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Relevant bibliographies by topics / Computer interfaces

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Academic literature on the topic 'Computer interfaces'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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Journal articles on the topic "Computer interfaces"

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Pepperberg, Irene M. "Animal-computer interfaces." Interaction Studies 24, no. 2 (November 3, 2023): 193–200. http://dx.doi.org/10.1075/is.23018.pep.

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Abstract The field of animal-computer interfaces has a longer history than one might at first suppose. In this Introduction, I first discuss some of the early attempts to integrate computers into the study of animal cognition, communication, and behavior and how they provided the groundwork for subsequent research in nonhuman-computer interfaces. I then summarize the various contributions to this special issue, emphasizing how they provide a snapshot into the current state of the field. I close by emphasizing the value of this work but also by suggesting some potential pitfalls of which we must also be aware.

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Allan, K. "Inspiring interfaces [computer game interfaces]." Engineering & Technology 2, no. 5 (May 1, 2007): 34–36. http://dx.doi.org/10.1049/et:20070503.

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Bartz, Christina. "Der Computer in der Küche." Zeitschrift für Medien- und Kulturforschung 9, no. 2 (2018): 13–26. http://dx.doi.org/10.28937/1000108172.

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Der Honeywell Kitchen Computer von 1969 ist einer der ersten Rechner, der für den Heimgebrauch hergestellt wurde. Schon allein aufgrund seines wenig benutzerfreundlichen Interfaces, das im Widerspruch zur nicht-professionellen Nutzung in der häuslichen Sphäre steht, stellt er eine Kuriosität dar. Zugleich weist er Aspekte auf, die die Idee eines Computers zu Hause plausibilisieren. Dazu gehört u.a. die Gestaltung des Interfaces, aber auch die Küche als Ort der heimischen Arbeit. In 1969, the Honeywell Kitchen Computer was the first data processor that was built explicitly for home use. Resembling something of an oddity, most of all because of its non-user-friendly interface that conflicts with the conditions of non-professional domestic use, the Honeywell Kitchen Computer at the same time shows some aspects which make the use of a computer at home plausible, i. a. the design of the interface and the factor of a kitchen being the place of domestic work

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Bogdanova, Nellija. "PRINCIPLES OF USER-CENTERED DESIGN." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 20, 2001): 245. http://dx.doi.org/10.17770/etr2001vol1.1921.

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Good user interfaces are essential for any successful product. A process of the user interface creation is not available include in the algorithmic scheme. In this articles will formulate principles principles o f user-centered design, criteria o f ergonomics interfaces and efficient interface’s rules of project. These principles are based usability computer training courses.

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Li, Jiayi. "Brain-computer interface for the treatment of mental illness." Theoretical and Natural Science 16, no. 1 (December 4, 2023): 93–96. http://dx.doi.org/10.54254/2753-8818/16/20240539.

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A brain-computer interface is a direct communication channel between the brain and external devices. Its signals come from the central nervous system, and its transmission is independent of the peripheral nervous and muscular systems. Brain-computer interface commonly used to assist, enhance, and repair human-motor sensations. Through the classification and recognition of Electroencephalogram (EEG) signals, the monitoring and rehabilitation of some neurological and psychological diseases can be realized. Brain-computer interfaces are currently in their infancy and are being explored. Non-invasive brain-computer interfaces refer to brain-computer interfaces that are performed in the cerebral cortex. Semi-invasive brain-computer interfaces are what the chip penetrates the cerebral cortex but does not penetrate the gray matter in the brain. An immersive brain-computer interface is when the chip penetrates the gray matter of the brain. At present, Brain-computer interfaces with chips implanted in the head are mainly located in the brain. Brain-computer interfaces located in the cerebellum, brainstem and other parts have not made significant breakthroughs. The brain-computer interface first collects signals transmitted by the brain, then sequences and encodes them . Finally, transfer them to the computer. The computer controls the robotic arm through the acquired signals and finally completes the instructions. This article focuses on invasive and semi-invasive brain-computer interfaces, using case studies, combinatorial studies, and other methods. This research can help patients live better, improve patients' quality of life, and promote future research in bioelectronics and organic electronics.

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Peters, Gabriele. "Criteria for the Creation of Aesthetic Images for Human-Computer Interfaces A Survey for Computer Scientists." International Journal of Creative Interfaces and Computer Graphics 2, no. 1 (January 2011): 68–98. http://dx.doi.org/10.4018/jcicg.2011010105.

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Interaction in modern human-computer interfaces is most intuitively initiated in an image-based way. Often images are the key components of an interface. However, too frequently, interfaces are still designed by computer scientists with no explicit education in the aesthetic design of interfaces and images. This article develops a well-defined system of criteria for the aesthetic design of images, motivated by principles of visual information processing by the human brain and by considerations of the visual arts. This theoretic disquisition establishes a framework for the evaluation of images in terms of aesthetics and it serves as a guideline for interface designers by giving them a collection of criteria at hand; how to deal with images in terms of aesthetics for the purpose of developing better user interfaces. The proposed criteria are exemplified by an analysis of the images of the web interfaces of four well known museums.

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Williams, Evelyn, and Evelyn Hewlett-Packard. "Panel on Visual Interface Design." Proceedings of the Human Factors Society Annual Meeting 33, no. 5 (October 1989): 323–24. http://dx.doi.org/10.1177/154193128903300519.

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User interface design has many components. Usable computer interfaces should be easy to learn, result in high user productivity and high user satisfaction. There are a number of components in user interface design that affect the usability of the interface. Within the human factors community we tend to emphasize the ergonomic and cognitive components of the computer interface. There is another component that is frequently ignored, the visual interface design. This panel will present information on the visual component in various user-computer interfaces and will discuss the contributions of the visual designer to the interfaces and usability.

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Young, Michael J., David J. Lin, and Leigh R. Hochberg. "Brain–Computer Interfaces in Neurorecovery and Neurorehabilitation." Seminars in Neurology 41, no. 02 (March 19, 2021): 206–16. http://dx.doi.org/10.1055/s-0041-1725137.

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AbstractRecent advances in brain–computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily living and personal goals. Here we evaluate the principles, benefits, challenges, and future directions of brain–computer interfaces in the context of neurorehabilitation. We then explore the clinical translation of these technologies and propose an approach to facilitate implementation of brain–computer interfaces for persons with neurologic disease.

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Gao, Xiaorong, Yijun Wang, Xiaogang Chen, and Shangkai Gao. "Interface, interaction, and intelligence in generalized brain–computer interfaces." Trends in Cognitive Sciences 25, no. 8 (August 2021): 671–84. http://dx.doi.org/10.1016/j.tics.2021.04.003.

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Chao, Dennis L. "Computer games as interfaces." Interactions 11, no. 5 (September 2004): 71–72. http://dx.doi.org/10.1145/1015530.1015567.

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Dissertations / Theses on the topic "Computer interfaces"

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Ward, David James. "Adaptive computer interfaces." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620273.

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Rihan, Jonathan. "Computer vision based interfaces for computer games." Thesis, Oxford Brookes University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.579554.

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Interacting with a computer game using only a simple web camera has seen a great deal of success in the computer games industry, as demonstrated by the numerous computer vision based games available for the Sony PlayStation 2 and PlayStation 3 game consoles. Computational efficiency is important for these human computer inter- action applications, so for simple interactions a fast background subtraction approach is used that incorporates a new local descriptor which uses a novel temporal coding scheme that is much more robust to noise than the standard formulations. Results are presented that demonstrate the effect of using this method for code label stability. Detecting local image changes is sufficient for basic interactions, but exploiting high-level information about the player's actions, such as detecting the location of the player's head, the player's body, or ideally the player's pose, could be used as a cue to provide more complex interactions. Following an object detection approach to this problem, a combined detection and segmentation approach is explored that uses a face detection algorithm to initialise simple shape priors to demonstrate that good real-time performance can be achieved for face texture segmentation. Ultimately, knowing the player's pose solves many of the problems encountered by simple local image feature based methods, but is a difficult and non-trivial problem. A detection approach is also taken to pose estimation: first as a binary class problem for human detection, and then as a multi-class problem for combined localisation and pose detection. For human detection, a novel formulation of the standard chamfer matching algo- rithm as an SVM classifier is proposed that allows shape template weights to be learnt automatically. This allows templates to be learnt directly from training data even in the presence of background and without the need to pre-process the images to extract their silhouettes. Good results are achieved when compared to a state of the art human detection classifier. For combined pose detection and localisation, a novel and scalable method of ex- ploiting the edge distribution in aligned training images is presented to select the most potentially discriminative locations for local descriptors that allows a much higher space of descriptor configurations to be utilised efficiently. Results are presented that show competitive performance when compared to other combined localisation and pose detection methods.

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Hawthorn, Dan. "Designing Effective Interfaces for Older Users." The University of Waikato, 2006. http://hdl.handle.net/10289/2538.

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The thesis examines the factors that need to be considered in order to undertake successful design of user interfaces for older users. The literature on aging is surveyed for age related changes that are of relevance to interface design. The findings from the literature review are extended and placed in a human context using observational studies of older people and their supporters as these older people attempted to learn about and use computers. These findings are then applied in three case studies of interface design and product development for older users. These case studies are reported and examined in depth. For each case study results are presented on the acceptance of the final product by older people. These results show that, for each case study, the interfaces used led to products that the older people evaluating them rated as unusually suitable to their needs as older users. The relationship between the case studies and the overall research aims is then examined in a discussion of the research methodology. In the case studies there is an evolving approach used in developing the interface designs. This approach includes intensive contribution by older people to the shaping of the interface design. This approach is analyzed and is presented as an approach to designing user interfaces for older people. It was found that a number of non-standard techniques were useful in order to maximize the benefit from the involvement of the older contributors and to ensure their ethical treatment. These techniques and the rationale behind them are described. Finally the interface design approach that emerged has strong links to the approach used by the UTOPIA team based at the university of Dundee. The extent to which the thesis provides support for the UTOPIA approach is discussed.

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Halder, Sebastian [Verfasser]. "Prediction of Brain-Computer Interface Performance: For P300 and Motor Imagery Brain-Computer Interfaces / Sebastian Halder." München : Verlag Dr. Hut, 2011. http://d-nb.info/1015607330/34.

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Hobro, Mark, and Marcus Heine. "Natural Language Interfaces in Computer Games." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166592.

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Natural language processing is a complex area of computer science whichhas been under discussion for more than forty years. During recent yearsnatural language interfaces have been established in conjunction withspeech recognition. This report will cover the theory behind naturallanguage processing and evaluate the weaknesses and strengths of implementingand using a natural language interface in a text-based gameenvironment using the Natural Language Toolkit for Python. The resultsshow that the Natural Language Toolkit has great potential forimplementing a natural language interface for a text-based game, butthe library alone is not sufficient to get good results when the scope oflanguage is increased.

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Zajicek, Mary Pamela. "The usability of alternative computer interfaces." Thesis, Oxford Brookes University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251356.

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Wong, Shu-Fai. "Motion recognition for human-computer interfaces." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613368.

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Yeung, C. "Spectroscopic analysis of nanodielectric interfaces." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/358897/.

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Polymeric nanocomposites have received an exceptional amount of attention over the recent years as they have the ability to possess enhanced properties. The use of nanosized phases in composite materials, as opposed to their microsized counterpart, delivers characteristics which allow nanodielectric systems to operate at an increased performance and improved efficiency. The requirements of the polymeric system can easily be tailored to suit speci�c applications with as little as 2 wt.% filler loading, whilst maintaining the typical weight of the virgin material. With the transition from micrometric to nanomeric phases, the volume of the interfacial region increases dramatically and this is where the mechanisms behind nanocomposite behaviour are believed to occur. As the potential for nanodielectrics is endless, the importance of in-depth studies into the �ller-matrix interface is fundamental. Many studies have already partaken in research which uses organosilanes as a coupling agent, however few the quantity of organosilane as a variable parameter, or compared the use of hydrous and anhydrous functionalisation methods. This study investigates the consequences of introducing differently functionalised nanosilicas into epoxy systems; a number of spectroscopic techniques (Raman spectroscopy, Fourier transform infrared spectroscopy and combustion analysis) were employed to quantify the level of surface modification on the surface of silica nanoparticles, before mixing methods were developed in an attempt to reach nanoparticle homogeneity in an epoxy matrix. Scanning electron microscopy was employed to investigate the dispersion state of the filler with respect to the degree of functionalisation, whilst data from AC breakdown studies, differential scanning calorimetry and dielectric spectroscopy were analysed to determine the effects of differently functionalised nanosilica in a dielectric system. Theinvestigation shows how condensation reactions within the interphase has an infuence dielectric behaviour, and highlights how changes in the stoichiometry of the epoxy system alters the polymerarchitecture to have an effect on the electrical properties of the nanocomposites. Further studies explore the use of confocal Raman spectroscopy as a tool in probing the nanofiller-matrix interface. A simulation based on the scattering of incident photons was compared with empirical data from a range of dielectric �lms; modi�cations to the scattering photon approach relates physically obtained values for bulk attenuation directly to those observed in confocal Raman depth profiles. Although it was found that the revised model was able to produce confocal Raman depth profiles that closely match experimental data from the nanocomposite films, the nature of nanoparticle agglomeration during functionalisation and the typical resolution of confocal Raman systems do not allow for the detection of chemical changes on the filler.

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Mynatt, Elizabeth D. "Transforming graphical interfaces into auditory interfaces." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/9209.

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Sebastián, Romagosa Marc. "Brain computer interfaces for brain acquired damage." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/670835.

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El terme Interfície Cervell-Ordinador (ICC), va sorgir als anys 70 pel Dr. Jacques J. Vidal, que mitjançant l’ús de l’electroencefalografia (EEG) fou el primer a intentar proporcionar una sortida alternativa als senyals cerebrals per controlar un dispositiu extern. L’objectiu principal d’aquesta fita era ajudar als pacients amb problemes de moviment i comunicació a relacionar-se amb el seu entorn. Des de llavors, molts neurocientífics han emprat aquesta idea i han intentat posar-la en pràctica utilitzant diferents mètodes d’adquisició i processament del senyal, nous dispositius d’interacció, noves metes i objectius. Tot això ha facilitat l’aplicació d’aquesta tecnologia en moltes àrees, i actualment les ICC s’utilitzen per jugar a videojocs, moure cadires de rodes, facilitar l’escriptura en persones sense mobilitat, definir criteris i preferències en el món del comerç i el consum, o inclús poden servir com a detector de mentides. Tot i així, el sector que presenta un major avenç en el desenvolupament de les ICC, és el sector biomèdic. A grans trets, podem utilitzar les ICC amb dues finalitats diferents dins de la neurorehabilitació; substituint una funció perduda o induint canvis en la plasticitat neuronal amb l’objectiu de restaurar o compensar la funció perduda. Existeixen diferents principis per al registre dels senyals del cervell; de manera invasiva, col·locant els elèctrodes de registre dintre de la cavitat cranial, o de manera no invasiva, col·locant els elèctrodes de registre fora de la cavitat cranial. El mètode més conegut i difós és l’EEG. El seu ús és molt adequat en entorns clínics, té una resolució temporal molt precisa i és possible obtenir una retroalimentació en temps real que pot induir la plasticitat cortical i el restabliment de la funció motora normal. En aquesta tesi presentem tres objectius diferents: (1) avaluar els afectes clínics de la rehabilitació mitjançant les ICC en pacients amb ictus, ja sigui realitzant un meta-anàlisi dels estudis publicats o avaluant els canvis funcionals dels pacients amb ictus després de la teràpia d’ICC; (2) explorar paràmetres alternatius per quantificar els efectes de les ICC en pacients amb ictus, avaluant diferents biomarcadors de l’EEG en pacients amb aquesta patologia i correlacionant aquests marcadors amb els resultats de les escales funcionals; (3) optimitzar el sistema ICC mitjançant la gamificació d’un avatar.
El término Interfaz Cerebro-Computadora (ICC) surgió en los años 70 por el Dr. Jacques J. Vidal, que mediante el uso de la electroencefalografía (EEG) trató de dar una salida alternativa a las señales del cerebro para controlar un dispositivo externo. El objetivo principal de esta hazaña era ayudar a los pacientes con problemas de movimiento o comunicación a relacionarse con el entorno. Desde entonces, muchos neurocientíficos han utilizado esta idea y han tratado de ponerla en práctica utilizando diferentes métodos de adquisición y procesamiento de señales, nuevos dispositivos de interacción y nuevas metas y objetivos. Todo ello ha facilitado la aplicación de esta tecnología en muchas áreas y actualmente las ICC se utilizan para jugar a videojuegos, mover sillas de ruedas, facilitar la escritura en personas sin movilidad, establecer criterios y preferencias de compra en el mundo del comercio y el consumo, o incluso pueden servir como detector de mentiras. Sin embargo, el sector que presenta un mayor avance y desarrollo de las ICC es el sector biomédico. A grandes rasgos podemos utilizar las ICC con dos finalidades distintas dentro de la neurorehabilitación; sustituir una función perdida o inducir cambios en la plasticidad neuronal con el objetivo de restaurar o compensar dicha función perdida. Hay diferentes principios para el registro de las señales del cerebro; de forma invasiva, colocando los electrodos de registro dentro de la cavidad craneal, o no invasiva, colocando los electrodos de registro fuera de la cavidad craneal. El método más conocido y difundido es la EEG. Su uso es adecuado para entornos clínicos, tiene una resolución temporal muy precisa y su retroalimentación en tiempo real puede inducir la plasticidad cortical y el restablecimiento de la función motora normal. En esta tesis presentamos tres objetivos diferentes: (1) evaluar los efectos clínicos de la rehabilitación mediante las ICC en pacientes con ictus, ya sea realizando un meta-análisis de los estudios publicados o evaluando los cambios funcionales en los pacientes con ictus después de la terapia de ICC; (2) explorar parámetros alternativos para cuantificar los efectos de las ICC en pacientes con ictus, evaluando diferentes biomarcadores de electroencefalografía en pacientes con esta patología y correlacionando los posibles cambios en estos parámetros con los resultados en las escalas funcionales; (3) optimizar el sistema ICC utilizando mediante la gamificación de un avatar.
The term Brain Computer Interface (BCI) emerged in the 70's by Dr. Jacques J Vidal, who by using electroencephalography (EEG) tried to give an alternative output to the brain signals in order to control an external device. The main objective of this feat was to help patients with impaired movement or communication to relate themselves to the environment. Since then many neuroscientists have used this idea and have tried to implement it using different methods of signal acquisition and processing, new interaction devices, new goals and objectives. All this has facilitated the implementation of this technology in many areas and currently BCI is used to play video games, move wheelchairs, facilitate writing in people without mobility, establish criteria and purchase preferences in the world of marketing and consumption, or even serve as a lie detector. However, the sector that presents the most marked progress and development of BCI is the biomedical sector. In rough outlines we can use BCI with two different purposes within the neurorehabilitation; to substitute a lost function or to induce neural plasticity changes with the aim to restore or compensate the lost function. To restore a lost function by inducing neuroplastic changes in the brain is undoubtedly a challenging strategy but a feasible goal through BCI technology. This type of intervention requires that the patient invests time and effort in a therapy based on the practice of motor image and feedback mechanisms in real time. There are different principles to record the brain signals; invasively, placing the recording electrodes inside the cranial cavity, or non-invasive, placing the recording electrodes outside of the cranial cavity. The best known and most widespread one is EEG, since they are suitable for clinical environments, have a highly accurate temporal resolution and their real-time feedback can induce cortical plasticity and the restoration of normal motor function. On this thesis we present three different objectives: (1) to evaluate the clinical effects of rehabilitation based on BCI system in stroke patients, either by performing a meta-analysis of published studies or by evaluating functional changes in stroke patients after BCI training; (2) to explore alternative parameters to quantify effects of BCI in stroke patients, by evaluating different electroencephalography biomarkers in stroke patients and correlating potential changes in these parameters with functional scales; (3) to optimize the BCI system by using a new gamified avatar.

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Books on the topic "Computer interfaces"

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Marquez-Chin, Cesar, Naaz Kapadia-Desai, and Sukhvinder Kalsi-Ryan. Brain–Computer Interfaces. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-01608-0.

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Hassanien, Aboul Ella, and Ahmad Taher Azar, eds. Brain-Computer Interfaces. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10978-7.

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Graimann, Bernhard, Gert Pfurtscheller, and Brendan Allison, eds. Brain-Computer Interfaces. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-02091-9.

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Tan, Desney S., and Anton Nijholt, eds. Brain-Computer Interfaces. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-272-8.

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Berger, Theodore W., John K. Chapin, Greg A. Gerhardt, Dennis J. McFarland, José C. Principe, Walid V. Soussou, Dawn M. Taylor, and Patrick A. Tresco. Brain-Computer Interfaces. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8705-9.

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Hordeski, Michael F. Personal computer interfaces. Maidenhead: McGraw-Hill, 1995.

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I, Vlaeminke, ed. Man-computer interfaces. Oxford: Blackwell Scientific, 1987.

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Nam, Chang S., Anton Nijholt, and Fabien Lotte, eds. Brain–Computer Interfaces Handbook. Boca Raton : Taylor & Francis, CRC Press, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9781351231954.

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Clerc, Maureen, Laurent Bougrain, and Fabien Lotte, eds. Brain-Computer Interfaces 1. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119144977.

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Clerc, Maureen, Laurent Bougrain, and Fabien Lotte, eds. Brain-Computer Interfaces 2. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119332428.

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Book chapters on the topic "Computer interfaces"

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Tan, Desney, and Anton Nijholt. "Brain-Computer Interfaces and Human-Computer Interaction." In Brain-Computer Interfaces, 3–19. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-272-8_1.

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Marquez-Chin, Cesar, Naaz Kapadia-Desai, and Sukhvinder Kalsi-Ryan. "Brain–Computer Interfaces." In Brain–Computer Interfaces, 51–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-01608-0_4.

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Brandman, David M., and Leigh R. Hochberg. "Brain Computer Interfaces." In Neurobionics: The Biomedical Engineering of Neural Prostheses, 231–63. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118816028.ch9.

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Schalk, Gerwin, and Jürgen Mellinger. "Brain–Computer Interfaces." In A Practical Guide to Brain–Computer Interfacing with BCI2000, 3–8. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-092-2_1.

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Sutcliffe, Alistair. "Computer Control Interfaces." In Human-Computer Interface Design, 156–80. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4899-6749-7_9.

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Holmes, Nate. "Camera Computer Interfaces." In Handbook of Machine and Computer Vision, 431–503. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2017. http://dx.doi.org/10.1002/9783527413409.ch8.

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Curio, Gabriel. "Brain-Computer Interfaces." In Bildverarbeitung für die Medizin 2012, 2. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28502-8_2.

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Millán, José del R. "Brain-Computer Interfaces." In Introduction to Neural Engineering for Motor Rehabilitation, 237–52. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118628522.ch12.

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Sibilano, Elena, Vladimiro Suglia, Antonio Brunetti, Domenico Buongiorno, Nicholas Caporusso, Christoph Guger, and Vitoantonio Bevilacqua. "Brain–Computer Interfaces." In Neuromethods, 203–40. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3545-2_10.

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He, Bin, Han Yuan, Jianjun Meng, and Shangkai Gao. "Brain–Computer Interfaces." In Neural Engineering, 131–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43395-6_4.

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Conference papers on the topic "Computer interfaces"

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Wolpaw, Jonathan R. "Brain-computer interfaces." In the 2nd ACM SIGHIT symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2110363.2110366.

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Jantz, Jay, Adam Molnar, and Ramses Alcaide. "A brain-computer interface for extended reality interfaces." In SIGGRAPH '17: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3089269.3089290.

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Rekimoto, Jun. "Multiple-computer user interfaces." In CHI '00 extended abstracts. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/633292.633297.

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Molina, Gary Garcia, Tsvetomira Tsoneva, and Anton Nijholt. "Emotional brain-computer interfaces." In 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops (ACII 2009). IEEE, 2009. http://dx.doi.org/10.1109/acii.2009.5349478.

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Hincks, Samuel, Sarah Bratt, Sujit Poudel, Vir V. Phoha, Robert J. K. Jacob, Daniel C. Dennett, and Leanne Hirshfield. "Entropic Brain-computer Interfaces." In 4th International Conference on Physiological Computing Systems. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006383300230034.

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Beckhaus, Steffi, and Ernst Kruijff. "Unconventional human computer interfaces." In the conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1103900.1103918.

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Igarashi, Takeo. "Sketching interfaces for computer graphics." In ACM SIGGRAPH ASIA 2009 Courses. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1665817.1665833.

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Lotte, Fabien, Junya Fujisawa, Hideaki Touyama, Rika Ito, Michitaka Hirose, and Anatole Lécuyer. "Towards ambulatory brain-computer interfaces." In the International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1690388.1690452.

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McCullagh, P. J., M. P. Ware, and G. Lightbody. "Brain Computer Interfaces for inclusion." In AH '10: 2010 Augmented Human International Conference. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/1785455.1785461.

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Grynszpan, Ouriel, Jean-Claude Martin, and Jacqueline Nadel. "Human computer interfaces for autism." In CHI '05 extended abstracts. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1056808.1056931.

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Reports on the topic "Computer interfaces"

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Norcio, A. F., and J. Stanley. Adaptive Human-Computer Interfaces. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada200930.

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Tolmie, D. E., W. St. John, and D. H. DuBois. Super-speed computer interfaces and networks. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/534509.

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Terranova, M. Team-computer interfaces in complex task environments. Office of Scientific and Technical Information (OSTI), September 1990. http://dx.doi.org/10.2172/6427485.

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Kirchstetter, Thomas. Brain-computer interfaces enabled by novel magnetometers. Office of Scientific and Technical Information (OSTI), December 2020. http://dx.doi.org/10.2172/1755426.

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Schmidt, Nick. Control of Physical Objects Utilizing Brain Computer Interfaces. Ames (Iowa): Iowa State University, January 2020. http://dx.doi.org/10.31274/cc-20240624-423.

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Myers, Brad A. Why are Human-Computer Interfaces Difficult to Design and Implement. Fort Belvoir, VA: Defense Technical Information Center, July 1993. http://dx.doi.org/10.21236/ada268843.

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Enright, Doug, and Ron Fedkiw. Robust Treatment of Interfaces for Fluid Flows and Computer Graphics. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada479018.

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Jyothi, Yadav. Neural implants: A meta analysis on the efficacy and the possibilities of brain-computer interfaces. Ames (Iowa): Iowa State University, May 2022. http://dx.doi.org/10.31274/cc-20240624-1048.

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Franza, Bernard R. Combining Broadband Connectivity and Immersive Human-to-Computer Interfaces to Improve Medical Simulation Training and Patient Care. Fort Belvoir, VA: Defense Technical Information Center, November 2010. http://dx.doi.org/10.21236/ada543828.

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Hannas, William, Huey-Meei Chang, Daniel Chou, and Brian Fleeger. China's Advanced AI Research: Monitoring China's Paths to "General" Artificial Intelligence. Center for Security and Emerging Technology, July 2022. http://dx.doi.org/10.51593/20210064.

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Abstract:

China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

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