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

¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a soft-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.To...

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

Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026
Same author

Temporal responses in sensorimotor cortex during hand movements.

PloS one·2026
Same author

Anatomy-corrected metabolic asymmetry predicts seizure freedom after surgery in focal cortical dysplasia.

European journal of nuclear medicine and molecular imaging·2026
Same author

Intracranial electroencephalographic approaches in the intensive care unit: Safety, feasibility, and coverage.

Epilepsia·2026
Same author

Implanted brain-computer interface functionality during nighttime in late-stage amyotrophic lateral sclerosis.

Scientific reports·2026
Same author

Epicranial electrical stimulation improves non-navigational spatial memory in macaque monkeys.

Neuroimage. Reports·2026
Same journal

A computational framework for fitting biophysical basal-ganglia network models, applied to Parkinsonian beta oscillations.

Journal of neural engineering·2026
Same journal

A sensor-driven Hill-type muscle modeling framework integrating sEMG and pFMG for biceps brachii force estimation.

Journal of neural engineering·2026
Same journal

Overcoming brain non-stationarity: Adaptive RLS classification for stable BCIs based on auditory evoked potentials.

Journal of neural engineering·2026
Same journal

Mapping neural representations of fine and gross upper-limb movements across dorsoventral subthalamic nucleus subregions in Parkinson's disease.

Journal of neural engineering·2026
Same journal

Ultra-flexible wireless endovascular stimulator for cortical simulation.

Journal of neural engineering·2026
Same journal

Influence of frequency and pulse train duration on respiratory responses during transcutaneous phrenic nerve stimulation in humans.

Journal of neural engineering·2026
查看所有相关文章

相关实验视频

Updated: May 17, 2026

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

25.6K

从高密度电皮质谱中解读手语指纹曲,使用图形优化的块术语张量回归.

Axel Faes1, Eva Calvo Merino1, Mariana P Branco2

  • 1KU Leuven-University of Leuven, Department of Neurosciences, Laboratory for Neuro- & Psychophysiology, B-3000 Leuven, Belgium.

Journal of neural engineering
|April 16, 2025
PubMed
概括
此摘要是机器生成的。

一种新的方法,图形优化区块术语张量回归 (Go-BTTR),从电皮质谱 (ECoG) 数据中解码手指运动的手语. Go-BTTR通过计算手指的协同激活来改善复杂手势的预测,为大脑-计算机接口提供计算效率.

关键词:
在BTTR,BTTR,BTTR等方面.在ECoG中,我们可以使用ECoG.一个手指指的手指指.这些手势,手势.这些都是回归,回归,回归.标语是指手语的使用方式.

更多相关视频

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.2K
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

300

相关实验视频

Last Updated: May 17, 2026

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

25.6K
Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
11:25

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Published on: July 26, 2013

43.2K
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

300

科学领域:

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

背景情况:

  • 电皮质谱 (ECoG) 记录大脑活动,为大脑与计算机接口 (BCI) 提供了潜在的潜力.
  • 从ECoG中解读复杂的运动意图,如手势语言,由于非线性关系和手指协同激活,具有挑战性.

研究的目的:

  • 介绍一种新的方法,图形优化区块术语张量回归 (Go-BTTR),用于从ECoG数据回归手指的手势语言运动.
  • 为BCI应用程序提高复杂手势解码的准确性和效率.

主要方法:

  • Go-BTTR结合了基于通缩的回归模型 (塔克分解) 和因果图过程 (CGP).
  • CGP根据它们的关系动态分组或分离手指,告知回归模型 (BTTR或eBTTR).
  • 该方法在两个ECoG数据集上得到了验证,其中包括美国和佛兰德的手势语言手势.

主要成果:

  • 与现有方法 (eBTTR,BTTR) 相比,Go-BTTR显示出优异的手指关节轨迹预测.
  • 取得的平均相关性为0.73 (美国手语) 和0.37 (佛兰德语手语) 的Go-BTTR.
  • 该方法有效地解释了非线性ECoG关系和无意指协同激活.

结论:

  • Go-BTTR成功地使用ECoG数据从手语字母来解码复杂的手势.
  • 该方法提供了计算效率,有利于手术前评估和BCI开发.
  • 在解码复杂的电机意图的BCI应用中,Go-BTTR代表了显著的进步.