Intelligent systems for pediatric rehabilitation

挑战**尽管出现了许多提供计算机和通信设备替代途径的技术，但仍有成千上万的加拿大严重残疾儿童和青年没有通信手段。这些所谓的接入技术利用从肌肉激活到脑电波的一切。然而，现有技术的不足部分是因为它们不知道用户的情绪或精神状态。例如，当用户感到沮丧或疲倦时，他或她的大脑和身体控制信号会发生巨大变化。因此，接入技术误解了用户的意图，进一步加剧了沟通能力的下降。**建议的研究**通过这项NSERC发现拨款，我们将以我们实验室和其他实验室最近的研究为基础，表明用户的某些性格，如焦虑、强烈的积极或消极情绪和精神疲劳，可以被机器可靠地检测到。特别是，申请人研究计划的下一阶段的目标是系统和全面地表征疲劳，沮丧和注意力，与访问技术使用最相关的用户状态。为了实现这一目标，我们将测量大脑活动（电和血液氧合）和面部温度分布，同时用户重复执行一些旨在诱导用户状态发生目标变化的活动。我们之所以选择上述测量，是因为已有文献表明，大脑和面部温度模式对用户的情绪反应高度敏感。我们将使用创新的成像和多元模式发现技术开发用户状态的生理表现模型，以及其他方法。我们打算回答的一些问题包括：(1)生理变化的总体模式最能预测用户状态的变化？(2)不同测量方式的生理变化序列是否有助于破译用户状态的演变？(3)什么样的信号/图像特征方法和相应的分类算法可以在线区分用户状态？**一旦我们有了识别用户状态的机制，我们将研究如何利用这些信息通过替代访问技术来改善通信。具体来说，我们将从探索用户状态的知识如何指导用户界面的适应开始，例如，通过向用户提供有用的提示。我们还将考虑用户状态可能告知机器对用户控制信号理解的持续改进的方法。这项研究之所以重要，是因为：(1)它将为多种生理测量的处理和机器解释提供新的分析方法；(2)它不仅会极大地改善儿童和青少年的交流，而且会极大地改善使用技术进行交流的各个年龄段的个人的交流。因此，拟议的项目将加强加拿大在康复工程方面的国际领导地位，与当地和国际学术、临床和工业利益相关者合作。**预期结果**通过这项NSERC资助，10名应用科学与工程博士生和4名博士后将在与康复工程相关的先进仪器，信号处理和信号分类技术方面进行培训。这些人将在学术界和工业界担任领导角色，从而进一步推进大脑和身体-机器接口的科学知识。

CHALLENGE**Many tens of thousands of Canadian children and youth with severe disabilities still do not have a means of communication despite the advent of numerous technologies that provide alternative access to computers and communication devices. These so-called access technologies tap into everything from muscle activations to brain waves. However, existing technologies fall short in part because they are unaware of the user's emotional or mental state. For example, when a user becomes frustrated or tired, his or her brain and bodily control signals can change dramatically. As a result the access technology misinterprets the user's intention, further exacerbating the decline in ability to communicate.**PROPOSED RESEARCH**Through this NSERC discovery grant, we will build on recent research by our lab and others, showing that certain dispositions of the user, such as anxiety, intense positive or negative emotions and mental fatigue, can be reliably detected by machine. In particular, the aim of this next phase of the applicant's research program is to systematically and comprehensively characterize fatigue, frustration and attention, user states that are most pertinent to access technology use. To realize this objective, we will measure brain activity (electrical and blood oxygenation) and temperature distributions in the face while users repeatedly perform a number of activities designed to induce the targeted changes in user state. We select the above measurements because literature has shown that brain and facial temperature modalities are highly sensitive to a user's emotional response. We will develop models of physiological manifestations of user state using innovative imaging and multivariate pattern discovery techniques, among other methods. Some of the questions we aim to answer will include: (1) What overall patterns of physiological change are most predictive of changes in user state? (2) Are there sequences of physiological changes across measurement modalities which could be helpful in deciphering user states as they evolve? (3) What method of signal/image characteristics and accompanying classification algorithm can discriminate user states in an online fashion?**Once we have a mechanism to discern user states, we will investigate ways in which this information could be used to improve communication via an alternative access technology. Specifically, we will start by exploring ways in which knowledge of user state might guide the adaptation of the user interface, for example, by providing helpful prompts to the user. We will also consider ways in which user state might inform the continuous improvement of a machine's understanding of the user's control signals.**IMPORTANCE**This research is important because: (1) it will yield new analytical methods for the treatment and machine interpretation of multiple physiological measurements; and (2) it stands to vastly improve communication not only for children and youth, but for individuals of all ages who use technology to enable communication. The proposed program will thus strengthen Canada's international leadership in rehabilitation engineering, in partnership with local and international academic, clinical and industrial stakeholders.**ANTICIPATED OUTCOMES**Through this NSERC funding, 10 applied science and engineering doctoral students and 4 post-doctoral fellows will be trained in advanced instrumentation, signal processing and signal classification techniques relating to rehabilitation engineering. These individuals will be well-positioned to take leading roles in academia and industry, and thereby further advance scientific knowledge about brain and body-machine interfaces.