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

Utilization of Classification Learning Algorithms for Upper-Body Non-Cyclic Motion Prediction.

Sensors (Basel, Switzerland)·2025
Same author

Characterization of internal jugular vein region-specific distension and flow patterns during progressive volume shifting.

Journal of applied physiology (Bethesda, Md. : 1985)·2024
Same author

Systematic review of the use of ultrasound for venous assessment and venous thrombosis screening in spaceflight.

NPJ microgravity·2024
Same author

Effects of whole-body vibration or resistive-vibration exercise on blood clotting and related biomarkers: a systematic review.

NPJ microgravity·2023
Same author

Eye-brain axis in microgravity and its implications for Spaceflight Associated Neuro-ocular Syndrome.

NPJ microgravity·2023
Same author

Pathophysiology, risk, diagnosis, and management of venous thrombosis in space: where are we now?

NPJ microgravity·2023
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jan 18, 2026

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

1.2K

无传感器,基于LSTM的人类运动预测使用sEMG数据.

Bon Ho Koo1, Ho Chit Siu2, Lonnie G Petersen3,4

  • 1Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
概括
此摘要是机器生成的。

使用表面电肌图 (sEMG) 进行运动预测的深度学习模型对硬件变化具有强大耐用性. 这表明深度学习网络对于sEMG运动预测任务是硬件不可知的.

关键词:
这是LSTM的LSTM.深度学习是一种深度学习.运动预测,运动预测.表面电力学图 (surface electromyography) 是一种表面电力学图.

更多相关视频

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
04:06

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Published on: January 12, 2024

1.0K
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

5.3K

相关实验视频

Last Updated: Jan 18, 2026

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

1.2K
Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography
04:06

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

Published on: January 12, 2024

1.0K
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

5.3K

科学领域:

  • 生物医学工程 生物医学工程
  • 机器学习 机器学习
  • 神经科学是一个神经科学.

背景情况:

  • 表面电肌图 (sEMG) 被广泛用于运动分类和预测.
  • 由于sEMG传感器硬件的变化存在限制.
  • 深度学习方法对于运动预测越来越受欢迎.

研究的目的:

  • 调查不同sEMG传感器硬件平台对深度学习模型性能的影响.
  • 评估神经网络使用各种sEMG传感器的数据来预测手臂角轨迹的能力.

主要方法:

  • 从使用两个不同的传感器平台进行练习的受试者收集的原始sEMG数据.
  • 训练了一种双向长期短期记忆 (bi-LSTM) 神经网络,以预测一个自由度 (DoF) 角轨迹.
  • 分析了传感器配置的影响,包括通信,DAQ,电极,缓冲,预处理和采样频率.

主要成果:

  • 在来自不同硬件平台的sEMG数据上训练的深度学习神经网络表现相似.
  • 双LSTM网络表现出一致的预测能力,无论传感器来源如何.
  • 这表明神经网络架构能够抵御数据采集硬件的变化.

结论:

  • 用于基于sEMG的运动预测的深度学习模型展示了硬件无关的特征.
  • 这些发现支持使用深度学习来在不同的sEMG传感器系统中可靠地预测运动.
  • 未来的应用程序可以利用这些强大的模型,而不被特定的硬件选择所限制.