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

Classification of Bones01:18

Classification of Bones

14.3K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
14.3K

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 author

Systematic Evaluation of Hip Exoskeleton Assistance Parameters for Enhancing Gait Stability During Ground Slip Perturbations.

IEEE transactions on bio-medical engineering·2026
Same author

Paretic limb biomechanical response to hip exoskeleton limb assistance strategies during walking for individuals post-stroke.

Journal of biomechanics·2026
Same author

Wearable technologies for assisted mobility in the real world.

Nature communications·2025
Same author

Deep domain adaptation eliminates costly data required for task-agnostic wearable robotic control.

Science robotics·2025
Same author

Robotic Ankle Exoskeleton and Limb Angle Biofeedback for Assisting Stroke Gait: A Feasibility Study.

IEEE robotics and automation letters·2025
Same author

Online Adaptation Framework Enables Personalization of Exoskeleton Assistance During Locomotion in Patients Affected by Stroke.

IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society·2025
Same journal

Multimodal Cross-Attention Fusion of B-Mode Ultrasound and Strain Elastography for Tumor Segmentation in Robotics-Assisted Surgery.

IEEE transactions on medical robotics and bionics·2026
Same journal

A Pneumatically Actuated Robotic Assistant for MRI-Guided Stereotactic Neurosurgery.

IEEE transactions on medical robotics and bionics·2026
Same journal

Interdisciplinary Dialogues on Surgical Data Science: Revising Its Benefits for Surgical Stakeholders and Patients.

IEEE transactions on medical robotics and bionics·2026
Same journal

Concentric Tube Robot-Assisted Intracerebral Hemorrhage Evacuation: Validation in an Ovine Model.

IEEE transactions on medical robotics and bionics·2026
Same journal

Autonomous Slip-Prevention Grip Force Control and Its Potential in Shared Control of Robotic Prosthetic Hands.

IEEE transactions on medical robotics and bionics·2026
Same journal

Modeling and Control For Minimally Invasive Intracerebral Hemorrhage Evacuation.

IEEE transactions on medical robotics and bionics·2026
查看所有相关文章

相关实验视频

Updated: May 3, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.1K

机器学习能够使用机器人部外骨架快速检测滑落

Reese R Peterson1, Jennifer K Leestma2, Inseung Kang3

  • 1Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332 USA. He is now with the Florida Institute for Human and Machine Cognition, Pensacola, FL, 32502 USA.

IEEE transactions on medical robotics and bionics
|August 21, 2025
PubMed
概括
此摘要是机器生成的。

研究人员开发了部外骨架的滑动检测算法,以帮助恢复平衡. 极端梯度提升 (XGBoost) 显示出最佳性能,为工业工人和老年人实现了高精度和快速检测时间.

关键词:
预防跌倒机动运动机器学习机器人部外骨架滑动检测器

更多相关视频

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.4K
Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
05:26

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

Published on: October 25, 2024

1.2K

相关实验视频

Last Updated: May 3, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.1K
Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.4K
Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
05:26

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

Published on: October 25, 2024

1.2K

科学领域:

  • 机器人技术
  • 生物力学
  • 机器学习

背景情况:

  • 滑倒是工业工人和老年人的伤害的主要原因.
  • 有效的平衡恢复系统需要快速发现滑动.
  • 目前的辅助设备缺乏有效的实时滑动检测功能.

研究的目的:

  • 使用部外骨架传感器检测滑落的不同机器学习模型的有效性.
  • 确定快速准确地检测滑动的最佳算法,以提高平衡恢复.

主要方法:

  • 使用线性差异分析 (LDA),极端梯度增强 (XGBoost) 和卷积神经网络 (CNN) 训练和评估用户独立的模型.
  • 使用来自部外骨的原生传感器数据在基于跑步机的滑动中.
  • 在不同级别的早期 (ES) 和后期 (LS) 滑动上测试模型.

主要成果:

  • 所有测试的模型,除了LS滑动的LDA,在滑动检测中达到90%以上的准确性.
  • 通过快速检测时间 (ES为155. 06毫秒,LS为228. 88毫秒) 和高中准确度 (ES为96. 25%,LS为93. 75%),XGBoost表现出卓越的性能.
  • 在195. 64毫秒 (ES) 和266. 24毫秒 (LS) 中,XGBoost获得了100%的灵敏度.

结论:

  • 机器学习模型,特别是XGBoost,对部外骨架的实时滑动检测具有显著的前景.
  • 开发的模型可以帮助设计有效的平衡恢复策略.
  • 需要进一步的研究来为不同的人群和滑动场景创建可通用的模型.