Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Vision01:24

Vision

52.2K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
52.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same authorSame journal

Myotonia Mimicking Paroxysmal Dystonia: Two Cases of SCN4A Temperature-Sensitive Sodium Channelopathy.

Movement disorders clinical practice·2026
Same author

Dystonia in Parkinson's disease: Clinical characteristics and predictors of treatment response.

Parkinsonism & related disorders·2026
Same author

Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.

Journal of Parkinson's disease·2026
Same author

Investigating smiling asymmetries in Parkinson's disease through the whistle-smile reflex.

Journal of neural transmission (Vienna, Austria : 1996)·2026
Same author

Driving Cerebellar Theta Oscillations Interferes With Voluntary Neck Movements in Cervical Dystonia.

Movement disorders : official journal of the Movement Disorder Society·2026
Same author

Improvement of Refractory Restless Legs Syndrome in a Parkinson's Disease Patient After Semaglutide Treatment: A Novel Clinical Observation.

Journal of movement disorders·2026

相关实验视频

Updated: May 9, 2025

VisualEyes: A Modular Software System for Oculomotor Experimentation
10:41

VisualEyes: A Modular Software System for Oculomotor Experimentation

Published on: March 25, 2011

12.6K

运动障碍中的计算机视觉技术:系统性审查

Pasquale Maria Pecoraro1,2, Luca Marsili3, Alberto J Espay3

  • 1Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.

Movement disorders clinical practice
|May 6, 2025
PubMed
概括

计算机视觉 (CV) 提供对运动障碍的客观,非侵入性分析,达到80%以上的诊断准确度. 在标准化视频设置和软件以广泛临床使用方面仍然存在挑战.

关键词:
计算机视觉 计算机视觉动力学分析 动力学分析机器学习是机器学习.运动障碍 运动障碍定量分析量化分析

更多相关视频

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis
07:00

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Published on: October 13, 2016

8.1K
Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking
07:26

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Published on: September 26, 2019

7.7K

相关实验视频

Last Updated: May 9, 2025

VisualEyes: A Modular Software System for Oculomotor Experimentation
10:41

VisualEyes: A Modular Software System for Oculomotor Experimentation

Published on: March 25, 2011

12.6K
Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis
07:00

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Published on: October 13, 2016

8.1K
Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking
07:26

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Published on: September 26, 2019

7.7K

科学领域:

  • 利用计算机视觉和机器学习进行神经学中的客观运动分析.
  • 专注于无标记器自动化视频分析的应用,以评估运动障碍.

背景情况:

  • 目前的运动障碍评估严重依赖主观现象学,导致诊断准确度低于最佳.
  • 需要客观,定量和非侵入性运动分析来弥合诊断准确性的差距.
  • 无标记器自动视频分析,或计算机视觉 (CV),为生态有效的评估提供了一个有希望的解决方案.

研究的目的:

  • 系统地审查计算机视觉 (CV) 在运动障碍的评估,诊断和监测中的应用.
  • 评估基于CV的临床神经病学方法的有效性和挑战.

主要方法:

  • 按照PRISMA指南进行的系统审查,搜索Cochrane,Embase,PubMed和Scopus数据库.
  • 搜索策略包括"视频分析"或"计算机视觉"与运动障碍和相关术语的全面列表相结合.
  • 纳入标准主要集中在1984年至2024年9月发表的研究,并根据专家判断纳入其他研究.

主要成果:

  • 在1099项确定研究中,有61项符合纳入标准,另外还有10项额外的研究.
  • 帕金森病是研究最多的疾病,步态分析是最常见的运动任务.
  • 对于大多数运动障碍,自动视频分析显示诊断准确率超过80%,其中OpenPose是常见的工具. 心血管显示与加速度计和临床评估对震, dystonia 和 tic 检测有很强的对齐.

结论:

  • 计算机视觉 (CV) 显示出对运动障碍存在和严重性的非侵入性量化有很大的潜力.
  • 现实世界应用的主要挑战包括视频设置的异质性,软件的使用,以及对标准化视频录制指南的需求.