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

Genetic Lingo01:11

Genetic Lingo

Overview
Surveys02:16

Surveys

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Arithmetic Mean01:08

Arithmetic Mean

The arithmetic mean is the most commonly used measure of the central tendency of a data set. It is defined as the sum of all the elements constituting the data set, divided by the total number of elements. It is sometimes loosely referred to as the “average.”
When all the values in a data set are not unique, the sum in the numerator can be calculated by multiplying each distinct value by its frequency.
Sometimes, the arithmetic mean of a sample can be affected by a few data points that are...
Quartile01:15

Quartile

Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
Data: Types and Distribution01:19

Data: Types and Distribution

In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...

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

Comment on "Symptom Relief and Practice Setting Variation in Bulkamid Injections for Stress Urinary Incontinence".

Neurourology and urodynamics·2026
Same author

Highly-destabilized ligand field excited states of iron carbene complexes and their relation to charge transfer state lifetimes.

Chemical science·2026
Same author

Effect of VTMS-Modified TiO<sub>2</sub> Nanoparticles on CO<sub>2</sub> Separation Performance of Polysulfone-Based Mixed Matrix Membranes.

Membranes·2025
Same author

Pulmonary Arterial Wedge Oxygen Saturation: Does It Confirm Wedge Position in Patients With Pulmonary Hypertension?

Pulmonary circulation·2025
Same author

Cobalt(II) Phthalocyanine Substituents Tune the Electrocatalytic CO<sub>2</sub> Conversion to Methanol.

Inorganic chemistry·2025
Same author

Long-term results of conservative and surgical treatment of congenital x-linked retinoschisis: A retrospective multicentre international study.

Acta ophthalmologica·2025

相关实验视频

Updated: May 13, 2026

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources
12:39

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

Published on: November 26, 2016

16.1K

ArEEG:一个开放的阿拉伯语内语EEG数据集

Donia Metwalli1, Antony E Kiroles2, Yousef A Radwan3

  • 1Center for Informatics Science (CIS), School of Information Technology and Computer Science, Nile University, 26th of July Corridor, Sheikh Zayed City, Giza, 12588, Egypt. d.khaled@nu.edu.eg.

Scientific data
|August 29, 2025
PubMed
概括

这项研究引入了一个新的阿拉伯语内在语音数据集,仅使用八个电极,使脑计算机接口 (BCI) 技术更容易获得. 这一数据集支持五种命令,

更多相关视频

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

2.1K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.6K

相关实验视频

Last Updated: May 13, 2026

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources
12:39

High-density Electroencephalographic Acquisition in a Rodent Model Using Low-cost and Open-source Resources

Published on: November 26, 2016

16.1K
Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

2.1K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.6K

科学领域:

  • 神经科学
  • 人与计算机的交互
  • 信号处理

背景情况:

  • 脑电脑接口 (BCI) 技术越来越多地专注于内在语言,而不是运动图像,以实现直观的设备控制.
  • 现有的BCI数据集通常需要多个电极,阻碍了成本效益和可访问系统的开发.
  • 缺乏公开可用的数据集限制了该领域的研究和开发.

研究的目的:

  • 推出一个新的,开放的阿拉伯语内语数据集用于脑电图 (EEG) 研究.
  • 为经济的BCI开发提供多类数据集 (五个命令),用最小数量的电极 (八个) 记录.
  • 促进阿拉伯语地区的BCI整合,并推进神经技术.

主要方法:

  • 开发一个新的阿拉伯语内语数据集.
  • 使用八个电极记录EEG数据.
  • 五种不同的内在语音命令的分类.

主要成果:

  • 创建了一个新的,具有成本效益的,多类阿拉伯语内语EEG数据集.
  • 该数据集仅使用八个电极,为BCI开发提供了经济的方法.
  • 数据集包括五个不同的类别,超过现有数据集的典型数量.

结论:

  • 开发的数据集解决了可访问和经济的BCI资源的需求.
  • 这项贡献支持神经技术和BCI应用在阿拉伯语社区的发展.
  • 开放式数据集将促进对特定语言的BCI开发的进一步研究和创新.