Significance: We propose a video-based, motion-resilient, and fast method for estimating the position of optodes on the scalp. Aim: Measuring the exact placement of probes (e.g., electrodes and optodes) on a participant’s head is a notoriously difficult step in acquiring neuroimaging data from methods that rely on scalp recordings (e.g., electroencephalography and functional near-infrared spectroscopy) and is particularly difficult for any clinical or developmental population. Existing methods of head measurements require the participant to remain still for a lengthy period of time, are laborious, and require extensive training. Therefore, a fast and motion-resilient method is required for estimating the scalp location of probes. Approach: We propose an innovative video-based method for estimating the probes’ positions relative to the participant’s head, which is fast, motion-resilient, and automatic. Our method builds on capitalizing the advantages and understanding the limitations of cutting-edge computer vision and machine learning tools. We validate our method on 10 adult subjects and provide proof of feasibility with infant subjects. Results: We show that our method is both reliable and valid compared to existing state-of-the-art methods by estimating probe positions in a single measurement and by tracking their translation and consistency across sessions. Finally, we show that our automatic method is able to estimate the position of probes on an infant head without lengthy offline procedures, a task that has been considered challenging until now. Conclusions: Our proposed method allows, for the first time, the use of automated spatial co-registration methods on developmental and clinical populations, where lengthy, motion-sensitive measurement methods routinely fail.

中文翻译：

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基于视频的三维位置运动弹性重建，用于功能性近红外光谱和脑电图头戴式探头。


意义：我们提出了一种基于视频、运动弹性且快速的方法来估计光极在头皮上的位置。目的：测量探针（例如电极和光极）在参与者头部的精确位置是通过依赖头皮记录（例如脑电图和功能性近红外光谱）的方法获取神经影像数据的一个非常困难的步骤，并且尤其困难适用于任何临床或发育人群。现有的头部测量方法要求参与者长时间保持静止，非常费力，并且需要大量的培训。因此，需要一种快速且运动弹性的方法来估计探头的头皮位置。方法：我们提出了一种基于视频的创新方法来估计探头相对于参与者头部的位置，该方法快速、运动弹性且自动。我们的方法建立在利用尖端计算机视觉和机器学习工具的优势并了解其局限性的基础上。我们在 10 名成人受试者上验证了我们的方法，并提供了婴儿受试者的可行性证明。结果：通过估计单次测量中的探针位置并跟踪其跨会话的翻译和一致性，我们表明与现有的最先进方法相比，我们的方法既可靠又有效。最后，我们表明，我们的自动方法能够估计探针在婴儿头部的位置，而无需冗长的离线程序，这是一项迄今为止被认为具有挑战性的任务。 结论：我们提出的方法首次允许在发育和临床人群中使用自动空间共同配准方法，而冗长的运动敏感测量方法通常会失败。