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Assistive mobile robots are a transformative technology that helps persons with disabilities regain the ability to move freely. Although autonomous wheelchairs significantly reduce user effort, they still require human input to allow users…

Robotics · Computer Science 2025-01-13 Xiaoshan Zhou , Carol M. Menassa , Vineet R. Kamat

Robots with wheeled, quadrupedal, or humanoid forms are increasingly integrated into built environments. However, unlike human social learning, they lack a critical pathway for intrinsic cognitive development, namely, learning from human…

Robotics · Computer Science 2025-04-15 Xiaoshan Zhou , Carol C. Menassa , Vineet R. Kamat

Motor imagery (MI)-based brain-computer interface (BCI) systems are being increasingly employed to provide alternative means of communication and control for people suffering from neuro-motor impairments, with a special effort to bring…

Machine Learning · Computer Science 2022-04-11 Alberto Zancanaro , Giulia Cisotto , João Ruivo Paulo , Gabriel Pires , Urbano J. Nunes

Many real-world brain-computer interface (BCI) applications rely on single-trial classification of event-related potentials (ERPs) in EEG signals. However, because different subjects have different neural responses to even the same…

Machine Learning · Computer Science 2020-02-13 Dongrui Wu

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…

Human-Computer Interaction · Computer Science 2021-06-11 Dalin Zhang , Lina Yao , Xiang Zhang , Sen Wang , Weitong Chen , Robert Boots

Recent advances in deep learning have had a methodological and practical impact on brain-computer interface research. Among the various deep network architectures, convolutional neural networks have been well suited for…

Signal Processing · Electrical Eng. & Systems 2020-03-06 Wonjun Ko , Eunjin Jeon , Seungwoo Jeong , Heung-Il Suk

Brain Computer Interface (BCI) can help patients of neuromuscular diseases restore parts of the movement and communication abilities that they have lost. Most of BCIs rely on mapping brain activities to device instructions, but limited…

Human-Computer Interaction · Computer Science 2017-05-23 Kang Wang , Xueqian Wang , Gang Li

A class of brain computer interfaces (BCIs) employs noninvasive recordings of electroencephalography (EEG) signals to enable users with severe speech and motor impairments to interact with their environment and social network. For example,…

Human-Computer Interaction · Computer Science 2017-10-11 Mohammad Moghadamfalahi , Murat Akcakaya , Hooman Nezamfar , Jamshid Sourati , Deniz Erdogmus

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…

Signal Processing · Electrical Eng. & Systems 2020-06-24 Bingchuan Liu , Xiaoshan Huang , Yijun Wang , Xiaogang Chen , Xiaorong Gao

In this paper we introduce the concept of Brain-Computer Interface (BCI) inhibitor, which is meant to standby the BCI until the user is ready, in order to improve the overall performance and usability of the system. BCI inhibitor can be…

Human-Computer Interaction · Computer Science 2011-11-09 Laurent George , Laurent Bonnet , Anatole Lécuyer

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

A calibration procedure is required in motor imagery-based brain-computer interface (MI-BCI) to tune the system for new users. This procedure is time-consuming and prevents na\"ive users from using the system immediately. Developing a…

Signal Processing · Electrical Eng. & Systems 2022-04-20 Navid Ayoobi , Elnaz Banan Sadeghian

Imagine unlocking the power of the mind to communicate, create, and even interact with the world around us. Recent breakthroughs in Artificial Intelligence (AI), especially in how machines "see" and "understand" language, are now fueling…

Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) is a direct communication pathway between the human brain and a computer. Most research so far studied more accurate BCIs, but much less attention has been paid…

Human-Computer Interaction · Computer Science 2024-11-19 Xiaoqing Chen , Siyang Li , Yunlu Tu , Ziwei Wang , Dongrui Wu

Brain-Machine Interaction (BMI) system motivates interesting and promising results in forward/feedback control consistent with human intention. It holds great promise for advancements in patient care and applications to neurorehabilitation.…

Human-Computer Interaction · Computer Science 2017-11-21 Reza Abiri , Soheil Borhani , Xiaopeng Zhao , Yang Jiang

Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices, providing critical support for individuals with motor impairments. However, accurate motor imagery (MI) decoding from…

Machine Learning · Computer Science 2026-04-08 Panagiotis Andrikopoulos , Siamak Mehrkanoon

A brain-computer interface (BCI) is a technology that enables direct communication between the brain and an external device or computer system. It allows individuals to interact with the device using only their thoughts, and holds immense…

Human-Computer Interaction · Computer Science 2023-05-23 Xin Zhou , Botao Hao , Jian Kang , Tor Lattimore , Lexin Li

Motor imagery-based brain-computer interfaces (BCIs) use an individuals ability to volitionally modulate localized brain activity as a therapy for motor dysfunction or to probe causal relations between brain activity and behavior. However,…

Brain-Computer Interface (BCI) systems allow users to perform actions by translating their brain activity into commands. Such systems usually need a training phase, consisting in training a classification algorithm to discriminate between…

Neurons and Cognition · Quantitative Biology 2023-12-14 Arthur Desbois , Tristan Venot , Fabrizio De Vico Fallani , Marie-Constance Corsi

Neurophysiological studies are typically conducted in laboratories with limited ecological validity, scalability, and generalizability of findings. This is a significant challenge for the development of brain-computer interfaces (BCIs),…

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