视频分析揭示了快速眼动睡眠行为障碍和帕金森病中运动迟缓的早期迹象

IF 8.2 1区 医学 Q1 NEUROSCIENCES
Diego L. Guarín, Gabriela Acevedo, Carolina Calonge, Joshua K. Wong, Nikolaus R. McFarland, Adolfo Ramirez-Zamora, David E. Vaillancourt
{"title":"视频分析揭示了快速眼动睡眠行为障碍和帕金森病中运动迟缓的早期迹象","authors":"Diego L. Guarín, Gabriela Acevedo, Carolina Calonge, Joshua K. Wong, Nikolaus R. McFarland, Adolfo Ramirez-Zamora, David E. Vaillancourt","doi":"10.1038/s41531-025-01082-0","DOIUrl":null,"url":null,"abstract":"<p>Idiopathic REM sleep behavior disorder (iRBD) is a strong predictor of neurodegenerative diseases like Parkinson’s disease (PD). Early detection of motor impairments such as bradykinesia is critical for identifying at-risk populations. This study analyzed Finger Tapping Task videos from 66 participants, including healthy controls (HC) and individuals with iRBD and PD. Only videos that received a clinician score of zero on the MDS-UPDRS Part-III finger tapping item were analyzed. Movement amplitude, speed, and their decrements during the task were directly estimated from the videos using machine learning algorithms. Bradykinesia and hypokinesia were detectable in PD but not in iRBD, while decrement in movement amplitude and speed were observed in PD and iRBD. Classification models achieved 81.5% accuracy distinguishing PD from HC, 79.8% distinguishing iRBD from HC, and 81.7% differentiating iRBD from PD. Video-based assessments offer a low-cost, scalable solution for supporting the identification individuals at risk of developing neurodegenerative diseases.</p>","PeriodicalId":19706,"journal":{"name":"NPJ Parkinson's Disease","volume":"15 1","pages":""},"PeriodicalIF":8.2000,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Video analysis reveals early signs of Bradykinesia in REM sleep behavior disorder and Parkinson’s disease\",\"authors\":\"Diego L. Guarín, Gabriela Acevedo, Carolina Calonge, Joshua K. Wong, Nikolaus R. McFarland, Adolfo Ramirez-Zamora, David E. Vaillancourt\",\"doi\":\"10.1038/s41531-025-01082-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Idiopathic REM sleep behavior disorder (iRBD) is a strong predictor of neurodegenerative diseases like Parkinson’s disease (PD). Early detection of motor impairments such as bradykinesia is critical for identifying at-risk populations. This study analyzed Finger Tapping Task videos from 66 participants, including healthy controls (HC) and individuals with iRBD and PD. Only videos that received a clinician score of zero on the MDS-UPDRS Part-III finger tapping item were analyzed. Movement amplitude, speed, and their decrements during the task were directly estimated from the videos using machine learning algorithms. Bradykinesia and hypokinesia were detectable in PD but not in iRBD, while decrement in movement amplitude and speed were observed in PD and iRBD. Classification models achieved 81.5% accuracy distinguishing PD from HC, 79.8% distinguishing iRBD from HC, and 81.7% differentiating iRBD from PD. Video-based assessments offer a low-cost, scalable solution for supporting the identification individuals at risk of developing neurodegenerative diseases.</p>\",\"PeriodicalId\":19706,\"journal\":{\"name\":\"NPJ Parkinson's Disease\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2025-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Parkinson's Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41531-025-01082-0\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Parkinson's Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41531-025-01082-0","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

特发性快速眼动睡眠行为障碍(iRBD)是帕金森病(PD)等神经退行性疾病的重要预测因子。运动迟缓等运动障碍的早期检测对于识别高危人群至关重要。这项研究分析了66名参与者的手指敲击任务视频,包括健康对照组(HC)和iRBD和PD患者。仅对MDS-UPDRS Part-III手指敲击项目临床医生评分为零的视频进行分析。使用机器学习算法直接从视频中估计运动幅度、速度及其衰减。PD组运动迟缓和运动不足,iRBD组未见,而PD组和iRBD组运动幅度和运动速度均有下降。分类模型区分PD和HC的准确率为81.5%,区分iRBD和HC的准确率为79.8%,区分iRBD和PD的准确率为81.7%。基于视频的评估提供了一种低成本、可扩展的解决方案,用于支持识别有患神经退行性疾病风险的个体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Video analysis reveals early signs of Bradykinesia in REM sleep behavior disorder and Parkinson’s disease

Video analysis reveals early signs of Bradykinesia in REM sleep behavior disorder and Parkinson’s disease

Idiopathic REM sleep behavior disorder (iRBD) is a strong predictor of neurodegenerative diseases like Parkinson’s disease (PD). Early detection of motor impairments such as bradykinesia is critical for identifying at-risk populations. This study analyzed Finger Tapping Task videos from 66 participants, including healthy controls (HC) and individuals with iRBD and PD. Only videos that received a clinician score of zero on the MDS-UPDRS Part-III finger tapping item were analyzed. Movement amplitude, speed, and their decrements during the task were directly estimated from the videos using machine learning algorithms. Bradykinesia and hypokinesia were detectable in PD but not in iRBD, while decrement in movement amplitude and speed were observed in PD and iRBD. Classification models achieved 81.5% accuracy distinguishing PD from HC, 79.8% distinguishing iRBD from HC, and 81.7% differentiating iRBD from PD. Video-based assessments offer a low-cost, scalable solution for supporting the identification individuals at risk of developing neurodegenerative diseases.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
NPJ Parkinson's Disease
NPJ Parkinson's Disease Medicine-Neurology (clinical)
CiteScore
9.80
自引率
5.70%
发文量
156
审稿时长
11 weeks
期刊介绍: npj Parkinson's Disease is a comprehensive open access journal that covers a wide range of research areas related to Parkinson's disease. It publishes original studies in basic science, translational research, and clinical investigations. The journal is dedicated to advancing our understanding of Parkinson's disease by exploring various aspects such as anatomy, etiology, genetics, cellular and molecular physiology, neurophysiology, epidemiology, and therapeutic development. By providing free and immediate access to the scientific and Parkinson's disease community, npj Parkinson's Disease promotes collaboration and knowledge sharing among researchers and healthcare professionals.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信