Relevant bibliographies by topics / Brain interfacing

Contents

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

Academic literature on the topic 'Brain interfacing'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Brain interfacing"

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Lee, Sungjun, Kyuha Park, Jeungeun Kum, et al. "Stretchable Surface Electrode Arrays Using an Alginate/PEDOT:PSS-Based Conductive Hydrogel for Conformal Brain Interfacing." Polymers 15, no. 1 (2022): 84. http://dx.doi.org/10.3390/polym15010084.

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An electrocorticogram (ECoG) is the electrical activity obtainable from the cerebral cortex and an informative source with considerable potential for future advanced applications in various brain-interfacing technologies. Considerable effort has been devoted to developing biocompatible, conformal, soft, and conductive interfacial materials for bridging devices and brain tissue; however, the implementation of brain-adaptive materials with optimized electrical and mechanical characteristics remains challenging. Herein, we present surface electrode arrays using the soft tough ionic conductive hyd
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Jellinger, K. A. "Toward Brain-Computer Interfacing." European Journal of Neurology 16, no. 3 (2009): e52-e52. http://dx.doi.org/10.1111/j.1468-1331.2008.02463.x.

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Singh, Satya P., Sachin Mishra, Sukrit Gupta, et al. "Functional Mapping of the Brain for Brain–Computer Interfacing: A Review." Electronics 12, no. 3 (2023): 604. http://dx.doi.org/10.3390/electronics12030604.

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Brain–computer interfacing has been applied in a range of domains including rehabilitation, neuro-prosthetics, and neurofeedback. Neuroimaging techniques provide insight into the structural and functional aspects of the brain. There is a need to identify, map and understand the various structural areas of the brain together with their functionally active roles for the accurate and efficient design of a brain–computer interface. In this review, the functionally active areas of the brain are reviewed by analyzing the research available in the literature on brain–computer interfacing in conjuncti
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Jackson, A., and E. E. Fetz. "Interfacing With the Computational Brain." IEEE Transactions on Neural Systems and Rehabilitation Engineering 19, no. 5 (2011): 534–41. http://dx.doi.org/10.1109/tnsre.2011.2158586.

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Daly, Ian, Duncan Williams, Alexis Kirke, et al. "Affective brain–computer music interfacing." Journal of Neural Engineering 13, no. 4 (2016): 046022. http://dx.doi.org/10.1088/1741-2560/13/4/046022.

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Xia, Kaijian, Yizhang Jiang, Yudong Zhang, and Wen Si. "Guest Editorial: Advanced Machine-Learning Methods for Brain-Machine Interfacing or Brain-Computer Interfacing." IEEE/ACM Transactions on Computational Biology and Bioinformatics 18, no. 5 (2021): 1643–44. http://dx.doi.org/10.1109/tcbb.2021.3078145.

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Min, Byoung-Kyong, and Klaus-Robert Müller. "Electroencephalography/sonication-mediated human brain–brain interfacing technology." Trends in Biotechnology 32, no. 7 (2014): 345–46. http://dx.doi.org/10.1016/j.tibtech.2014.04.001.

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Valencia, Daniel, Jameson Thies, and Amirhossein Alimohammad. "Frameworks for Efficient Brain-Computer Interfacing." IEEE Transactions on Biomedical Circuits and Systems 13, no. 6 (2019): 1714–22. http://dx.doi.org/10.1109/tbcas.2019.2947130.

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Bryan, Matthew J., Stefan A. Martin, Willy Cheung, and Rajesh P. N. Rao. "Probabilistic co-adaptive brain–computer interfacing." Journal of Neural Engineering 10, no. 6 (2013): 066008. http://dx.doi.org/10.1088/1741-2560/10/6/066008.

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Sunny, T. D., T. Aparna, P. Neethu, J. Venkateswaran, V. Vishnupriya, and P. S. Vyas. "Robotic Arm with Brain – Computer Interfacing." Procedia Technology 24 (2016): 1089–96. http://dx.doi.org/10.1016/j.protcy.2016.05.241.

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Dissertations / Theses on the topic "Brain interfacing"

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Kaper, Matthias. "P300 based brain computer interfacing." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=979538203.

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Daly, Ian. "Phase synchronisation in brain computer interfacing." Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553633.

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Brain Computer Interfaces (BCls) are an emerging area of research combining the Neuroscience, Computer Science, Engineering, Mathematics, Human Computer Interaction and Psychology research fields. A BCI enables an individual to exert control of a computer without activation of the efferent nervous system or the muscles. This allows individuals suffering with partial or complete paralysis and associated conditions which prevent muscle movement to control a computer and hence communicate and exert control over their environment. This thesis first investigates tools for automatically removing art
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Shoker, Leor. "Signal processing algorithms for brain computer interfacing." Thesis, Cardiff University, 2006. http://orca.cf.ac.uk/56097/.

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A brain computer interface (BCI) allows the user to communicate with a computer using only brain signals. In this way, the conventional neural pathways of peripheral nerves and muscles are bypassed, thereby enabling control of a computer by a person with no motor control. The brain signals, known as electroencephalographs (EEGs), are recorded by electrodes placed on the surface of the scalp. A requirement for a successful BCI is that interfering artifacts are removed from the EEGs, so that thereby the important cognitive information is revealed. Two systems based on second order blind source s
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Dornhege, Guido. "Increasing information transfer rates for brain-computer interfacing." Phd thesis, [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98051276X.

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Valbuena, Varon Diana Alexandra [Verfasser]. "Practical Brain Computer Interfacing / Diana Alexandra Valbuena Varon." München : Verlag Dr. Hut, 2012. http://d-nb.info/1029399751/34.

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Melano, Timothy. "Insect-Machine Interfacing." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145388.

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A terrestrial robotic electrophysiology platform has been developed that can hold a moth (<italic>Manduca sexta</italic>), record signals from its brain or muscles, and use these signals to control the rotation of the robot. All signal processing (electrophysiology, spike detection, and robotic control) was performed onboard the robot with custom designed electronic circuits. Wireless telemetry allowed remote communication with the robot. In this study, we interfaced directionally-sensitive visual neurons and pleurodorsal steering muscles of the mesothorax with the robot and used the spike rat
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Nazarpour, Kianoush. "Brain signal analysis in space-time-frequency domain : an application to brain computer interfacing." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54718/.

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In this dissertation, advanced methods for electroencephalogram (EEG) signal analysis in the space-time-frequency (STF) domain with applications to eye-blink (EB) artifact removal and brain computer interfacing (BCI) are developed. The two methods for EB artifact removal from EEGs are presented which respectively include the estimated spatial signatures of the EB artifacts into the signal extraction and the robust beamforming frameworks. In the developed signal extraction algorithm, the EB artifacts are extracted as uncorrelated signals from EEGs. The algorithm utilizes the spatial signatures
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Eaton, Joel. "Brain-computer music interfacing : designing practical systems for creative applications." Thesis, University of Plymouth, 2016. http://hdl.handle.net/10026.1/5221.

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Brain-computer music interfacing (BCMI) presents a novel approach to music making, as it requires only the brainwaves of a user to control musical parameters. This presents immediate benefits for users with motor disabilities that may otherwise prevent them from engaging in traditional musical activities such as composition, performance or collaboration with other musicians. BCMI systems with active control, where a user can make cognitive choices that are detected within brain signals, provide a platform for developing new approaches towards accomplishing these activities. BCMI systems that u
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Spüler, Martin [Verfasser]. "Assessing the Benefit of Adaptive Brain-Computer Interfacing / Martin Spüler." München : Verlag Dr. Hut, 2013. http://d-nb.info/1037287002/34.

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Wang, Suogang. "Enhancing brain-computer interfacing through advanced independent component analysis techniques." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/65897/.

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A brain-computer interface (BCI) is a direct communication system between a brain and an external device in which messages or commands sent by an individual do not pass through the brain’s normal output pathways but is detected through brain signals. Some severe motor impairments, such as Amyothrophic Lateral Sclerosis, head trauma, spinal injuries and other diseases may cause the patients to lose their muscle control and become unable to communicate with the outside environment. Currently no effective cure or treatment has yet been found for these diseases. Therefore using a BCI system to reb
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Books on the topic "Brain interfacing"

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Miranda, Eduardo Reck, and Julien Castet, eds. Guide to Brain-Computer Music Interfacing. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6584-2.

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Schalk, Gerwin, and Jürgen Mellinger. A Practical Guide to Brain–Computer Interfacing with BCI2000. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-092-2.

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Coates, Thomas D. Neural interfacing: Forging the human-machine connection. Morgan & Claypool Publishers, 2008.

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Schalk, Gerwin. A practical guide to brain-computer interfacing with BCI2000: General-purpose software for brain-computer interface research, data acquisition, stimulus presentation, and brain monitoring. Springer, 2010.

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Dornhege, Guido, José del R. Millán, Thilo Hinterberger, Dennis J. McFarland, and Klaus-Robert Müller, eds. Toward Brain-Computer Interfacing. The MIT Press, 2007. http://dx.doi.org/10.7551/mitpress/7493.001.0001.

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Toward brain-computer interfacing. MIT Press, 2007.

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Toward brain-computer interfacing. MIT Press, 2008.

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Mcfarland, Dennis J., Jose del R. Millan, Guido Dornhege, Thilo Hinterberger, and Klaus-robert Müller. Toward Brain-Computer Interfacing. MIT Press, 2007.

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Toward Brain-Computer Interfacing. MIT Press, 2019.

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Rao, Rajesh P. N. Brain-Computer Interfacing: An Introduction. Cambridge University Press, 2013.

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Book chapters on the topic "Brain interfacing"

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Sanei, Saeid, and J. A. Chambers. "Brain-Computer Interfacing." In EEG Signal Processing. John Wiley & Sons Ltd,, 2013. http://dx.doi.org/10.1002/9780470511923.ch7.

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Singh, Paras Nath. "Brain–Computer Interfacing." In Machine Learning in Signal Processing. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003107026-6.

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Plass-Oude Bos, Danny, Boris Reuderink, Bram van de Laar, et al. "Brain-Computer Interfacing and Games." In Brain-Computer Interfaces. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-272-8_10.

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Nijholt, Anton. "Competing and Collaborating Brains: Multi-brain Computer Interfacing." In Brain-Computer Interfaces. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10978-7_12.

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Williams, Duncan. "Brain Computer Music Interfacing (BCMI)." In Emotion in Video Game Soundtracking. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72272-6_6.

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George, Laurent, and Anatole Lécuyer. "Passive Brain–Computer Interfaces." In Guide to Brain-Computer Music Interfacing. Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6584-2_13.

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Clausen, Jens. "Ethical Implications of Brain–Computer Interfacing." In Handbook of Neuroethics. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-4707-4_40.

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Schalk, Gerwin. "Sensor Modalities for Brain-Computer Interfacing." In Human-Computer Interaction. Novel Interaction Methods and Techniques. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02577-8_67.

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Friedman, Doron. "Brain-Computer Interfacing and Virtual Reality." In Handbook of Digital Games and Entertainment Technologies. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-4560-50-4_2.

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Friedman, Doron. "Brain-Computer Interfacing and Virtual Reality." In Handbook of Digital Games and Entertainment Technologies. Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-4560-52-8_2-1.

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Conference papers on the topic "Brain interfacing"

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Bale, Ajay Sudhir, Anitha Nair, Nandini R, Yashas, Abdul Khadar, and Monisha M. "Neuronet: Convergence of Brain-Computer Interfacing and Networking Technologies." In 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS). IEEE, 2024. https://doi.org/10.1109/icicnis64247.2024.10823315.

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Van Helleputte, Nick. "Tutorial: Circuits and Technologies for Cell and Brain Interfacing." In 2017 IEEE International Solid- State Circuits Conference - (ISSCC). IEEE, 2017. https://doi.org/10.1109/isscc15680.2017.11005922.

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Lee, Hunjun, Yeongwoo Jang, Daye Jung, Seunghyun Song, and Jangwoo Kim. "Rearchitecting a Neuromorphic Processor for Spike-Driven Brain-Computer Interfacing." In 2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO). IEEE, 2024. https://doi.org/10.1109/micro61859.2024.00082.

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Raja Padmaja, Gokul Krishna, Nikunj Arunkumar Bhagat, and Pragathi Priyadharsini Balasubramani. "Tapping the Differences Between Reward Processes and Executive Control for Efficient Brain-Machine Interfacing (BMI) Recovery in Post-Stroke Patients with Upper Limb Impairments." In 2024 International Conference on Brain Computer Interface & Healthcare Technologies (iCon-BCIHT). IEEE, 2024. https://doi.org/10.1109/icon-bciht63907.2024.10882377.

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Min, Byoung-Kyong. "Eeg/sonication-based brain-brain interfacing." In 2013 International Winter Workshop on Brain-Computer Interface (BCI). IEEE, 2013. http://dx.doi.org/10.1109/iww-bci.2013.6506614.

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Roula, Mohammed Ali, Sriharsha Ramaraju, and Peter McCarthy. "Brain Stimulation and Brain Computer Interfacing." In Proceedings of the 32nd International BCS Human Computer Interaction Conference. BCS Learning & Development, 2018. http://dx.doi.org/10.14236/ewic/hci2018.231.

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Herron, Jeffrey, Scott Stanslaski, Tom Chouinard, Rob Corey, Timothy Denison, and Heather Orser. "Bi-directional brain interfacing instrumentation." In 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC ). IEEE, 2018. http://dx.doi.org/10.1109/i2mtc.2018.8409795.

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Mattia, Donatella, Laura Astolfi, Jlenia Toppi, Manuela Petti, Floriana Pichiorri, and Febo Cincotti. "Interfacing brain and computer in neurorehabilitation." In 2016 4th International Winter Conference on Brain-Computer Interface (BCI). IEEE, 2016. http://dx.doi.org/10.1109/iww-bci.2016.7457446.

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Shoham, Shy. "Photonic Interfacing with Large Scale Natural and Bioengineered Neuronal Networks." In Optics and the Brain. OSA, 2015. http://dx.doi.org/10.1364/brain.2015.brm2b.2.

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Gangadhar, Garipelli, Ricardo Chavarriaga, and Jose del R. Millan. "Anticipation based Brain-Computer Interfacing (aBCI)." In 2009 4th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2009. http://dx.doi.org/10.1109/ner.2009.5109332.

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Reports on the topic "Brain interfacing"

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Lee, Timothy C., and Luke J. Currano. Interfacing a Microelectromechanical System (MEMS) Sensor Array for Traumatic Brain Injury Detection with a Microcontroller. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada569540.

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