Relevant bibliographies by topics / BCI - Brain Computer Interface

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'BCI - Brain Computer Interface'

Author: Grafiati
Published: 5 September 2021
Last updated: 29 July 2025

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Journal articles on the topic "BCI - Brain Computer Interface"

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Lu, Junshi, and Yujia Peng. "Brain-Computer Interface for Cyberpsychology." International Journal of Cyber Behavior, Psychology and Learning 4, no. 1 (2014): 1–14. http://dx.doi.org/10.4018/ijcbpl.2014010101.

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As a new way of implementing human-computer interface, brain-computer interfaces (BCI) dramatically change the user experiences and have broad applications in cyber behavior research. This methodological review attempts to provide an overall picture of the BCI science and its role in cyberpsychology. After an introduction of BCI and the literature search methods used in this review, we offer an overview of terms, history, components, methods and signals used in BCI. Different applications of BCI on both the clinical population and the healthy population are summarized in detail, with a conclus
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Vanshi, Sharma. "Brain Computer Interface." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 464–73. https://doi.org/10.35940/ijeat.F1609.089620.

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Computer Technology is advancing day by day and with that it has led to the idea of Brain Computer interaction. Modern computers are advancing parallelly to our understanding of the human brain. This paper basically deals with the technology of BCI (Brain Computer Interface) that can capture brain signals and translate these signals into commands that will allow humans to control devices just by thinking. These devices can be robots, computers or virtual reality environment. The basis of BCI is a pathway connecting the brain and an external device. The aim is to assist, augment or repair human
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Mridha, M. F., Sujoy Chandra Das, Muhammad Mohsin Kabir, Aklima Akter Lima, Md Rashedul Islam, and Yutaka Watanobe. "Brain-Computer Interface: Advancement and Challenges." Sensors 21, no. 17 (2021): 5746. http://dx.doi.org/10.3390/s21175746.

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Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the last decades, several groundbreaking research has been conducted in this domain. Still, no comprehensive review that covers the BCI domain completely has been conducted yet. Hence, a comprehensive overview of the BCI domain is presented in this study. This study covers several applications of BCI and upholds the significance of this domain. Then, each element of BCI systems, including techniques, datasets, feature extr
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Sreejith, S., M. Saminathan, K. Vishnu, and M. Vikash. "Advancements and Applications of Brain-Computer Interface Technology in Healthcare -A Review." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43406.

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For centuries, scientists, academics, and engineers have been fascinated by the human brain, which is considered the most advanced organ. Exploration of the human brain's capacities and complexities is intriguing and exciting, stretching the limits of neuroscience and technology. Among the most noteworthy developments in this field is the creation of the Brain-Computer Interface (BCI) technology, which creates an amazing link between the human brain and machines or computers. The BCI system offers the possibility to connect with the human brain or thinking through technology, representing a so
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Rezeika, Aya, Mihaly Benda, Piotr Stawicki, Felix Gembler, Abdul Saboor, and Ivan Volosyak. "Brain–Computer Interface Spellers: A Review." Brain Sciences 8, no. 4 (2018): 57. http://dx.doi.org/10.3390/brainsci8040057.

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A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradig
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Büyükgöze, Selma. "THE BRAIN-COMPUTER INTERFACE." International Conference on Technics, Technologies and Education, ICTTE 2019 (2019): 133–38. http://dx.doi.org/10.15547/ictte.2019.02.094.

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The Brain-Computer Interface (BCI), defined as systems that allow people to use a computer, an electromechanical arm or various neuroprostheses without the use of motor nervous systems, is a communication pathway used to establish direct communication between the brain and a peripheral interface. The brain-computer interface is often used to help or repair human cognitive or sensory motor functions. However, with today's developing technology, it hasn’t only been used for this purpose and has started to be used in many different areas from advertising, to smart peripheral systems, to games, ev
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Korotenko, YA S., YU I. Yakymenko, A. O. Popov, YE S. Karplyuk, and M. A. Tsyparsʹkyy. "Electrooculographic brain-computer interface system." Electronics and Communications 16, no. 3 (2011): 162–66. http://dx.doi.org/10.20535/2312-1807.2011.16.3.266312.

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Problems of brain-computer interface (BCI) systems construction are considered. The fundamentals of constructing BCI systems using the electrooculogram are presented. A method and software for determining eye rotation angle by a frequency-modulated electrooculographic signal processing are given
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Li, Shuangjie. "Brain-Computer Interface Technologies for Neurological Diseases." Highlights in Science, Engineering and Technology 36 (March 21, 2023): 593–97. http://dx.doi.org/10.54097/hset.v36i.5741.

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A Brain-Computer Interface (BCI) is a device that monitors central nervous system (CNS) activity and transforms it into artificial output that can be used to replace, improve, supplement, or restore the natural CNS output. Brain-Computer Interface (BCI) technologies for neurological diseases are vital for the well-being of related patients. This paper presents 4 forms of BCI technologies used for neurological diseases: EEG-based BCI for the treatment of Attention Deficit Hyperactivity Disorder (ADHD), Neural Cursor and BCI Spellers for ALS patients, Seizure Prediction BCI for those with epilep
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Lebedev, M. A. "BRAIN-COMPUTER INTERFACE FOR THE AUGMENTATION OF BRAIN FUNCTIONS." Science and Innovations in Medicine 1, no. 3 (2016): 11–27. http://dx.doi.org/10.35693/2500-1388-2016-0-3-11-27.

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Brain-computer interface (BCI) connects the nervous system departments with external devices for the purpose of recovery of motor and sensory functions of patients with neurological lesions. Over the past half-century BCI have gone from initial ideas to the high-tech modern incarnations. This development contributed significantly to the invasive techniques of multichannel registration activity of neuronal ensembles. Modern BCI are able to manage mechanical prosthetic arms and legs. Furthermore, BCI can provide sensory feedback, allowing the user to feel the movement of the prosthesis and its i
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Mouček, Roman, Lukáš Vařeka, Petr Brůha, and Pavel Šnejdar. "On applications of brain-computer interface." Acta Polytechnica CTU Proceedings 39 (December 15, 2022): 32–40. http://dx.doi.org/10.14311/app.2022.39.0032.

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Brain-computer interface (BCI) applications implement a direct communication path between the brain and the computer. This paper deals with the fundamentals of BCI systems and the experience of the neuroinformatics team with the design and implementation of various BCI applications. Their advantages, drawbacks and suitability are discussed in multiple contexts.
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Dissertations / Theses on the topic "BCI - Brain Computer Interface"

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Petrucci, Maila. "Sistemi Brain Computer Interface: dalla macchina al paziente." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10137/.

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C’è un crescente interesse nella comunità scientifica per l’applicazione delle tecniche della bioingegneria nel campo delle interfacce fra cervello e computer. Questo interesse nasce dal fatto che in Europa ci sono almeno 300.000 persone con paralisi agli arti inferiori, con una età media piuttosto bassa (31 anni), registrandosi circa 5.000 nuovi casi ogni anno, in maggioranza dovuti ad incidenti automobilistici. Tali lesioni traumatiche spinali inducono delle disfunzioni sensoriali a causa dell’interruzione tra gli arti e i centri sopraspinali. Per far fronte a questi problemi gli scienziati
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Lind, Carl Jonas. "Brain Computer Interface (BCI) : - Översiktsartikel utifrån ett neuropsykologiskt perspektiv med tillämpningar och enkätundersökning." Thesis, Stockholms universitet, Psykologiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-186099.

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Syftet med uppsatsen är att ge en uppdaterad översikt av området BCI (Brain Computer Interface) och undersöka vad som hänt sedan begreppet introducerades i forskningssammanhang; vilka praktiska resultat forskningen lett till och vilka tillämpningar som tillkommit. Metoden som företrädesvis används är litteraturstudie som tecknar bakgrund och enkät. Därefter följer en diskussion där utmaningar för framtiden, potential och tillämpningar i BCI-tekniken behandlas utifrån ett neuropsykologiskt perspektiv. Kommer BCI-tekniken att implementeras på samma sätt som radio, TV och telekommunikationer i sa
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Del, Monte Tamara. "Utilizzo dell'elettroencefalografia per la brain-computer interface." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9220/.

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Con Brain-Computer Interface si intende un collegamento diretto tra cervello e macchina, che essa sia un computer o un qualsiasi dispositivo esterno, senza l’utilizzo di muscoli. Grazie a sensori applicati alla cute del cranio i segnali cerebrali del paziente vengono rilevati, elaborati, classificati (per mezzo di un calcolatore) e infine inviati come output a un device esterno. Grazie all'utilizzo delle BCI, persone con gravi disabilità motorie o comunicative (per esempio malati di SLA o persone colpite dalla sindrome del chiavistello) hanno la possibilità di migliorare la propria qualità di
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Bhalotiya, Anuj Arun. "Brain Computer Interface (BCI) Applications: Privacy Threats and Countermeasures." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984122/.

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In recent years, brain computer interfaces (BCIs) have gained popularity in non-medical domains such as the gaming, entertainment, personal health, and marketing industries. A growing number of companies offer various inexpensive consumer grade BCIs and some of these companies have recently introduced the concept of BCI "App stores" in order to facilitate the expansion of BCI applications and provide software development kits (SDKs) for other developers to create new applications for their devices. The BCI applications access to users' unique brainwave signals, which consequently allows them t
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JUBIEN, Guillaume. "Decoding Electrocorticography Signals by Deep Learning for Brain-Computer Interface." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-243903.

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Brain-Computer Interface (BCI) offers the opportunity to paralyzed patients to control their movements without any neuromuscular activity. Signal processing of neuronal activity enables to decode movement intentions. Ability for patient to control an effector is closely linked to this decoding performance. In this study, I tackle a recent way to decode neuronal activity: Deep learning. The study is based on public data extracted by Schalk et al. for BCI Competition IV. Electrocorticogram (ECoG) data from three epileptic patients were recorded. During the experiment setup, the team asked subjec
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Sicbaldi, Marcello. "Brain-Computer Interface per riabilitazione motoria e cognitiva." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18556/.

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Pazienti con lesioni cerebrali o spinali possono essere affetti da gravi deficit nelle funzioni sensoriali, motorie e comunicative; sono perciò sempre più necessarie tecniche di riabilitazione avanzate, personalizzate e adattative, per limitare i deficit insorti e restituire al paziente una vita il più normale possibile. Negli ultimi decenni, numerosi gruppi di ricerca hanno sviluppato Brain-Computer Interface (BCI) basate sul segnale elettroencefalografico (EEG) con l’obbiettivo di fornire mezzi di comunicazione o riabilitazione motoria funzionale. Tuttavia, le tecnologie BCI hanno un ampio p
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Szafir, Daniel J. "Non-Invasive BCI through EEG." Thesis, Boston College, 2010. http://hdl.handle.net/2345/1208.

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Thesis advisor: Robert Signorile<br>It has long been known that as neurons fire within the brain they produce measurable electrical activity. Electroencephalography (EEG) is the measurement and recording of these electrical signals using sensors arrayed across the scalp. Though there is copious research in using EEG technology in the fields of neuroscience and cognitive psychology, it is only recently that the possibility of utilizing EEG measurements as inputs in the control of computers has emerged. The idea of Brain-Computer Interfaces (BCIs) which allow the control of devices using brain s
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Belluomo, Paola. "New proposals for EEG and fMRI based Brain Computer Interface technology." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1305.

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In this manuscript three related aspects of research on BCI systems were discussed. These aspects were the evaluation of a nonlinear feature extraction algorithm for BCI, the analysis of the functional connectivity between the signals acquired in different brain regions when a user performs an operant conditioning paradigm with fMRI based BCI technology, and the development of BCIs applications for disabled subjects. We have introduced a new EEG signals features extraction techniques based on nonlinear time series analysis. This signal processing approach was tested offline considering three s
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Clanton, Samuel T. "Brain-Computer Interface Control of an Anthropomorphic Robotic Arm." Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/170.

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This thesis describes a brain-computer interface (BCI) system that was developed to allow direct cortical control of 7 active degrees of freedom in a robotic arm. Two monkeys with chronic microelectrode implants in their motor cortices were able to use the arm to complete an oriented grasping task under brain control. This BCI system was created as a clinical prototype to exhibit (1) simultaneous decoding of cortical signals for control of the 3-D translation, 3-D rotation, and 1-D finger aperture of a robotic arm and hand, (2) methods for constructing cortical signal decoding models based on
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Boldeanu, Silvia. "Merging brain-computer interfaces and virtual reality : A neuroscientific exploration." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15774.

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Brain-computer interfaces (BCIs) blend methods and concepts researched by cognitive neuroscience, electrophysiology, computer science and engineering, resulting in systems of bi-directional information exchange directly between brain and computer. BCIs contribute to medical applications that restore communication and mobility for disabled patients and provide new forms of sending information to devices for enhancement and entertainment. Virtual reality (VR) introduces humans into a computer-generated world, tackling immersion and involvement. VR technology extends the classical multimedia expe
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Books on the topic "BCI - Brain Computer Interface"

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Guger, Christoph, Brendan Z. Allison, and Michael Tangermann, eds. Brain-Computer Interface Research. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60460-8.

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Guger, Christoph, Brendan Z. Allison, and Aysegul Gunduz, eds. Brain-Computer Interface Research. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79287-9.

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Guger, Christoph, Brendan Allison, and Mikhail Lebedev, eds. Brain-Computer Interface Research. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64373-1.

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Guger, Christoph, Natalie Mrachacz-Kersting, and Brendan Z. Allison, eds. Brain-Computer Interface Research. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05668-1.

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Guger, Christoph, Theresa Vaughan, and Brendan Allison, eds. Brain-Computer Interface Research. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09979-8.

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Guger, Christoph, Brendan Z. Allison, and Günter Edlinger, eds. Brain-Computer Interface Research. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36083-1.

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Guger, Christoph, Brendan Z. Allison, and Kai Miller, eds. Brain–Computer Interface Research. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49583-1.

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Guger, Christoph, Gernot Müller-Putz, and Brendan Allison, eds. Brain-Computer Interface Research. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25190-5.

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Clément, Claude. Brain-Computer Interface Technologies. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27852-6.

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Guger, Christoph, Brendan Allison, and Junichi Ushiba, eds. Brain-Computer Interface Research. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57132-4.

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Book chapters on the topic "BCI - Brain Computer Interface"

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Sood, Suraj. "Brain–Computer Interface (BCI)." In Brain Technology in Augmented Cognition. CRC Press, 2024. http://dx.doi.org/10.1201/9781032692982-5.

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Tang, Alan. "Brain–Computer Interface (BCI)." In Safeguarding the Future. CRC Press, 2025. https://doi.org/10.1201/9781003390695-14.

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Kalcher, J., D. Flotzinger, S. Gölly, Ch Neuper, and G. Pfurtscheller. "Graz Brain-Computer Interface (BCI) II." In Computers for Handicapped Persons. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58476-5_121.

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Chaudhary, Ujwal. "What Is Brain-Computer Interface (BCI)?" In Expanding Senses using Neurotechnology. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-78991-5_1.

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Brunner, Peter, and Gerwin Schalk. "BCI Software." In Brain–Computer Interfaces Handbook. CRC Press, 2018. http://dx.doi.org/10.1201/9781351231954-17.

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Looney, David, Preben Kidmose, and Danilo P. Mandic. "Ear-EEG: User-Centered and Wearable BCI." In Brain-Computer Interface Research. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54707-2_5.

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Guger, Christoph, Brendan Allison, and E. C. Leuthardt. "Recent Advances in Brain-Computer Interface Research – A Summary of the BCI Award 2012 and BCI Research Trends." In Brain-Computer Interface Research. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54707-2_11.

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Allison, Brendan Z., and Christa Neuper. "Could Anyone Use a BCI?" In Brain-Computer Interfaces. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-272-8_3.

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Mellinger, Jürgen, and Gerwin Schalk. "Using BCI2000 in BCI Research." In Brain-Computer Interfaces. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02091-9_15.

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Neuper, Christa, and Gert Pfurtscheller. "Neurofeedback Training for BCI Control." In Brain-Computer Interfaces. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02091-9_4.

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Conference papers on the topic "BCI - Brain Computer Interface"

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Park, Ji-Ha, Seo-Hyun Lee, Soowon Kim, and Seong-Whan Lee. "Dynamic Neural Communication: Convergence of Computer Vision and Brain-Computer Interface." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931467.

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Ko, Byung-Kwan, Jun-Young Kim, and Seo-Hyun Lee. "Imagined Speech State Classification for Robust Brain-Computer Interface." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931499.

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Lee, Byeong-Hoo, and Kang Yin. "Towards a Network Expansion Approach for Reliable Brain-Computer Interface." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931572.

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Salah, Nada O., Mohamed W. Moufaddal, Pakinam Y. Zakaria, Ahmed Allam, and Sameh Sherif. "EEG-Based Brain-Computer Interface (BCI) Controlled Robotic Arm." In 2024 12th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC). IEEE, 2024. https://doi.org/10.1109/jac-ecc64419.2024.11061232.

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Jeong, Seungwoo, Jaehyun Jeon, and Heung-Il Suk. "Energy-Guided Topology Mamba for EEG-Based BCI." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931412.

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Kwak, Heon-Gyu, Gi-Hwan Shin, Yeon-Woo Choi, et al. "Towards Personalized Brain-Computer Interface Application Based on Endogenous EEG Paradigms." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931473.

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Lee, Seo-Hyun, Ji-Ha Park, and Deok-Seon Kim. "Imagined Speech and Visual Imagery as Intuitive Paradigms for Brain-Computer Interfaces." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931355.

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Lee, Hyung-Tak, and Han-Jeong Hwang. "A Novel Channel Selection Method for Near-Infrared Spectroscopy-based Brain-Computer Interfaces." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931551.

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Choi, Yunseok. "Designing an Architecture for a Brain-Computer Interface Operating System: Addressing Neural Input Complexity." In 2025 13th International Conference on Brain-Computer Interface (BCI). IEEE, 2025. https://doi.org/10.1109/bci65088.2025.10931583.

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Fong, Manson Cheuk-Man, James William Minett, Thierry Blu, and William Shi-Yuan Wang. "Brain--computer interface (BCI)." In the 10th asia pacific conference. ACM Press, 2012. http://dx.doi.org/10.1145/2350046.2350071.

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Reports on the topic "BCI - Brain Computer Interface"

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Potter, Michael, and Lydia Harriss. Brain-computer interfaces. Parliamentary Office of Science and Technology, 2020. http://dx.doi.org/10.58248/pn614.

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Brain-Computer Interfaces (BCIs) measure brain activity and can be used to control digital devices. The focus of BCI development has been on using the technology to allow patients to control assistive equipment such as wheelchairs or prostheses. Beyond medicine they are under development for applications in entertainment, marketing and defence. This POSTnote looks at the underpinning technology, its applications and the associated ethical and regulatory challenges.
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Pasupuleti, Murali Krishna. Next-Generation Extended Reality (XR): A Unified Framework for Integrating AR, VR, and AI-driven Immersive Technologies. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv325.

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Abstract: Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), is evolving into a transformative technology with applications in healthcare, education, industrial training, smart cities, and entertainment. This research presents a unified framework integrating AI-driven XR technologies with computer vision, deep learning, cloud computing, and 5G connectivity to enhance immersion, interactivity, and scalability. AI-powered neural rendering, real-time physics simulation, spatial computing, and gesture recognition enable more realistic and adap
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Moore, Brian E. The Brain Computer Interface Future: Time for a Strategy. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ad1018886.

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Mourino, Josep, Jose del Millan, Febo Cincotti, Silvia Chiappa, and Raimon Jane. Spatial Filtering in the Training Process of a Brain Computer Interface. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada412411.

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Guo, Xiaozhen, and Pan Li. The effect of brain-computer interface on lower limb function in stroke patients:a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2024. http://dx.doi.org/10.37766/inplasy2024.6.0070.

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Cutter, Patrick A. The Shape of Things to Come: The Military Benefits of the Brain-Computer Interface in 2040. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ad1012768.

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Patil, Sauvit, and Siddharth Shahi. From Research to Rehabilitation: A Systematic Review of Brain-Computer Interface Feasibility and Functional Outcomes in Health. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2024. http://dx.doi.org/10.37766/inplasy2024.6.0111.

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Wan, Chunli, Huaide Qiu, Xue Wang, et al. Effect of brain computer interface rehabilitation training on functional rehabilitation of stroke patients: A protocol for meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.7.0067.

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Han, Shiyu, Yi Xie, and Anqin Dong. Functional electrical stimulation based on brain-computer interface improves upper limb function in post-stroke patients: a meta-analysis of randomized controlled trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2023. http://dx.doi.org/10.37766/inplasy2023.8.0057.

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Gong, Zhijia, Jiao He, and Li Zhang. Application of Brain-Computer Interface-Based Functional Electrical Stimulation, Transcranial Direct Current Stimulation and Motor Rehabilitation in Upper Limb Rehabilitation of Stroke Survivors: A Systematic Review and Network Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2025. https://doi.org/10.37766/inplasy2025.5.0066.

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