English
Related papers

Related papers: A Real-time Control Approach for Unmanned Aerial V…

200 papers

BCI systems are able to communicate directly between the brain and computer using neural activity measurements without the involvement of muscle movements. For BCI systems to be widely used by people with severe disabilities, long-term…

Human-Computer Interaction · Computer Science 2023-05-31 Krishna Pai , Rakhee Kallimani , Sridhar Iyer , B. Uma Maheswari , Rajashri Khanai , Dattaprasad Torse

Brain-computer interface (BCI) aims to establish and improve human and computer interactions. There has been an increasing interest in designing new hardware devices to facilitate the collection of brain signals through various…

Machine Learning · Computer Science 2020-08-19 Javad Rahimipour Anaraki , Jae Moon , Tom Chau

Non-invasive Brain-Computer Interfaces (BCI) offer a safe and accessible means of connecting the human brain to external devices, with broad applications in home and clinical settings to enhance human capabilities. However, the high noise…

Machine Learning · Computer Science 2025-08-06 Jiamin Wu , Zichen Ren , Junyu Wang , Pengyu Zhu , Yonghao Song , Mianxin Liu , Qihao Zheng , Lei Bai , Wanli Ouyang , Chunfeng Song

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…

Signal Processing · Electrical Eng. & Systems 2020-05-28 Abdul Moeed

This article presents a Visual Servoing Nonlinear Model Predictive Control (NMPC) scheme for autonomously tracking a moving target using multirotor Unmanned Aerial Vehicles (UAVs). The scheme is developed for surveillance and tracking of…

Brain-computer interface (BCI) builds a bridge between human brain and external devices by recording brain signals and translating them into commands for devices to perform the user's imagined action. The core of the BCI system is the…

Methodology · Statistics 2025-07-08 Jingyi Zheng , Huajun Huang , Yuyan Yi , Yuexin Li , Shu-Chin Lin

Similar to most of the real world data, the ubiquitous presence of non-stationarities in the EEG signals significantly perturb the feature distribution thus deteriorating the performance of Brain Computer Interface. In this letter, a novel…

Quantitative Methods · Quantitative Biology 2019-01-23 Satyam Kumar , Tharun Kumar Reddy , Laxmidhar Behera

Brain-computer interfaces (BCIs) provide a hands-free control modality for mobile robotics, yet decoding user intent during real-world navigation remains challenging. This work presents a brain-robot control framework for offline decoding…

The non-stationary characteristics of EEG signal and the individual differences of brain-computer interfaces (BCIs) lead to poor performance in the control process of the brain-controlled vehicles (BCVs). In this paper, by combining…

Neurons and Cognition · Quantitative Biology 2024-03-12 Hongguang Pan , Xinyu Yu , Yong Yang

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working…

Human-Computer Interaction · Computer Science 2021-08-27 Simanto Saha , Khondaker A. Mamun , Khawza Ahmed , Raqibul Mostafa , Ganesh R. Naik , Ahsan Khandoker , Sam Darvishi , Mathias Baumert

Autonomous tracking of flying aerial objects has important civilian and defense applications, ranging from search and rescue to counter-unmanned aerial systems (counter-UAS). Ground based tracking requires setting up infrastructure, could…

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…

The cognitive mechanisms underlying subjects' self-regulation in Brain-Computer Interface (BCI) and neurofeedback (NF) training remain poorly understood. Yet, a mechanistic computational model of each individual learning trajectory is…

Human-Computer Interaction · Computer Science 2024-10-10 Côme Annicchiarico , Fabien Lotte , Jérémie Mattout

Brain-computer interface (BCI) aims to decode motor intent from noninvasive neural signals to enable control of external devices, but practical deployment remains limited by noise and variability in motor imagery (MI)-based…

Machine Learning · Computer Science 2025-11-12 Si-Hyun Kim , Heon-Gyu Kwak , Byoung-Hee Kwon , Seong-Whan Lee

This paper addresses the problem of asymptotic tracking for high-order control-affine MIMO nonlinear systems with unknown dynamic terms subject to input and transient state constraints. We introduce Barrier Integral Control (BRIC), a novel…

Systems and Control · Electrical Eng. & Systems 2026-01-21 Christos K. Verginis

As autonomous service robots become more affordable and thus available also for the general public, there is a growing need for user friendly interfaces to control the robotic system. Currently available control modalities typically expect…

A brain-computer interface (BCI) based on electroencephalography (EEG) can be useful for rehabilitation and the control of external devices. Five grasping tasks were decoded for motor execution (ME) and motor imagery (MI). During this…

Human-Computer Interaction · Computer Science 2022-12-15 Jeong-Hyun Cho , Byoung-Hee Kwon , Byeong-Hoo Lee

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…

Human-Computer Interaction · Computer Science 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…

Machine Learning · Computer Science 2025-03-11 Jianchao Lu , Yuzhe Tian , Yang Zhang , Quan Z. Sheng , Xi Zheng

In this paper, we propose a conceptual framework for personalized brain-computer interface (BCI) applications, which can offer an enhanced user experience by customizing services to individual preferences and needs, based on endogenous…

Human-Computer Interaction · Computer Science 2024-11-19 Heon-Gyu Kwak , Gi-Hwan Shin , Yeon-Woo Choi , Dong-Hoon Lee , Yoo-In Jeon , Jun-Su Kang , Seong-Whan Lee
‹ Prev 1 4 5 6 7 8 10 Next ›