u00e9, UFR des Sciences du Sport, F-21000 Dijon, France"},{"name":"INSERM, CIC 1432, Module Plurithematique, Plateforme d\u2019Investigation Technologique, CHU Dijon-Bourgogne, Centre d\u2019Investigation Clinique, Module Plurith\u00e9matique, Plateforme d\u2019Investigation Technologique, 21079 Dijon, France"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.irbm.2014.02.005","article-title":"APSIC: Training and fitting amputees during situations of daily living","volume":"35","author":"Drevelle","year":"2014","journal-title":"IRBM"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1097\/01.phm.0000174665.74933.0b","article-title":"A Clinical Comparison of Variable-Damping and Mechanically Passive Prosthetic Knee Devices","volume":"84","author":"Johansson","year":"2005","journal-title":"Am. 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