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Titlebook: Brain-Computer Interface Research; A State-of-the-Art S Christoph Guger,Brendan Allison,Junichi Ushiba Book 2017 The Author(s) 2017 BCI Pri

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發(fā)表于 2025-3-21 18:38:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Brain-Computer Interface Research
期刊簡稱A State-of-the-Art S
影響因子2023Christoph Guger,Brendan Allison,Junichi Ushiba
視頻videohttp://file.papertrans.cn/191/190289/190289.mp4
發(fā)行地址Summarizes prize-winning BCI innovations.Extends the categories of disabilities and patient groups that can benefit from BCI technologies..Includes both cutting edge science and important medical adva
學(xué)科分類SpringerBriefs in Electrical and Computer Engineering
圖書封面Titlebook: Brain-Computer Interface Research; A State-of-the-Art S Christoph Guger,Brendan Allison,Junichi Ushiba Book 2017 The Author(s) 2017 BCI Pri
影響因子This book describes the prize-winning brain-computer-interface (BCI) projects honored in the community‘s most prestigious annual award. BCIs enable people to communicate and control their limbs and/or environment?using thought processes alone. Research in this field?continues to develop and expand rapidly, with many new ideas, research groups, and improved technologies having emerged in recent years.?The chapters in this volume?feature the newest developments from many of the best labs worldwide. They present both non-invasive systems (based on the EEG) and intracortical methods (based on spikes or ECoG), and numerous innovative applications that will benefit new user groups
Pindex Book 2017
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Motor Imagery BCI with Auditory Feedback as a Mechanism for Assessment and Communication in Disordeopted scales, which have a poor prognostic reliability [.]. Individuals who are in a minimally conscious state (MCS) or vegetative state (VS), or with unresponsive wakefulness syndrome (UWS), may be incapable of providing volitional overt motor responses. This has resulted in a rate of 43% of patien
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Brain-Computer Interface Controlling Cyborg: A Functional Brain-to-Brain Interface Between Human anific micro electrical stimulation, the cyborg could be remotely controlled to make left and right turns. The motion intention could be retrieved from the human brain via brain-computer interface (BCI). Steady-state visual evoked potential (SSVEP) based-electroencephalography (EEG), as a robust BCI,
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Recovery of Brain Function by Neuroprostheses: A Challenge for Neuroscience and Technology,a biomimetic synthetic model that reliably recovered the motor learning function of the cerebellar network [., .]. While we proved feasibility by managing some neuroscientific and methodological challenges, this project was critically suggestive of the grave challenges expected on the way to reach a
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BCI-Based Facilitation of Cortical Activity Associated to Gait Onset After Single Event Multi-levellographic signal, are currently subject to extensive research. Such rehabilitation strategies follow a top-down approach in which targeted neurophysiological changes in the central nervous system are expected to induce functional improvement. However, such approach presents a set of specific limitat
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A Brain-Computer-Interface to Combat Musculoskeletal Pain, induced by musculoskeletal pain. The EEG activity patterns of participants with chronic pain (tennis elbow) were differentiated from those of healthy, age and sex matched controls during real-time movement performance. Our results showed a dominance of power in the alpha frequency range only that w
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