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

Transtendinous corticosteroid with contrast injection in trigger finger: a radiological and clinical study.

The Journal of hand surgery, European volume·2026
Same author

Functional results after extensor indicis proprius to extensor pollicis longus tendon transfer for ruptures associated with distal radius fractures.

Journal of plastic surgery and hand surgery·2026
Same author

Exploring discrepancies between in vivo and simulated correction in 3D-planned distal radius osteotomies: the influence of biological factors.

PloS one·2026
Same author

Normative data on extensor pollicis longus force, lift-off height, and tendon gliding amplitude.

Journal of hand therapy : official journal of the American Society of Hand Therapists·2026
Same author

Item-level reanalysis of DASH outcomes after flexor tendon repair using Svensson's non-parametric method.

BMC musculoskeletal disorders·2026
Same author

Understanding the Epidemiology of Malaria in Zanzibar Through Molecular and Serological Analysis of Samples Collected During Reactive Case Detection.

Open forum infectious diseases·2026

相关实验视频

Updated: Jun 1, 2025

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

431

根据HDsEMG的单个峰值定位进行肌肉活动映射.

Jonathan Lundsberg1, Anders Björkman2, Nebojsa Malesevic1

  • 1Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
|January 19, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的方法,使用电肌图 (EMG) 精确确定肌肉激活来源,以更好地控制假肢. 该技术准确地区分手指肌肉活动,增强人机界面.

关键词:
在EMG分类中,EMG的分类.高密度的sEMG是什么定位局部化 定位局部化肌肉建模的模型.

更多相关视频

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

2.5K
Muscle Function Obtained with Motion Mode Ultrasound and Surface Electromyography during Core Endurance Exercise
09:21

Muscle Function Obtained with Motion Mode Ultrasound and Surface Electromyography during Core Endurance Exercise

Published on: August 25, 2022

3.1K

相关实验视频

Last Updated: Jun 1, 2025

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography
09:42

Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography

Published on: January 24, 2025

431
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
09:57

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization

Published on: September 20, 2024

2.5K
Muscle Function Obtained with Motion Mode Ultrasound and Surface Electromyography during Core Endurance Exercise
09:21

Muscle Function Obtained with Motion Mode Ultrasound and Surface Electromyography during Core Endurance Exercise

Published on: August 25, 2022

3.1K

科学领域:

  • 生物医学工程 生物医学工程
  • 神经科学是一个神经科学.
  • 康复技术 康复技术 康复技术

背景情况:

  • 电肌图 (EMG) 对于人机界面 (HMI) 在假肢和康复方面至关重要.
  • 解码肌肉激活模式是先进HMI控制的关键.
  • 目前的方法在紧的解剖学中精确地定位肌肉活动时面临挑战.

研究的目的:

  • 开发和验证一种使用高密度表面EMG评估和解码肌肉活动的新方法.
  • 在指部伸展过程中,从前臂肌肉的EMG信号中定位个体时峰的起源.
  • 估计每个手指的不同肌肉体积,并根据这些体积对EMG峰值进行分类.

主要方法:

  • 在低力指部伸展过程中利用背部前臂的高密度表面EMG记录.
  • 应用了一个空间域表面高斯适配以定位EMG峰值起源.
  • 在10名受试者中,对个别指部伸展的肌肉体积的估计.
  • 根据估计的体积,分类的个体EMG峰值被分为相应的指动.

主要成果:

  • 在各个受试者中,估计的肌肉体积具有很高的一致性,这表明每个手指的动作都具有不同的肌肉区域.
  • 实现了高分类精度的EMG峰值:79% (指数),84% (中),76% (环) 和79% (小指).
  • 标示了数字之间的肌肉纤维的潜在结构差异.

结论:

  • 体积分析方法有效地评估紧的肌肉群中的空间激活模式.
  • 单个峰值分类方法使肌肉激活几乎可以立即识别.
  • 这种技术为基于EMG的HMI提供了有前途的进步,改善了假肢控制和辅助技术.