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Brain-Computer Interfaces (BCIs) implement a direct communication pathway between the brain of an user and an external device, as a computer or a machine in general. One of the most used brain responses to implement non-invasive BCIs is the…

人机交互 · 计算机科学 2016-11-16 Enrico Calore

A brain-computer interface (BCI) facilitates direct communication between the brain and external equipment through EEG, which is preferred for its superior temporal resolution. Among EEG techniques, the steady-state visual evoked potential…

人机交互 · 计算机科学 2025-04-22 Saif Bashar , Samia Nasir Nira , Shabbir Mahmood , Md. Humaun Kabir , Sujit Roy , Iffat Farhana

The steady-state visual evoked potential (SSVEP) is one of the most widely used modalities in brain-computer interfaces (BCIs) due to its many advantages. However, the existence of harmonics and the limited range of responsive frequencies…

神经元与认知 · 定量生物学 2021-08-12 Jing Mu , David B. Grayden , Ying Tan , Denny Oetomo

Brain-Computer Interfaces (BCIs) based on Steady State Visually Evoked Potentials (SSVEPs) have proven effective and provide significant accuracy and information-transfer rates. This family of strategies, however, requires external devices…

信号处理 · 电气工程与系统科学 2022-04-26 Arturo Micheli , Davide Consoli , Adrien Merlini , Paolo Ricci , Francesco P. Andriulli

In brain-computer interface (BCI) systems, steady-state visual evoked potentials (SSVEP) and P300 responses have achieved widespread implementation owing to their superior information transfer rates (ITR) and minimal training requirements.…

信息检索 · 计算机科学 2025-09-22 Ekgari Kasawala , Surej Mouli

Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities. Among the existing solutions the systems relying on electroencephalograms…

Brain-computer interfaces (BCI) have the potential to play a vital role in future healthcare technologies by providing an alternative way of communication and control. More specifically, steady-state visual evoked potential (SSVEP) based…

人机交互 · 计算机科学 2016-09-13 A. Fatih Demir , Huseyin Arslan , Ismail Uysal

Steady State Visual Evoked Potential (SSVEP) methods for brain computer interfaces (BCI) are popular due to higher information transfer rate and easier setup with minimal training, compared to alternative methods. With precisely generated…

人机交互 · 计算机科学 2025-09-22 Surej Mouli , Ramaswamy Palaniappan , Emmanuel Molefi , Ian McLoughlin

Brain-computer interfaces (BCIs) and their associated technologies have the potential to shape future forms of communication, control, and security. Specifically, the steady-state visual evoked potential (SSVEP) based BCIs have the…

信号处理 · 电气工程与系统科学 2019-11-04 Ali Fatih Demir , Hüseyin Arslan , Ismail Uysal

Brain-Computer Interface (BCI) initially gained attention for developing applications that aid physically impaired individuals. Recently, the idea of integrating BCI with Augmented Reality (AR) emerged, which uses BCI not only to enhance…

人机交互 · 计算机科学 2023-08-15 Yasmine Mustafa , Mohamed Elmahallawy , Tie Luo , Seif Eldawlatly

Steady-state visually evoked potentials (SSVEP)-based brain-computer interfaces (BCIs) are widely used due to their high signal-to-noise ratio and user-friendliness. Accurate decoding of SSVEP signals is crucial for interpreting user…

机器学习 · 计算机科学 2026-01-30 Weiguang Wang , Yong Liu , Yingjie Gao , Guangyuan Xu

Steady-state visual evoked potential (SSVEP) recognition methods are equipped with learning from the subject's calibration data, and they can achieve extra high performance in the SSVEP-based brain-computer interfaces (BCIs), however their…

计算机视觉与模式识别 · 计算机科学 2022-04-19 Vangelis P. Oikonomou

Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram…

Steady-State Visual Evoked Potential is a brain response to visual stimuli flickering at constant frequencies. It is commonly used in brain-computer interfaces for direct brain-device communication due to their simplicity, minimal training…

人机交互 · 计算机科学 2025-06-03 Chenlong Wang , Jiaao Li , Shuailei Zhang , Wenbo Ding , Xinlei Chen

Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) offer a non-invasive means of communication through high-speed speller systems. However, their efficiency heavily relies on individual training data…

机器学习 · 计算机科学 2023-11-22 Sung-Yu Chen , Chi-Min Chang , Kuan-Jung Chiang , Chun-Shu Wei

We proposed a novel visual stimulus for brain-computer interface. The stimulus is in the form gaiting sequence of a human. The hypothesis is that observing such a visual stimulus would simultaneously induce 1) steady-state motion visual…

信号处理 · 电气工程与系统科学 2021-03-11 Xin Zhang , Guanghua Xu , Aravind Ravi , Sarah Pearce , Ning Jiang

A fully customisable chip-on board (COB) LED design to evoke two brain responses simultaneously (steady state visual evoked potential (SSVEP) and transient evoked potential, P300) is discussed in this paper. Considering different possible…

信号处理 · 电气工程与系统科学 2025-08-05 Surej Mouli , Ramaswamy Palaniappan

A brain-computer interface (BCI) is a system that allows a person to communicate or control the surroundings without depending on the brain's normal output pathways of peripheral nerves and muscles. A lot of successful applications have…

人机交互 · 计算机科学 2023-07-18 Ce Zhou

Brain-computer interface (BCI) provides an alternative means to communicate and it has sparked growing interest in the past two decades. Specifically, for Steady-State Visual Evoked Potential based BCI, marked improvement has been made in…

信号处理 · 电气工程与系统科学 2020-06-24 Bingchuan Liu , Xiaoshan Huang , Yijun Wang , Xiaogang Chen , Xiaorong Gao

The key to electroencephalography (EEG)-based brain-computer interface (BCI) lies in neural decoding, and its accuracy can be improved by using hybrid BCI paradigms, that is, fusing multiple paradigms. However, hybrid BCIs usually require…

机器学习 · 计算机科学 2022-12-13 Wenwei Luo , Wanguang Yin , Quanying Liu , Youzhi Qu
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