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超低成本 3D 凝视估计:一种直观的高信息吞吐量,可与直接脑机接口相辅相成。

Ultra-low-cost 3D gaze estimation: an intuitive high information throughput compliment to direct brain-machine interfaces.

机构信息

Department of Bioengineering, Imperial College London, SW7 2AZ London, UK.

出版信息

J Neural Eng. 2012 Aug;9(4):046016. doi: 10.1088/1741-2560/9/4/046016. Epub 2012 Jul 12.

DOI:10.1088/1741-2560/9/4/046016
PMID:22791699
Abstract

Eye movements are highly correlated with motor intentions and are often retained by patients with serious motor deficiencies. Despite this, eye tracking is not widely used as control interface for movement in impaired patients due to poor signal interpretation and lack of control flexibility. We propose that tracking the gaze position in 3D rather than 2D provides a considerably richer signal for human machine interfaces by allowing direct interaction with the environment rather than via computer displays. We demonstrate here that by using mass-produced video-game hardware, it is possible to produce an ultra-low-cost binocular eye-tracker with comparable performance to commercial systems, yet 800 times cheaper. Our head-mounted system has 30 USD material costs and operates at over 120 Hz sampling rate with a 0.5-1 degree of visual angle resolution. We perform 2D and 3D gaze estimation, controlling a real-time volumetric cursor essential for driving complex user interfaces. Our approach yields an information throughput of 43 bits s(-1), more than ten times that of invasive and semi-invasive brain-machine interfaces (BMIs) that are vastly more expensive. Unlike many BMIs our system yields effective real-time closed loop control of devices (10 ms latency), after just ten minutes of training, which we demonstrate through a novel BMI benchmark--the control of the video arcade game 'Pong'.

摘要

眼球运动与运动意图高度相关,即使患者存在严重的运动缺陷,也常常能保留这些运动意图。尽管如此,由于信号解释困难且控制灵活性不足,眼动追踪并未被广泛用作受损患者的运动控制界面。我们认为,通过追踪 3D 中的注视位置,而不是 2D 中的注视位置,为人机界面提供了一个更为丰富的信号,因为它可以直接与环境进行交互,而无需通过计算机显示器进行交互。我们在这里证明,通过使用批量生产的视频游戏硬件,结合超低成本的双目眼动追踪器,可以实现与商业系统相当的性能,而成本却便宜 800 倍。我们的头戴式系统的材料成本为 30 美元,其采样率超过 120Hz,视角分辨率为 0.5-1 度。我们执行 2D 和 3D 注视估计,并控制实时体积光标,这对驱动复杂用户界面至关重要。我们的方法提供了 43 位/秒的信息吞吐量,是侵入性和半侵入性脑机接口(BMI)的十倍以上,后者要昂贵得多。与许多 BMI 不同的是,我们的系统在经过十分钟的训练后,能够实现设备的有效实时闭环控制(延迟 10 毫秒),我们通过一项新颖的 BMI 基准——视频街机游戏“Pong”的控制,证明了这一点。

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