{"title":"多发性硬化症患者无标记视频步态分析。","authors":"Matteo Moro;Giorgia Marchesi;Maria Cellerino;Giacomo Boffa;Francesca Odone;Matilde Inglese;Maura Casadio","doi":"10.1109/TNSRE.2025.3589765","DOIUrl":null,"url":null,"abstract":"Gait analysis plays a crucial role in assessing mobility impairments and monitoring disease progression in individuals with Multiple Sclerosis (MS). Markerless, video-based methods offer a non-invasive, practical alternative to traditional marker-based systems, making them particularly suitable for clinical applications. This study employs a markerless video-based approach to extract spatio-temporal and kinematic parameters from 25 individuals with MS and 25 age- and sex-matched unimpaired controls. The MS cohort was divided into two subgroups based on the Expanded Disability Status Scale (EDSS): “high” disability (<inline-formula> <tex-math>$\\textit {EDSS} \\geq {3}$ </tex-math></inline-formula>) and “low” disability (<inline-formula> <tex-math>$\\textit {EDSS} \\lt {3}$ </tex-math></inline-formula>). Both normal and tandem gait patterns were evaluated. In normal gait, significant spatio-temporal and joint kinematic differences were observed between the high EDSS group and unimpaired controls, while the low EDSS group exhibited no notable deviations. In contrast, tandem gait analysis revealed significant differences in heel-to-toe distance between the low EDSS group and unimpaired controls, highlighting subtle changes that were undetectable in normal gait. These findings underscore the potential of video-based methods to enhance disease monitoring and guide targeted rehabilitation strategies in MS.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"2743-2749"},"PeriodicalIF":5.2000,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082420","citationCount":"0","resultStr":"{\"title\":\"Markerless Video-Based Gait Analysis in People With Multiple Sclerosis\",\"authors\":\"Matteo Moro;Giorgia Marchesi;Maria Cellerino;Giacomo Boffa;Francesca Odone;Matilde Inglese;Maura Casadio\",\"doi\":\"10.1109/TNSRE.2025.3589765\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gait analysis plays a crucial role in assessing mobility impairments and monitoring disease progression in individuals with Multiple Sclerosis (MS). Markerless, video-based methods offer a non-invasive, practical alternative to traditional marker-based systems, making them particularly suitable for clinical applications. This study employs a markerless video-based approach to extract spatio-temporal and kinematic parameters from 25 individuals with MS and 25 age- and sex-matched unimpaired controls. The MS cohort was divided into two subgroups based on the Expanded Disability Status Scale (EDSS): “high” disability (<inline-formula> <tex-math>$\\\\textit {EDSS} \\\\geq {3}$ </tex-math></inline-formula>) and “low” disability (<inline-formula> <tex-math>$\\\\textit {EDSS} \\\\lt {3}$ </tex-math></inline-formula>). Both normal and tandem gait patterns were evaluated. In normal gait, significant spatio-temporal and joint kinematic differences were observed between the high EDSS group and unimpaired controls, while the low EDSS group exhibited no notable deviations. In contrast, tandem gait analysis revealed significant differences in heel-to-toe distance between the low EDSS group and unimpaired controls, highlighting subtle changes that were undetectable in normal gait. These findings underscore the potential of video-based methods to enhance disease monitoring and guide targeted rehabilitation strategies in MS.\",\"PeriodicalId\":13419,\"journal\":{\"name\":\"IEEE Transactions on Neural Systems and Rehabilitation Engineering\",\"volume\":\"33 \",\"pages\":\"2743-2749\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11082420\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Neural Systems and Rehabilitation Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11082420/\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11082420/","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Markerless Video-Based Gait Analysis in People With Multiple Sclerosis
Gait analysis plays a crucial role in assessing mobility impairments and monitoring disease progression in individuals with Multiple Sclerosis (MS). Markerless, video-based methods offer a non-invasive, practical alternative to traditional marker-based systems, making them particularly suitable for clinical applications. This study employs a markerless video-based approach to extract spatio-temporal and kinematic parameters from 25 individuals with MS and 25 age- and sex-matched unimpaired controls. The MS cohort was divided into two subgroups based on the Expanded Disability Status Scale (EDSS): “high” disability ($\textit {EDSS} \geq {3}$ ) and “low” disability ($\textit {EDSS} \lt {3}$ ). Both normal and tandem gait patterns were evaluated. In normal gait, significant spatio-temporal and joint kinematic differences were observed between the high EDSS group and unimpaired controls, while the low EDSS group exhibited no notable deviations. In contrast, tandem gait analysis revealed significant differences in heel-to-toe distance between the low EDSS group and unimpaired controls, highlighting subtle changes that were undetectable in normal gait. These findings underscore the potential of video-based methods to enhance disease monitoring and guide targeted rehabilitation strategies in MS.
期刊介绍:
Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.