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

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

Molecular identification of trichomonads in captive sugar gliders and tortoises with diarrhea: a case study.

Scientific reports·2026
Same author

CLIP-Actor-X: Text-Driven 4D Human Avatar Generation via Cross-Modal Synthesis-Through-Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Drosophila Abi maintains blood cell homeostasis by promoting clathrin-mediated endocytosis of Notch.

The Journal of cell biology·2025
Same author

Se Nanowire Crystal Formation via Oxidation of 2D HfSe<sub>2</sub>: A Solid-State, In Situ Reaction Coupling for Heterogeneous Integration Technologies.

ACS applied nano materials·2025
Same author

Author Correction: Cortical representations of affective pain shape empathic fear in male mice.

Nature communications·2025
Same author

Assessing the Physical Impact of Supernumerary Limbs on a Human Subject: A Simulation Study.

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

相关实验视频

Updated: May 24, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.4K

用假肢手产生现实的声音:一种强化学习方法

Taemoon Jeong, Sankalp Yamsani, Jooyoung Hong

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括
    此摘要是机器生成的。

    假肢手现在可以通过强化学习产生现实的声音来识别材料. 这项技术通过模仿类似人类的听觉反来增强假肢的功能.

    更多相关视频

    Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
    13:44

    Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

    Published on: August 8, 2011

    13.8K
    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
    05:21

    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

    Published on: January 7, 2019

    7.8K

    相关实验视频

    Last Updated: May 24, 2025

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
    06:58

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

    Published on: November 6, 2015

    9.4K
    Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
    13:44

    Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

    Published on: August 8, 2011

    13.8K
    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
    05:21

    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

    Published on: January 7, 2019

    7.8K

    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 生物声学是一种生物声学.
    • 机器学习 机器学习

    背景情况:

    • 听觉反对于材料识别至关重要,提高了假肢手的功能.
    • 目前的假肢手缺乏准确复制声音以获得触觉声学反的能力.
    • 通过声音来区分材料 (例如,干墙与) 是假肢用户面临的重大挑战.

    研究的目的:

    • 为了使假手能够准确地重现声音,进行物质歧视.
    • 通过听觉反来增强假肢设备的功能和用户体验.
    • 开发一种方法,在假肢手中产生类似人类的声音特征.

    主要方法:

    • 使用强化学习 (RL) 技术来训练假肢手.
    • 专注于模拟类似人类的声音特征,特别是振幅和发病时间.
    • 根据幅度,发作强度和时间标准开发了一个定制的奖励功能.

    主要成果:

    • 假肢手被训练来产生模仿人类听觉信号的声音.
    • 该方法整合了声音属性分析,以指导假肢手的运动.
    • 奖励功能确保了假肢运动与所需的声音输出之间的紧密对齐.

    结论:

    • 强化学习可以训练假肢手产生准确的听觉反.
    • 这项技术有可能显著改善假肢用户的材料识别.
    • 模仿类似人类的声音特征是提高假肢感官能力的关键.