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

Carbon Skeletons01:12

Carbon Skeletons

Life on Earth is carbon-based, as all macromolecules that make up living organisms contain carbon atoms. All organic compounds have a carbon backbone. Each carbon atom is tetravalent and can bond with four other atoms, making it an extraordinarily flexible component of biological molecules. Because carbon’s valence electrons are stable, it rarely becomes an ion. As the carbon chain increases in length, structural modifications such as ring structures, double bonds, and branching side chains...

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

The combined and independent influence of food texture and a 'mindful eating' instruction on eating rate and food intake among Dutch primary schoolchildren.

Appetite·2026
Same author

Deep learning for freezing of gait assessment using inertial measurement units: a multicentre validation study.

NPJ Parkinson's disease·2026
Same author

AI and Internet of Things for Chronic Obstructive Pulmonary Disease Remote Monitoring: Systematic Review of Exacerbation Prediction and Key Physiological Variables.

JMIR medical informatics·2026
Same author

Durable VO<sub>2</sub>-Based Thermochromic Paint for Energy-Efficient Opaque Building Facades.

ACS applied materials & interfaces·2026
Same author

Prevalence of Early Rheumatic Heart Disease Among Asymptomatic Students in Underserved Communities in Ethiopia: Cross-Sectional Observational Study.

JMIR public health and surveillance·2026
Same author

Robust Multimodal Learning Framework for Intake Gesture Detection Using Contactless Radar and Wearable IMU Sensors.

IEEE journal of biomedical and health informatics·2026
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
查看所有相关文章

相关实验视频

Updated: Jun 16, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

2.1K

基于骨架的摄入手势检测与时空图形卷积网络.

Chunzhuo Wang, Zhewen Xue, T Sunil Kumar

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究介绍了一种基于骨架的ST-GCN-BiLSTM模型,用于自动检测食物摄入手势. 这种方法提供了隐私的好处,并在不同的饮食监测数据集中展示了强大的性能.

    更多相关视频

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    5.2K
    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    1.1K

    相关实验视频

    Last Updated: Jun 16, 2026

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
    09:41

    Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

    Published on: April 21, 2023

    2.1K
    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    5.2K
    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    1.1K

    科学领域:

    • 计算机视觉 计算机视觉
    • 人与计算机的交互
    • 生物医学工程 生物医学工程

    背景情况:

    • 肥胖和超重是与不良饮食习惯相关的重大健康问题.
    • 自动化食物摄入手势检测可以改善日常生活中的饮食监测.
    • 基于骨架的方法为手势识别提供了隐私和稳定性.

    研究的目的:

    • 开发和验证基于骨架的方法,用于自动化食物摄入手势检测.
    • 在多个数据集上评估拟议的ST-GCN-BiLSTM模型的性能.
    • 评估系统作为营养分析的自动注释工具的潜力.

    主要方法:

    • 开发了一种基于骨架的方法,将扩展的时空图卷积网络 (ST-GCN) 与双向长期短期记忆 (BiLSTM) 框架相结合.
    • 这个名为ST-GCN-BiLSTM的模型使用OREBA数据集 (实验室视频) 和自行收集的智能手机数据集进行了训练和验证.
    • 使用分段F1评分来评估饮食和饮食手势检测的表现.

    主要成果:

    • 在OREBA数据集上,ST-GCN-BiLSTM模型获得了高F1分数:食用86.18%和饮用手势74.84%.
    • 交叉数据集验证显示了自我收集数据集的强大表现:饮食手势的85.40%和饮酒手势的67.80%.
    • 结果证实了骨架数据在各种条件下用于摄入手势检测的可行性和稳定性.

    结论:

    • 基于骨的摄入手势检测对于饮食监测是可行的和有效的.
    • 拟议的ST-GCN-BiLSTM模型显示了数据集的稳定性和通用性.
    • 这个系统可以作为一个有价值的自动化工具营养专家来分析饮食行为.