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Brain-computer interfaces (BCIs), particularly the P300 BCI, facilitate direct communication between the brain and computers. The fundamental statistical problem in P300 BCIs lies in classifying target and non-target stimuli based on…

应用统计 · 统计学 2024-02-16 Bangyao Zhao , Jane E. Huggins , Jian Kang

The brain computer interface (BCI) is a nonstimulatory direct and occasionally bidirectional communication link between the brain and a computer or an external device. Classically, EEG-based BCI algorithms have relied on models such as…

信号处理 · 电气工程与系统科学 2022-08-19 Andrea Duggento , Mario De Lorenzo , Stefano Bargione , Allegra Conti , Vincenzo Catrambone , Gaetano Valenza , Nicola Toschi

As brain-computer interfacing (BCI) systems transition from assistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important. Dynamic stopping methods enhance BCI system speed by…

人机交互 · 计算机科学 2024-06-18 Sara Ahmadi , Peter Desain , Jordy Thielen

In brain machine interfaces (BMI) that are used to control motor rehabilitation devices there is the need to process the monitored brain signals with the purpose of recognizing patient's intentions to move his hands or limbs and reject…

人机交互 · 计算机科学 2018-05-09 Kalogiannis Gregory , Karampelas Nikolaos , Hassapis George

Electroencephalography (EEG) has become one of the key modalities underpinning brain-computer interfaces (BCIs) due to its high temporal resolution, rapid responsiveness, non-invasiveness, low cost, and portability. However, EEG signals are…

神经元与认知 · 定量生物学 2026-04-17 Yihang Dong , Changhong Jing , Shuqiang Wang

One of the main causes of long-term prosthetic abandonment is the lack of ownership over the prosthesis, caused mainly by the absence of sensory information regarding the lost limb. One strategy to overcome this problem is to provide…

We present a hybrid brain-machine interface (BMI) that integrates steady-state visually evoked potential (SSVEP)-based EEG and facial EMG to improve multimodal control and mitigate fatigue in assistive applications. Traditional BMIs relying…

Motivated by the inconceivable capability of the human brain in simultaneously processing multi-modal signals and its real-time feedback to the outer world events, there has been a surge of interest in establishing a communication bridge…

信号处理 · 电气工程与系统科学 2020-02-04 Soroosh Shahtalebi , Amir Asif , Arash Mohammadi

For social robots to maintain long-term engagement as exercise instructors, rapport-building is essential. Motor mimicry--imitating one's physical actions--during social interaction has long been recognized as a powerful tool for fostering…

We study the performance of brain computer interface (BCI) system in a virtual reality (VR) environment and compare it to 2D regular displays. First, we design a headset that consists of three components: a wearable electroencephalography…

人机交互 · 计算机科学 2020-06-19 Reza Abbasi-Asl , Mohammad Keshavarzi , Dorian Yao Chan

Brain-Computer Interface (BCI) is a system empowering humans to communicate with or control the outside world with exclusively brain intentions. Electroencephalography (EEG) based BCIs are promising solutions due to their convenient and…

人机交互 · 计算机科学 2021-06-11 Dalin Zhang , Lina Yao , Xiang Zhang , Sen Wang , Weitong Chen , Robert Boots

Stroke is the leading cause of serious and long-term disability worldwide. Some studies have shown that motor imagery (MI) based BCI has a positive effect in poststroke rehabilitation. It could help patients promote the reorganization…

人机交互 · 计算机科学 2018-05-15 Zhaoyang Qiu , Shugeng Chen , Ian Daly , Jie Jia , Xingyu Wang , Jing Jin

Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (ALS). However, to maintain high performance over time, iBCIs…

Controlling the surrounding world and predicting future events has always seemed like a dream, but that could become a reality using a Brain-Computer/Machine Interface (BCI/BMI). Epilepsy is a group of neurological diseases characterized by…

信号处理 · 电气工程与系统科学 2019-06-10 Zaghloul Saad Zaghloul , Magdy Bayoumi

A brain--machine interface (BMI) based on motor imagery (MI) enables the control of devices using brain signals while the subject imagines performing a movement. It plays a vital role in prosthesis control and motor rehabilitation. To…

信号处理 · 电气工程与系统科学 2024-09-20 Xiaying Wang , Michael Hersche , Michele Magno , Luca Benini

A multitude of individuals across the globe grapple with motor disabilities. Neural prosthetics utilizing Brain-Computer Interface (BCI) technology exhibit promise for improving motor rehabilitation outcomes. The intricate nature of EEG…

信号处理 · 电气工程与系统科学 2025-02-21 Syed Saim Gardezi , Soyiba Jawed , Mahnoor Khan , Muneeba Bukhari , Rizwan Ahmed Khan

One of the current issues in Brain-Computer Interface is how to deal with noisy Electroencephalography measurements organized as multidimensional datasets. On the other hand, recently, significant advances have been made in multidimensional…

定量方法 · 定量生物学 2018-07-27 Jordi Sole-Casals , Cesar F. Caiafa , Qibin Zhao , Adrzej Cichocki

Due to hemiparesis, stroke survivors frequently develop a dysfunctional gait that is often characterized by an overall decrease in walking speed and a unilateral decrease in step length. With millions currently affected by this…

机器人学 · 计算机科学 2025-12-04 Vaughn Chambers , Panagiotis Artemiadis

Brain-computer interfaces (BCIs) allow users to control computer applications by modulating their brain activity. Since BCIs rely solely on brain activity, they have enormous potential as an alternative access method for engaging children…

人机交互 · 计算机科学 2021-05-27 Javad Rahimipour Anaraki , Chelsea Anne Rauh , Jason Leung , Tom Chau

Non-invasive brain-computer interfaces (BCIs) have the potential to enable intuitive control of prosthetic limbs for individuals with upper limb amputations. However, existing EEG-based control systems face challenges related to signal…

人机交互 · 计算机科学 2025-11-21 Abdul Basit , Maha Nawaz , Muhammad Shafique