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However, oculo\u2010gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear.<\/jats:p><\/jats:sec><jats:sec><jats:title>METHODS<\/jats:title><jats:p>Patients with CSVD from a hospital\u2010based cohort (<jats:italic>n<\/jats:italic> = 194) and individuals with presumed early CSVD from a community\u2010based cohort (<jats:italic>n<\/jats:italic> = 319) were included. Oculo\u2010gait patterns were measured using the artificial intelligence (AI) \u2013assisted \u2018EyeKnow\u2019 eye\u2010tracking and \u2018ReadyGo\u2019 motor evaluation systems. Multivariable linear and logistic regression models were employed to investigate the association between the oculo\u2010gait parameters and cognition.<\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p>Anti\u2010saccade accuracy, stride velocity, and swing velocity were significantly associated with cognition in both patients and community dwellers with CSVD, and could identify cognitive impairment in CSVD with moderate accuracy (area under the curve [AUC]: hospital cohort, 0.787; community cohort, 0.810) after adjusting for age and education.<\/jats:p><\/jats:sec><jats:sec><jats:title>DISCUSSION<\/jats:title><jats:p>The evaluation of oculo\u2010gait features (anti\u2010saccade accuracy, stride velocity, and swing velocity) may help screen cognitive impairment in CSVD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Highlights<\/jats:title><jats:p><jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>Oculo\u2010gait features (lower anti\u2010saccade accuracy, stride velocity, and swing velocity) were associated with cognitive impairment in cerebral small vessel disease (CSVD).<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>Logistic model integrating the oculo\u2010gait features, age, and education level moderately distinguished cognitive status in CSVD.<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>Artificial intelligence\u2013assisted oculomotor and gait measurements provide quick and accurate evaluation in hospital and community settings.<\/jats:p><\/jats:list-item>\n<\/jats:list><\/jats:p><\/jats:sec>","DOI":"10.1002\/alz.14288","type":"journal-article","created":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T03:54:19Z","timestamp":1729050859000},"page":"8516-8526","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Artificial intelligence\u2013assisted oculo\u2010gait measurements for cognitive impairment in cerebral small vessel disease"],"prefix":"10.1002","volume":"20","author":[{"given":"Huimin","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Neurology Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences  Dongcheng Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Neurology Xiangya Hospital, Central South University  Changsha Hunan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Yi","sequence":"additional","affiliation":[{"name":"Department of Geriatric Neurology Xiangya Hospital, Central South University  Changsha Hunan China"},{"name":"National Clinical Research Center for Geriatric Disorders Xiangya Hospital, Central South University  Changsha Hunan 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