Collaborative Proposal: Functional Near Infrared Imaging for Communication and Control

严重的运动障碍严重影响着全世界数百万人的生活质量。最严重的运动障碍，即所谓的闭锁综合征，描述的是完全瘫痪和无法说话的人-他们聪明而警觉，但甚至无法交流他们最基本的需求。 几种基于检测大脑信号中微小电变化的技术已经被评估是否可以为闭锁综合征患者提供沟通渠道;尽管这些研究的结果令人鼓舞，但界面缓慢，极易出错，并且通常需要数周或数月的培训才能实现控制。 功能性近红外（fNIR）成像是一种新的和有前途的脑成像技术，测量脑中血容量和氧合的微小变化。 该技术已被探索用于增强认知和诊断，但尚未对其控制潜力进行研究。 在身体健全和锁定的受试者中进行的初步研究表明，fNIR控制更准确，更容易激活，并且不需要任何培训。 本研究的总体目标是充分表征和测试fNIR成像的控制应用。 为此，PI将首先进行全面研究，以确定最佳fNIR激活方法（例如，确定可以容易地执行并且导致可检测的大脑激活的精神任务）。本研究的产品将是一个筛选方案，可用于确定个人用户最可控的大脑区域和设备配置。 PI还将致力于改进fNIR成像方法，通过进行离线和在线研究来确定fNIR控制的最佳灵敏度，皮层深度，滤波器和信号处理算法。 本研究的产品将是一种尽可能准确、灵敏和稳健的fNIR成像设备，以及一套为特定用户优化配置设备的方法。 最后，PI将通过确定fNIR信号与传统辅助技术控制界面（如扫描或逻辑界面、光标移动和直接选择）的最佳映射，在实际应用中演示fNIR控制。 所有这些研究的结果都将通过将研究结果结合到fNIR系统的综合测试中来进行验证，具体方法是实施一个家庭使用的系统，以控制电灯开关、电视机和MP3播放器等设备，并将对五名锁定受试者进行测试。对于有严重运动障碍的人来说，研究和改善辅助技术的使用具有深远的意义。 这项研究将通过引入一种新的、未经探索的脑成像控制方法，为脑机接口领域做出重大贡献。 它还将通过建立fNIR设备和控制界面之间的协议和映射，增加辅助技术和人机界面的知识体系。 有许多人有不太严重的运动障碍（例如，麻痹），也可以通过fNIR输入设备来帮助。 对fNIR控制的进一步研究可能会导致对假肢的控制，从而恢复瘫痪肢体的运动。 另外，用于低带宽、高错误率上下文的接口策略可以在诸如移动的和可穿戴计算系统以及免提设备操作的其他领域中具有重要应用。

Severe motor disabilities significantly impact the quality of life for millions of people worldwide. The most profound motor disability, so-called locked-in syndrome, describes people who are completely paralyzed and unable to speak - they are intelligent and alert, but unable to communicate even their most basic needs. Several technologies, based on detecting minute electrical changes in brain signals, have been assessed for whether they can provide a channel of communication for people with locked-in syndrome; although the results from these studies are encouraging, the interfaces are slow, highly error prone, and often require weeks or months of training before control is achieved. Functional Near-Infrared (fNIR) imaging is a new and promising brain-imaging technology that measures small changes in blood volume and oxygenation in the brain. The technology has been explored for augmented cognition and for diagnosis, but has not been investigated for its control potential. Initial studies in able-bodied and locked-in subjects suggest that fNIR control is more accurate, easier to activate, and does not require any training. The overall goal of this research is to fully characterize and test fNIR imaging for control application. To this end, the PIs will first conduct a comprehensive study to determine optimal fNIR activation methods (e.g., determination of mental tasks that can be easily performed and that result in detectable brain activations). The product of this study will be a screening protocol that can be used to determine the most controllable brain area and device configuration for an individual user. The PIs will also work to improve fNIR imaging methods, by conducting offline and online studies to determine optimal sensitivity, cortical depth, filters, and signal processing algorithms for fNIR control. The product of this study will be an fNIR imaging device that is as accurate, sensitive, and robust as possible, as well as a set of heuristics for optimally configuring the device for a particular user. Finally, the PIs will demonstrate fNIR control in real-world applications by determining optimal mappings of fNIR signals to traditional assistive technology control interfaces such as scanning or logical interfaces, cursor movement, and direct selection. The results from all of these studies will be validated by combining and incorporating the findings into a comprehensive test of the fNIR system, by implementing a system for in-home use to control devices such as light switches, a television, and an MP3 player, which will be tested with five locked-in subjects.Broader Impacts: For people with severe motor disabilities, the implications of researching and improving access to assistive technologies are profound. This research will make a significant contribution to the area of brain-computer interfaces by introducing a new, unexplored brain imaging method for control. It will also add to the body of knowledge for assistive technology and human-computer interfaces, by establishing protocols and mappings between an fNIR device and control interfaces. There are many people with less profound motor impairments (e.g., palsy), who might also be helped by an fNIR input device. Further research in fNIR control could lead to control of prosthetics that could restore movement in paralyzed limbs. Additionally, interface strategies for low-bandwidth, high error rate contexts may have significant application in other domains such as mobile and wearable computing systems and hands-free device operation.