Intelligent monitoring: diagnosis and rehabilitation of stroke patients

智能监测：脑卒中患者的诊断与康复

• 批准号: 336975-2006
• 负责人: Glasgow, Janice
• 金额: $ 13.27万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=364357
• 关键词: Intelligent; monitoring; diagnosis; rehabilitation; stroke

Stroke is one of the most common forms of neurological disability, causing a loss of independence and a need for substantial physical and financial support. Assessment of sensory and motor impairment plays a crucial role in all facets of patient care. Current approaches for identifying impairment involve subjective rating systems that lack sensitivity and reliability. Our primary goal is to integrate robotic technology with intelligent systems for the assessment and treatment of stroke patients. We will design, develop and evaluate advanced software tc objectively quantify sensorimotor function and to assist in the diagnosis of impairment, monitoring of progress, and planning of rehabilitation therapy. As well, we will systematically study the relationship between sensory and motor control in our subjects. The proposed research will involve seven graduate students who will receive advanced training in the interdisciplinary field of neuroscience.The proposal involves a team of world class researchers working in the areas of neuroscience and biomedical computing. The research will be carried out in collaboration with industrial partners (IBM, BKIN and C-Motion) and with clinicians at Saint Mary's of the Lake Hospital in Kingston. Real-time data will be collected using KINARM, an advanced robotic device developed by our team, to measure sensory, motor and reflexive abilities in the upper limbs during multiple stages of recovery for stroke patients. This data will provide the necessary input for the development of our computational tools.Our research into intelligent systems for real-time monitoring, diagnosis and treatment of stroke patients is unique and important to Canada's aging population. The market demand for objective clinical assessment tools is enormous due to the large number of individuals afflicted with neurophysiological disorders. The outcome o: our research will provide the next generation of clinical assessment tools for upper limb sensorimotor control.

中风是最常见的神经系统残疾形式之一，导致失去独立性，需要大量的身体和经济支持。感觉和运动障碍的评估在患者护理的各个方面都起着至关重要的作用。目前识别减值的方法涉及缺乏敏感性和可靠性的主观评级系统。我们的主要目标是将机器人技术与智能系统相结合，用于中风患者的评估和治疗。我们将设计，开发和评估先进的软件，以客观地量化感觉运动功能，并协助诊断障碍，监测进展和规划康复治疗。同时，我们将系统地研究我们的主题中感觉和运动控制之间的关系。这项研究将涉及七名研究生，他们将接受神经科学跨学科领域的高级培训。这项研究涉及一个在神经科学和生物医学计算领域工作的世界级研究人员团队。这项研究将与工业合作伙伴（IBM、BKIN和C-Motion）以及金斯顿湖医院圣玛丽医院的临床医生合作进行。实时数据将使用我们团队开发的先进机器人设备KINARM收集，以测量中风患者在多个恢复阶段上肢的感觉，运动和反射能力。这些数据将为我们的计算工具的开发提供必要的输入。我们对中风患者的实时监测、诊断和治疗智能系统的研究对加拿大的老龄化人口来说是独特和重要的。客观的临床评估工具的市场需求是巨大的，由于大量的人患有神经生理疾病。结果表明：我们的研究将为上肢感觉运动控制提供新一代的临床评估工具。