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Controlling Assistive Machines in Paralysis Using Brain Waves and Other Biosignals

机译:使用脑电波和其他生物信号控制瘫痪中的辅助机器

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摘要

The extent to which humans can interact with machines significantly enhanced through inclusion of speech, gestures, and eye movements. However, these communication channels depend on a functional motor system. As many people suffer from severe damage of the motor system resulting in paralysis and inability to communicate, the development of brain-machine interfaces (BMI) that translate electric or metabolic brain activity into control signals of external devices promises to overcome this dependence. People with complete paralysis can learn to use their brain waves to control prosthetic devices or exoskeletons. However, information transfer rates of currently available noninvasive BMI systems are still very limited and do not allow versatile control and interaction with assistive machines. Thus, using brain waves in combination with other biosignals might significantly enhance the ability of people with a compromised motor system to interact with assistive machines. Here, we give an overview of the current state of assistive, noninvasive BMI research and propose to integrate brain waves and other biosignals for improved control and applicability of assistive machines in paralysis. Beside introducing an example of such a system, potential future developments are being discussed.
机译:通过包含语音,手势和眼球运动,人类与机器交互的程度大大提高。但是,这些通讯通道取决于功能正常的电机系统。由于许多人遭受严重的运动系统损害,导致瘫痪和无法交流,因此开发出将人的脑电活动或新陈代谢活动转换为外部设备控制信号的脑机接口(BMI),有望克服这种依赖性。完全瘫痪的人可以学习使用脑波来控制假肢或外骨骼。但是,当前可用的非侵入性BMI系统的信息传输率仍然非常有限,并且不允许通用控制以及与辅助机器的交互。因此,将脑波与其他生物信号结合使用可能会大大增强运动系统受损的人与辅助机器进行交互的能力。在此,我们概述了无创BMI辅助研究的现状,并建议整合脑电波和其他生物信号,以改善对辅助机器的控制和麻痹性。除了介绍此类系统的示例外,还在讨论潜在的未来发展。

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  • 来源
    《Advances in human-computer interaction 》 |2013年第2013期| 369425.1-369425.9| 共9页
  • 作者单位

    Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, University of Tuebingen, Silcherstrasse 5, 72076 Tuebingen, Germany,Applied Neurotechnology Lab, Department of Psychiatry and Psychotherapy, University of Tuebingen, Calwerstrasse 14, 72076 Tuebingen, Germany,International Max Planck Research School for Neural Information Processing, OEsterbergstrasse 3, 72074 Tuebingen, Germany;

    Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, University of Tuebingen, Silcherstrasse 5, 72076 Tuebingen, Germany,Applied Neurotechnology Lab, Department of Psychiatry and Psychotherapy, University of Tuebingen, Calwerstrasse 14, 72076 Tuebingen, Germany,International Max Planck Research School for Neural & Behavioral Sciences, OEsterbergstrasse 3, 72074 Tuebingen, Germany;

    Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, University of Tuebingen, Silcherstrasse 5, 72076 Tuebingen, Germany,Applied Neurotechnology Lab, Department of Psychiatry and Psychotherapy, University of Tuebingen, Calwerstrasse 14, 72076 Tuebingen, Germany;

    Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, University of Tuebingen, Silcherstrasse 5, 72076 Tuebingen, Germany,Applied Neurotechnology Lab, Department of Psychiatry and Psychotherapy, University of Tuebingen, Calwerstrasse 14, 72076 Tuebingen, Germany;

    The BioRobotics Institute, Scuola Superiore Sant'Anna, V.le R. Piaggio 34, 56025 Pontedera, Italy;

    The BioRobotics Institute, Scuola Superiore Sant'Anna, V.le R. Piaggio 34, 56025 Pontedera, Italy;

    The BioRobotics Institute, Scuola Superiore Sant'Anna, V.le R. Piaggio 34, 56025 Pontedera, Italy;

    Institute of Medical Psychology and Behavioral Neurobiology and MEG Center, University of Tuebingen, Silcherstrasse 5, 72076 Tuebingen, Germany,Applied Neurotechnology Lab, Department of Psychiatry and Psychotherapy, University of Tuebingen, Calwerstrasse 14, 72076 Tuebingen, Germany;

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