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检索条件"主题词=Brain-computer Interface"

共 3602 条记录，以下是71-80 订阅

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brain-computer interface: Generic Control interface for Social Interaction Applications

Brain-Computer Interface: Generic Control Interface for Soci...

引用

11th International Work-Conference on Artificial Neural Networks (IWANN)

作者： Hintermueller, C. Guger, C. Edlinger, G. G Tec Med Engn GmbH Schiedlberg Austria Guger Technol OG Schiedlberg Austria

ISBN: (纸本)9783642215018

After suffering a more severe disease like spinal cord injury or stroke patients are often not able to interact or even communicate with their environment anymore, especially at the beginning of rehabilitation. brain-computer interfaces (BCIs) can substitute this temporarily lost communication channels and might support rehabilitation by providing an alternative way for controlling a computer only by thoughts without any muscle activity. This enables the patient to communicate by writing letters on the screen, to stay socially in contact with friends or people outside the rehabilitation facility by participating in games like Second Life where they may appear as healthy persons. Another application is to control items in their room connected to the BCI system like the lights which can be turned off and on as it can be done in a virtual smart home without leaving the bed. In this paper a generic BCI interface is described which allows to control the aforementioned applications concurrently and transparently switch among them utilizing the P300 approach. The results of a recent study show that such a BCI can be used by patients suffering from cervical spinal cord injury almost as well as by healthy people which encourages us to think it may assist rehabilitation regarding the social aspect.

关键词： brain-computer interface BCI P300 visual evoked potentials speller Second Life Twitter

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brain-computer interface (BCI) based Musical Composition

Brain-Computer Interface (BCI) based Musical Composition

引用

International Conference on Cyberworlds (CW)

作者： Hamadicharef, Brahim Xu, Mufeng Aditya, Sheel Tiara 22-02 1 Kim Seng Walk Singapore 239403 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9780769542157

In this paper we present, for the first time in brain-computer interface (BCI) research, a novel application for music composition. We developed, based on the I 2 R NeuroComm BCI platform, a novel Graphical User interface (GUI) to allow composition of short melodies by selecting individual musical notes. The user can select any individual musical key (quarter note with Do, Re, Mi, Fa, Sol, La, Si, Do, etc.), insert a silence (quarter rest), delete (Del) the last note to correct the composition, or listen (Play) to the final melody, shown in text form and as a musical partition. Our BCI system for music composition has been successfully demonstrated and shown to be, with very short training time, effective and easy to use. This work is the first step towards a more intelligent BCI system that will extend current BCI-based Virtual Reality (VR) navigation for e. g. exploring a Virtual Synthesizer Museum/shop, in which the user would first move around within the virtual museum/shop and at the point of interest would try the synthesizer by composing music. More advanced modes (e. g. musical puzzle) with various levels of difficulty will be added in future developments as well as using the OpenVibe environment and mobile platforms such as the Apple's iPAD.

关键词： brain-computer interface Musical Composition Entertainment Rehabilitation

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brain-computer interface in Chronic Stroke: an Application of Sensorimotor Closed-loop and Contingent Force Feedback

Brain-Computer Interface in Chronic Stroke: an Application o...

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IEEE International Conference on Communications (ICC)

作者： Cisotto, Giulia Pupolin, Silvano Silvoni, Stefano Cavinato, Marianna Agostini, Michela Piccione, Francesco Univ Padua Dept Informat Engn I-35100 Padua Italy IRCCSS Camillo Hosp Fdn Dept Neurophysiol Venice Italy

ISBN: (纸本)9781467331227

Motor rehabilitation after stroke injury is highly important since the number of people suffering this disease is constantly increasing. brain-computer interfaces (BCIs) have been recently used in the recovery of motor functions: in particular, the closed loop involving sensorimotor brain rhythms, assistive-robot training and proprioceptive feedback in an operant learning fashion might be potentially one of the most effective ways to promote the neural plasticity of the ipsilesional brain hemisphere and to restore motor abilities. This study aimed at implementing such a scheme: one chronic stroke patient was recruited and underwent the experiment using both the damaged and the healthy arm, considered as control during the following analysis. Kinematic and neurophysiological outcomes confirmed the efficacy of this treatment and supported the hypothesis that a contingent force feedback can improve motor functions of the upper limb.

关键词： stroke upper limb brain-computer interface proprioceptive contingent force feedback sensorimotor closed-loop sensorimotor rhythms neuroplasti city motor rehabilitation

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brain-computer interface Based Stroke Rehabilitation For Hemiplegia 7

Brain-Computer Interface Based Stroke Rehabilitation For Hem...

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7th Biomedical Engineering International Conference

作者： Triponyuwasin, Preechapawan Wongsawat, Yodchanan Mahidol Univ Dept Biomed Engn Puttamonthon 4 Salaya 73170 Nakornpathom Thailand

ISBN: (纸本)9781479968008

Stroke is widely common cause of death and disability in adult. It is occurred when the blood supply in the brain is ruptured or blocked. Post stroke rehabilitation is the most important for stroke survivors because it assists them to restore their physical function such as arm movement, walking and daily life activity. Neuro-rehabilitation can enhance neuron pathways and improve motor function of patients. The neuron system can be restored their function and it is called neuroplasticity. The purpose of this paper is to develop stroke rehabilitation for hemiplegia based on brain-computer interface (BCI). ERD/ERS which occur during motor imagery and motor execution of arm or leg are used as the control in this system. Most of BCI based stroke rehabilitation classified between right and left arm but stroke patients with hemiplegia cannot move their arm and leg on each side of the body. So this system is designed to classify between arm and leg. The upper limb and lower limb rehabilitation device are controlled from their motor imagery and feed back to user via rehabilitation device and virtual reality game. The rehabilitation system was design with facilitation and suitability for stroke patients.

关键词： Stroke Rehabilitation brain-computer interface Event-Related Desynchronization Hemiplegia

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brain-computer interface Based Stochastic Navigation and Control of a Semiautonomous Mobile Robot in an Indoor Environment 2

Brain-Computer Interface Based Stochastic Navigation and Con...

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2nd International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Su, Wenbin Li, Zhijun South China Univ Technol Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781538632604

In this paper, we propose a brain-computer interface (BCI) based on the control strategy which combines the simultaneous localization and mapping (SLAM) to obtain the unknown environmental information and builds a global environment map for a mobile robot. The online BCI analyzes the electroencephalograph (EEG) signals based on steady-state visually evoked potentials (SSVEP) that the human intentions can be recognized accurately, and the motion commands are produced by the multivariate synchronization index (MSI) algorithm. Probability potential fields (PPF) approach based on the probability density function of two dimensional normal distribution is connected with the brain signals to produce the motion commands which generate a trajectory without collision. The whole system is semi-autonomous when the RGB landmarks are regarded as the environmental features learned by the FastSLAM algorithm, and the robot's low level behaviors are autonomous since the stochastic navigation is executed by the BCI. In addition, a kinematic controller is also adopted to control the low level movements. The entire system has been tested and the results have verified the effectiveness of the proposed approach.

关键词： brain-computer interface steady-state visually evoked potentials multivariate synchronization index probability potential field FastSLAM

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brain-computer interface for the epileptic seizures prediction and prevention 8

Brain-computer interface for the epileptic seizures predicti...

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8th International Winter Conference on brain-computer interface (BCI)

作者： Maksimenko, Vladimir Luettjohann, Annika van Heukelum, Sabrina Kelderhuis, Janita Makarov, Vladimir Hramov, Alexander Koronovskii, Alexey van Luijtelaar, Gilles Innopolis Univ Innopolis Tatarstan Russia Univ Munster Munster Germany Radboud Univ Nijmegen Nijmegen Netherlands Saratov NG Chernyshevskii State Univ Saratov Russia

ISBN: (数字)9781728147079

ISBN: (纸本)9781728147079

30% of epileptic patients are resistant to drug therapy. A prospective treatment strategy for refractory epilepsy patients is a brain-computer interface (BCI) in which the epileptic seizures are modulated either by the preprogrammed stimulation schedules (open loop) or via the closed-loop stimulation. The closed-loop BCI implies that seizures are automatically detected and that the detection triggers stimulation which subsequently aborts seizures. Up to now, this experimental treatment is only able to reduce seizures duration, while the ultimate aim is their complete abolishment. We have developed a closed-loop BCI aimed to predict and prevent spike-wave discharges, the electro-physiological anchor of absence seizures, in a genetic absence rat model;it predicted 45% of the seizures while the remaining ones were detected. When we evaluated the combination of the prediction and seizure detection with closed-loop electrical stimulation, a 72% decrease of seizure activity duration was achieved.

关键词： brain-computer interface seizure prediction brain stimulation

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brain-computer interface as Networking Entity in Body Area Networks 13th

Brain-Computer Interface as Networking Entity in Body Area N...

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13th International Conference on Wired and Wireless Internet Communications (WWIC)

作者： Lopez-Gordo, M. A. Pelayo Valle, F. Univ Cadiz Dept Engn Automat & Elect Elect Architecture Comp Cadiz Spain Univ Granada Dept Signal Theory Commun & Networking E-18071 Granada Spain Nicolo Assoc Granada Spain Univ Granada Dept Comp Architecture & Technol E-18071 Granada Spain

ISBN: (纸本)9783319225722;9783319225715

Modern BCIs are non-invasive, wireless, wearable and EEG-based systems capable to transduce brain signals into cognitive information and stream it out in form of data. BCIs have rarely been considered as part of the network. Thus, data communication approaches have not even tried. The consequence is a suboptimal communication in terms of performance, usability and reliability. In this paper we present BCI as a paradigm in Wireless Body Area Networks (WBANs) that interfaces multisensorial sources with the user brain. The BCI-WBAN concept treats cognitive processes as communication end-points in which sensorial information is consumed by cognitive processes. In the context of WBAN, BCIs implement the functionalities of the lower layers of communication open system: signal transduction into data, access control to the physical and cognitive media and data transmission. The BCI-WBAN paradigm extends the scope of WBAN from mere biosignal sensing by adding interpretation of neural correlates of cognitive information.

关键词： Telemedicine EEG WBAN brain-computer interface

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brain-computer interface with Robot-Assisted Training for Neurorehabilitation 26th

Brain-Computer Interface with Robot-Assisted Training for Ne...

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26th International Conference on Artificial Neural Networks (ICANN)

作者： Rosipal, Roman Porubcova, Natalia Barancok, Peter Cimrova, Barbora Teplan, Michal Farkas, Igor Slovak Acad Sci Inst Measurement Sci Bratislava Slovakia EuroRehab Sro Bratislava Slovakia Comenius Univ Fac Math Phys & Informat Bratislava Slovakia

ISBN: (纸本)9783319686004;9783319685991

To improve upper limb neurorehabilitation in chronic stroke patients, we apply new methods and tools of clinical training and machine learning for the design and development of an intelligent system allowing the users to go through the process of self-controlled training of impaired motor pathways. We combine the brain–computer interface (BCI) technology with a robotic splint into a compact system that can be used as a robot-assisted neurorehabilitation tool. First, we use the mirror therapy (MT) which represents a mental process where an individual rehearses a specific limb movement by reflecting the movements of the non-paretic side in the mirror as if it were the affected side. This step is not used for improving the motor functions only, but also for identification of subject’s specific electroencephalogram (EEG) oscillatory elemental patterns or “atoms” associated with imagery or real hand movements. We estimate these EEG atoms using a multiway analysis, specifically the parallel factor analysis (PARAFAC) for modeling. Using the data from a longitudinal case study, we will report statically significant effects of the MT on the modulation of sensorimotor EEG atoms of a patient with chronic upper limb impairment due to a stroke. Second, we introduce the BCI-based robotic system operating on the principle of the motor imagery and incorporating a reward-based physical movement of the impaired upper limb. The novelty of this approach lies in the design of the control protocol which uses spatial and frequency weights of the previously estimated sensorimotor atoms during the MT sessions. By projecting the recorded EEG onto the spatial and frequency weights, one-dimensional time scores of the atoms are computed. Getting under the empirically preset threshold of the scores triggers the robotic splint which executes the physical movement with the impaired hand (up and down). We will report analytical and clinical results of three patients with different severity of the u

关键词： brain-computer interface Robotic arm Multiway analysis

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brain-computer interface for alertness estimation and improving 15

Brain-computer interface for alertness estimation and improv...

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Conference on Dynamics and Fluctuations in Biomedical Photonics XV

作者： Hramov, Alexander Maximenko, Vladimir Hramova, Marina Yurij Gagarin State Tech Univ Saratov REC Artificial Intelligence Syst & Neurotechnol Politech Skaya Str 77 Saratov 410056 Russia Saratov NG Chernyshevskii State Univ Fac Comp Sci & Informat Technol Astrakhanskaya Str 83 Saratov 410026 Russia

ISBN: (数字)9781510614727

ISBN: (纸本)9781510614727

Using wavelet analysis of the signals of electrical brain activity (EEG), we study the processes of neural activity, associated with perception of visual stimuli. We demonstrate that the brain can process visual stimuli in two scenarios: (i) perception is characterized by destruction of the alpha-waves and increase in the high-frequency (beta) activity, (ii) the beta-rhythm is not well pronounced, while the alpha-wave energy remains unchanged. The special experiments show that the motivation factor initiates the first scenario, explained by the increasing alertness. Based on the obtained results we build the brain-computer interface and demonstrate how the degree of the alertness can be estimated and controlled in real experiment.

关键词： Electroencephalogram continuous wavelet analysis brain-computer interface alertness

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brain-computer interface Design using Alpha Wave

Brain-Computer Interface Design using Alpha Wave

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8th International Conference on Mechatronics and Information Technology (ICMIT09)

作者： Zhao, Hai-bin Wang, Hong Liu, Chong Li, Chun-sheng Northeastern Univ Sch Mech Engn & Automat Shenyang Peoples R China

ISBN: (纸本)9780819478115

A brain-computer interface (BCI) is a novel communication system that translates brain activity into commands for a computer or other electronic devices. BCI system based on non-invasive scalp electroencephalogram (EEG) has become a hot research area in recent years. BCI technology can help improve the quality of life and restore function for people with severe motor disabilities. In this study, we design a real-time asynchronous BCI system using Alpha wave. The basic theory of this BCI system is alpha wave-block phenomenon. Alpha wave is the most prominent wave in the whole realm of brain activity. This system includes data acquisition, feature selection and classification. The subject can use this system easily and freely choose anyone of four commands with only short-time training. The results of the experiment show that this BCI system has high classification accuracy, and has potential application for clinical engineering and is valuable for further research.

关键词： electroencephalogram (EEG) brain-computer interface Alpha wave

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