Intelligent systems for pediatric rehabilitation

挑战 尽管出现了许多技术，提供了使用计算机和通信设备的替代途径，但成千上万的加拿大严重残疾儿童和青年仍然没有通信手段。这些所谓的接入技术利用了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劳时，他或她的大脑和身体控制信号可能会发生显着变化。因此，接入技术误解了用户的意图，进一步加剧了通信能力的下降。 拟议研究 通过这项NSERC发现补助金，我们将建立在我们实验室和其他人最近的研究基础上，表明用户的某些倾向，如焦虑，强烈的积极或消极情绪和精神疲劳，可以通过机器可靠地检测到。特别是，申请人的研究计划的下一阶段的目的是系统和全面地表征疲劳，挫折和注意力，用户状态是最相关的接入技术的使用。为了实现这一目标，我们将测量大脑活动（电和血氧）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。我们选择上述测量，因为文献表明，大脑和面部温度模态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等方法开发用户状态的生理表现模型。我们旨在回答的一些问题包括：（1）哪些总体生理变化模式最能预测用户状态的变化？(2)在测量模式中是否存在有助于解读用户状态的生理变化序列？(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？ 一旦我们有了一个机制来识别用户状态，我们将研究如何通过替代访问技术使用这些信息来改善通信。具体来说，我们将从探索用户状态的知识可以指导用户界面的适应的方式开始，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通知机器对用户控制信号的理解的持续改进的方式。 重要性 这项研究很重要，因为：（1）它将产生新的分析方法，用于治疗和机器解释多种生理测量结果;（2）它不仅可以大大改善儿童和青少年的沟通，还可以大大改善使用技术进行沟通的所有年龄段的个人的沟通。因此，拟议的计划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。 预期成果 通过NSERC的资助，10名应用科学和工程博士生和4名博士后研究员将接受与康复工程相关的先进仪器，信号处理和信号分类技术的培训。这些人将有能力在学术界和工业界发挥主导作用，从而进一步推进有关大脑和身体-机器界面的科学知识。

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.