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Brain-computer interfaces (BCIs) provide alternative communication methods for individuals with motor disabilities by allowing control and interaction with external devices. Non-invasive BCIs, especially those using electroencephalography…

机器学习 · 计算机科学 2025-02-27 Aline Xavier Fidêncio , Felix Grün , Christian Klaes , Ioannis Iossifidis

Human-Computer Interaction (HCI) provides a new communication channel between human and the computer. We develop an assistive system based on block scanning techniques using eye blinks that presents a hands-free interface between human and…

人机交互 · 计算机科学 2020-01-01 Supriya Sarker , Md. Shahraduan Mazumder , Md. Sajedur Rahman , Md. Anayt Rabbi

Objective: This paper targets a major challenge in developing practical EEG-based brain-computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, with minimum…

机器学习 · 计算机科学 2019-04-03 He He , Dongrui Wu

P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and non-target stimulus categories during model training, which imparts bias…

神经元与认知 · 定量生物学 2018-10-31 Jonathan R. McDaniel , Stephen M. Gordon , Amelia J. Solon , Vernon J. Lawhern

New mental tasks were investigated for suitability in Brain-Computer Interface (BCI). Electroencephalography (EEG) signals were collected and analyzed to identify these mental tasks. MS Windows-based software was developed for investigating…

人机交互 · 计算机科学 2023-07-07 Zahmeeth Sayed Sakkaff

Hull is an accelerator-rich distributed implantable Brain-Computer Interface (BCI) that reads biological neurons at data rates that are 2-3 orders of magnitude higher than the prior state of art, while supporting many neuroscientific…

Brain--computer interfaces are groundbreaking technology whereby brain signals are used to control external devices. Despite some advances in recent years, electroencephalogram (EEG)-based motor-imagery tasks face challenges, such as…

人机交互 · 计算机科学 2025-02-26 Jianchao Lu , Yuzhe Tian , Yang Zhang , Quan Z. Sheng , Xi Zheng

Brain--computer interfaces are groundbreaking technology whereby brain signals are used to control external devices. Despite some advances in recent years, electroencephalogram (EEG)-based motor-imagery tasks face challenges, such as…

机器学习 · 计算机科学 2025-03-11 Jianchao Lu , Yuzhe Tian , Yang Zhang , Quan Z. Sheng , Xi Zheng

We describe the experimental procedures for a dataset that we have made publicly available at https://doi.org/10.5281/zenodo.1494163 in mat and csv formats. This dataset contains electroencephalographic (EEG) recordings of 24 subjects doing…

Brain-computer interface (BCI) technology enables direct communication between the brain and external devices, allowing individuals to control their environment using brain signals. However, existing BCI approaches face three critical…

信号处理 · 电气工程与系统科学 2023-08-21 Sidharth Pancholi , Amita Giri

Developments in Brain Computer Interfaces (BCIs) are empowering those with severe physical afflictions through their use in assistive systems. Common methods of achieving this is via Motor Imagery (MI), which maps brain signals to code for…

信号处理 · 电气工程与系统科学 2020-05-28 Abdul Moeed

Myoelectric interfaces enable intuitive and natural control by decoding residual muscle activity, providing an effective pathway for motor restoration in individuals with preserved musculature. However, in patients with severe muscular…

神经元与认知 · 定量生物学 2025-11-26 Sun Ye , Zuo Cuiming , Zhang Rui , Shi Bin , Pang Yajing , Gao Lingyun , Zhao Bowei , Wang Jing , Yao Dezhong , Liu Gang

Human-machine interactions are being increasingly explored to create alternative ways of communication and to improve our daily life. Based on a classification of the user's intention from the user's underlying neural activity,…

神经元与认知 · 定量生物学 2020-01-07 Fabrizio De Vico Fallani , Danielle S. Bassett

This article proposes a novel framework that utilizes an over-the-air Brain-Computer Interface (BCI) to learn Metaverse users' expectations. By interpreting users' brain activities, our framework can optimize physical resources and enhance…

人机交互 · 计算机科学 2024-10-10 Nguyen Quang Hieu , Dinh Thai Hoang , Diep N. Nguyen , Van-Dinh Nguyen , Yong Xiao , Eryk Dutkiewicz

The devices that can read Electroencephalography (EEG) signals have been widely used for Brain-Computer Interfaces (BCIs). Popularity in the field of BCIs has increased in recent years with the development of several consumer-grade EEG…

人机交互 · 计算机科学 2022-04-25 Cameron Aume , Shantanu Pal , Subhas Mukhopadhyay

Brain-computer interface (BCI) is the technology that enables the communication between humans and devices by reflecting status and intentions of humans. When conducting imagined speech, the users imagine the pronunciation as if actually…

人机交互 · 计算机科学 2021-12-15 Dae-Hyeok Lee , Sung-Jin Kim , Keon-Woo Lee

A Brain-Computer Interface (BCI) is a system that measures central nervous system activity and translates the recorded data into an output suitable for a computer to use as an input signal. Such a BCI system consists of three parts, the…

人机交互 · 计算机科学 2014-12-22 Bastian Venthur , Benjamin Blankertz

Human Computer Interaction (HCI) has been redefined in this era. People want to interact with their devices in such a way that has physical significance in the real world, in other words, they want ergonomic input devices. In this paper, we…

人机交互 · 计算机科学 2016-06-24 Sayem Mohammad Siam , Jahidul Adnan Sakel , Md. Hasanul Kabir

Brain computer interfaces (BCIs) offer individuals suffering from major disabilities an alternative method to interact with their environment. Sensorimotor rhythm (SMRs) based BCIs can successfully perform control tasks; however, the…

A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most research so far focuses on…

人机交互 · 计算机科学 2024-12-17 K. Xia , W. Duch , Y. Sun , K. Xu , W. Fang , H. Luo , Y. Zhang , D. Sang , X. Xu , F-Y Wang , D. Wu