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在MATLAB仪表板中可视化眼手同步运动。

Visualizing simultaneous eye-hand movements in a MATLAB dashboard.

作者信息

Te Hudson, A Seiple, A Shafiee Sabet, M Beheshti, Jr Rizzo

机构信息

Department of Rehabilitation Medicine, NYU Langone Health, 244 E38th St., New York, NY, 10016, USA.

Department of Neurology, NYU Langone Health, 222 E40th St., New York, NY, 10016, USA.

出版信息

MethodsX. 2024 Apr 30;12:102722. doi: 10.1016/j.mex.2024.102722. eCollection 2024 Jun.

Abstract

Eye-hand coordination (EHC) is crucial to our daily activities, and its underlying mechanisms are being intensely studied. The analysis of simultaneous eye and hand movements can provide valuable insights into EHC, particularly for individuals struggling with dexterous control, such as might be caused by stroke or traumatic brain injuries. Despite advancements in motion-capture and eye tracking technologies, there is currently no automated method for visualizing concurrent eye- and hand-movement data. To address this need, we have developed a MATLAB-based dashboard designed for near instantaneous analysis and visualization of eye and hand-tracking data. This paper introduces the design of the dashboard and presents experimental results obtained from its application, leveraging simulated data inspired by our recent work in stroke. This testing suggests that our solution has the potential to significantly aid in understanding and investigating EHC by providing side-by-side and time-locked comparison of eye/hand movements along with their timing and spatio-temporal errors, offering novel opportunities for research and clinical applications.•Continuous eye movement data is collected throughout the experiment•Continuous hand movement data is collected throughout the experiment•Combine datasets and display time-locked eye-hand data in a single dashboard.

摘要

眼手协调(EHC)对我们的日常活动至关重要,其潜在机制正在被深入研究。对同时发生的眼动和手动进行分析可以为眼手协调提供有价值的见解,特别是对于那些在灵巧控制方面存在困难的个体,比如可能由中风或创伤性脑损伤导致的情况。尽管运动捕捉和眼动追踪技术取得了进步,但目前还没有用于可视化同步眼动和手动数据的自动化方法。为满足这一需求,我们开发了一个基于MATLAB的仪表盘,用于近乎即时地分析和可视化眼动和手动追踪数据。本文介绍了该仪表盘的设计,并展示了从其应用中获得的实验结果,这些结果利用了受我们近期中风研究启发而生成的模拟数据。该测试表明,我们的解决方案有可能通过提供眼/手运动的并排比较和时间锁定比较,以及它们的时间和时空误差,显著有助于理解和研究眼手协调,为研究和临床应用提供新的机会。

  • 在整个实验过程中收集连续的眼动数据

  • 在整个实验过程中收集连续的手动数据

  • 合并数据集并在单个仪表盘中显示时间锁定的眼手数据。

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