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English(EN) An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production

新型多模态系统通过MRI、脑电图和肌电图捕捉语音产生过程

研究人员开发了一种在语音产生过程中同步采集实时MRI视频、脑电图(EEG)和表面肌电图(EMG)数据的新颖方法。这种多模态方法捕捉大脑信号、肌肉激活和发音运动,由于MRI的干扰而带来了重大的技术挑战。引入了一个伪影抑制流程来解决这些问题,旨在提供对语音神经科学前所未有的见解,并推进脑机接口技术。相关的源代码和数据是公开可用的。 AI

影响 为语音神经科学和脑机接口领域开辟了新的研究途径。

排序理由 该集群描述了一篇研究论文,详细介绍了一种用于语音产生过程中数据采集的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新型多模态系统通过MRI、脑电图和肌电图捕捉语音产生过程

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该集群描述了一篇研究论文,详细介绍了一种用于语音产生过程中数据采集的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jihwan Lee, Parsa Razmara, Kevin Huang, Sean Foley, Aditya Kommineni, Haley Hsu, Woojae Jeong, Prakash Kumar, Xuan Shi, Yoonjeong Lee, Tiantian Feng, Takfarinas Medani, Ye Tian, Sudarsana Reddy Kadiri, Krishna S. Nayak, Dani Byrd, Louis Goldstein, Richar… ·

    一种用于语音产生过程中关节、大脑和肌肉活动的实时MRI视频、EEG和表面肌电图同步采集方法

    arXiv:2603.04840v2 Announce Type: replace-cross Abstract: Speech production is a complex process spanning neural planning, motor control, muscle activation, and articulatory kinematics. While the acoustic speech signal is the most accessible product of the speech production act, …