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Technologies such as wearable sensors show potential for this purpose, but consensus is needed to optimize collection and interpretation of digital measures in PwMS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To propose a framework for measuring and interpreting key aspects of impaired gait in PwMS using a smartphone worn at the waist level.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>The framework was developed on the basis of clinical understanding and knowledge of sensor signal processing, supported by a systematic literature review (SLR). The SLR targeted articles published after 2011 that measured gait characteristics in PwMS. Findings were used to propose standardized definitions for complementary gait domains and define digital measures that should be captured for each domain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The resulting framework for PwMS recommends definitions for pace, rhythm, stability, symmetry, variability, smoothness, complexity and fatigability gait domains. For each domain, a set of digital measures is described with respect to their interpretability and associated caveats.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>This framework provides recommendations for measuring complex gait patterns in PwMS using widely available technology. This work promotes the use of standardized gait domain definitions and harmonized descriptions of associated digital measures, paving the way for future validation efforts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13524585251316242","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T05:16:56Z","timestamp":1739855816000},"page":"512-528","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6474-9377","authenticated-orcid":false,"given":"Angelos","family":"Karatsidis","sequence":"first","affiliation":[{"name":"Biogen Digital Health, Baar, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenza","family":"Angelini","sequence":"additional","affiliation":[{"name":"F. 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