{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T16:16:14Z","timestamp":1723047374340},"reference-count":48,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,24]],"date-time":"2022-05-24T00:00:00Z","timestamp":1653350400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"FCT","doi-asserted-by":"publisher","award":["UIDB\/00408\/2020","UIDP\/00408\/2020","SFRH\/BD\/144242\/2019"],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Union\u2019s Horizon 2020 research and innovation programme","doi-asserted-by":"publisher","award":["952279"],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"There is growing interest in monitoring gait patterns in people with neurological conditions. The democratisation of wearable inertial sensors has enabled the study of gait in free living environments. One pivotal aspect of gait assessment in uncontrolled environments is the ability to accurately recognise gait instances. Previous work has focused on wavelet transform methods or general machine learning models to detect gait; the former assume a comparable gait pattern between people and the latter assume training datasets that represent a diverse population. In this paper, we argue that these approaches are unsuitable for people with severe motor impairments and their distinct gait patterns, and make the case for a lightweight personalised alternative. We propose an approach that builds on top of a general model, fine-tuning it with personalised data. A comparative proof-of-concept evaluation with general machine learning (NN and CNN) approaches and personalised counterparts showed that the latter improved the overall accuracy in 3.5% for the NN and 5.3% for the CNN. More importantly, participants that were ill-represented by the general model (the most extreme cases) had the recognition of gait instances improved by up to 16.9% for NN and 20.5% for CNN with the personalised approaches. It is common to say that people with neurological conditions, such as Parkinson\u2019s disease, present very individual motor patterns, and that in a sense they are all outliers; we expect that our results will motivate researchers to explore alternative approaches that value personalisation rather than harvesting datasets that are may be able to represent these differences.<\/jats:p>","DOI":"10.3390\/s22113980","type":"journal-article","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T04:14:14Z","timestamp":1653452054000},"page":"3980","source":"Crossref","is-referenced-by-count":1,"title":["Personalised Gait Recognition for People with Neurological Conditions"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-6067-6318","authenticated-orcid":false,"given":"Leon","family":"Ingelse","sequence":"first","affiliation":[{"name":"LASIGE, Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisbon, Portugal"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9756-3907","authenticated-orcid":false,"given":"Diogo","family":"Branco","sequence":"additional","affiliation":[{"name":"LASIGE, Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisbon, Portugal"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-0770-4268","authenticated-orcid":false,"given":"Hristijan","family":"Gjoreski","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, Skopje 1000, North Macedonia"}]},{"given":"Tiago","family":"Guerreiro","sequence":"additional","affiliation":[{"name":"LASIGE, Faculdade de Ci\u00eancias, Universidade de Lisboa, 1749-016 Lisbon, Portugal"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3756-2763","authenticated-orcid":false,"given":"Raquel","family":"Bou\u00e7a-Machado","sequence":"additional","affiliation":[{"name":"Instituto de Medicina Molecular Jo\u00e3o Lobo Antunes, 1649-028 Lisbon, Portugal"},{"name":"CNS\u2014Campus Neurol\u00f3gico, 2560-280 Torres Vedras, Portugal"}]},{"given":"Joaquim J.","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Instituto de Medicina Molecular Jo\u00e3o Lobo Antunes, 1649-028 Lisbon, Portugal"},{"name":"CNS\u2014Campus Neurol\u00f3gico, 2560-280 Torres Vedras, Portugal"},{"name":"Laboratory of Clinical Pharmacology and Therapeutics, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal"}]},{"name":"The CNS Physiotherapy Study Group","sequence":"additional","affiliation":[]}],"member":"1968","published-online":{"date-parts":[[2022,5,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1111\/ene.14674","article-title":"Functional motor disorders associated with other neurological diseases: Beyond the boundaries of \u201corganic\u201d neurology","volume":"28","author":"Tinazzi","year":"2021","journal-title":"Eur. 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