Collaborative Proposal: Functional Near Infrared Imaging for Communication and Control

严重的运动残疾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，即所谓的闭锁综合症，描述的是完全瘫痪、不能说话的人——他们聪明、警觉，但甚至连最基本的需求都无法交流。一些基于检测大脑信号微小电变化的技术，已经被评估是否能为闭锁综合症患者提供一种沟通渠道；尽管这些研究的结果令人鼓舞，但这些界面速度缓慢，极易出错，并且通常需要数周或数月的训练才能实现控制。功能性近红外（fNIR）成像是一种新的、有前途的脑成像技术，可以测量大脑中血容量和氧合的微小变化。该技术已被用于增强认知和诊断，但尚未研究其控制潜力。对健全和闭锁受试者的初步研究表明，fNIR控制更准确，更容易激活，并且不需要任何训练。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将首先进行全面的研究，以确定最佳的fNIR激活方法（例如，确定容易执行的心理任务，并导致可检测的大脑激活）。这项研究的成果将是一个筛选方案，可用于确定个人用户最可控的大脑区域和设备配置。pi还将通过进行离线和在线研究来改进fNIR成像方法，以确定fNIR控制的最佳灵敏度、皮质深度、滤波器和信号处理算法。本研究的产品将是一个尽可能准确、敏感和健壮的fNIR成像设备，以及一组针对特定用户优化配置设备的启发式方法。最后，pi将通过确定fNIR信号到传统辅助技术控制接口（如扫描或逻辑接口、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将通过将研究结果结合并纳入fNIR系统的综合测试来验证，通过实施一个家庭使用的系统来控制电灯开关、电视和MP3播放器等设备，这些设备将在五个锁定的受试者中进行测试。更广泛的影响：对于患有严重运动障碍的人来说，研究和改善获得辅助技术的机会具有深远的意义。这项研究通过引入一种新的、未开发的脑成像控制方法，将对脑机接口领域做出重大贡献。它还将通过建立fNIR设备和控制接口之间的协议和映射，增加辅助技术和人机接口的知识体系。还有很多运动障碍不那么严重的人（例如，瘫痪），他们也可能会得到近红外输入设备的帮助。对近红外控制的进一步研究可能会导致对假肢的控制，从而使瘫痪的肢体恢复运动。此外，低带宽、高错误率环境下的接口策略可能在其他领域有重要的应用，如移动和可穿戴计算系统以及免提设备操作。

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.