{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T13:39:32Z","timestamp":1762177172482,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,2,25]],"date-time":"2019-02-25T00:00:00Z","timestamp":1551052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["H2020-FOF-2016 Grant Agreement #723737"],"award-info":[{"award-number":["H2020-FOF-2016 Grant Agreement #723737"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009888","name":"Regione Toscana","doi-asserted-by":"publisher","award":["Bando FAR-FAS 2014"],"award-info":[{"award-number":["Bando FAR-FAS 2014"]}],"id":[{"id":"10.13039\/501100009888","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The number of exoskeletons providing load-lifting assistance has significantly increased over the last decade. In this field, to take full advantage of active exoskeletons and provide appropriate assistance to users, it is essential to develop control systems that are able to reliably recognize and classify the users\u2019 movement when performing various lifting tasks. To this end, the movement-decoding algorithm should work robustly with different users and recognize different lifting techniques. Currently, there are no studies presenting methods to classify different lifting techniques in real time for applications with lumbar exoskeletons. We designed a real-time two-step algorithm for a portable hip exoskeleton that can detect the onset of the lifting movement and classify the technique used to accomplish the lift, using only the exoskeleton-embedded sensors. To evaluate the performance of the proposed algorithm, 15 healthy male subjects participated in two experimental sessions in which they were asked to perform lifting tasks using four different techniques (namely, squat lifting, stoop lifting, left-asymmetric lifting, and right-asymmetric lifting) while wearing an active hip exoskeleton. Five classes (the four lifting techniques plus the class \u201cno lift\u201d) were defined for the classification model, which is based on a set of rules (first step) and a pattern recognition algorithm (second step). Leave-one-subject-out cross-validation showed a recognition accuracy of 99.34 \u00b1 0.85%, and the onset of the lift movement was detected within the first 121 to 166 ms of movement.<\/jats:p>","DOI":"10.3390\/s19040963","type":"journal-article","created":{"date-parts":[[2019,2,25]],"date-time":"2019-02-25T03:06:52Z","timestamp":1551064012000},"page":"963","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Classification of Lifting Techniques for Application of A Robotic Hip Exoskeleton"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2840-7617","authenticated-orcid":false,"given":"Baojun","family":"Chen","sequence":"first","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Lanotte","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenzo","family":"Grazi","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicola","family":"Vitiello","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"},{"name":"Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9833-4401","authenticated-orcid":false,"given":"Simona","family":"Crea","sequence":"additional","affiliation":[{"name":"The BioRobotics Institute, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"},{"name":"Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,25]]},"reference":[{"key":"ref_1","unstructured":"Parent-Thirion, A., Biletta, I., Cabrita, J., Vargas, O., Vermeylen, G., Wilczynska, A., and Wilkens, M. 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