Collaboration with the UCSF Memory and Aging Center in the Development of Computer-based Technology for the Diagnosis of Neurodegenerative Diseases

与加州大学旧金山分校记忆与衰老中心合作开发用于诊断神经退行性疾病的计算机技术

• 批准号: EP/J006726/1
• 负责人: Stephen Smith
• 金额: $ 2.44万
• 依托单位: University of York
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FJ006726%2F1
• 关键词: Collaboration; UCSF; Memory; Aging; Center

Parkinson's disease, Alzheimer's disease and Lewy Body Dementia are three of the most common neurodegenerative brain disorders, affecting in excess of 600,000 people in the UK alone. All three disorders share similar symptoms and consequently, can be easily misdiagnosed. For example, diagnosis of idiopathic Parkinson's disease based on clinical features is particularly unsafe with an error in diagnosis of up to 25% having been reported. Dr Smith has developed a novel non-invasive assessment of Parkinson's Disease which uses a computer-based system to measure patients undertaking simple tasks used in conventional clinical evaluation, such as finger tapping and drawing simple geometric shapes. An initial clinical trial has recently been completed at Leeds General Infirmary which demonstrated that this technology can be used to reliably identify Parkinson's disease patients, despite them receiving medication to compensate for their symptoms. The technology has also recently been patented by IP21 Ltd on behalf of the University of York.The aim of this work is to develop the technology further to discriminate between Parkinson's disease, Alzheimer's disease and Lewy Body Dementia. The purpose of the proposed visit to the Memory Center at the University of California, San Francisco is to establish a collaboration in which to study these conditions, having well integrated teams of academics and clinical staff using the latest methods of assessment.

帕金森病、阿尔茨海默病和路易体痴呆是三种最常见的神经退行性脑疾病，仅在英国就有超过60万人受到影响。这三种疾病都有相似的症状，因此很容易被误诊。例如，基于临床特征的特发性帕金森病的诊断是特别不安全的，已经报告了高达25%的诊断错误。史密斯博士开发了一种新的帕金森病非侵入性评估方法，该方法使用基于计算机的系统来测量患者进行传统临床评估中使用的简单任务，例如手指敲击和绘制简单的几何形状。最近在利兹总医院完成了一项初步临床试验，该试验表明，尽管帕金森病患者接受药物治疗以弥补其症状，但该技术可用于可靠地识别帕金森病患者。该技术最近也由IP21有限公司代表约克大学申请了专利。这项工作的目的是进一步开发该技术，以区分帕金森氏病、阿尔茨海默氏病和路易体痴呆症。拟议访问加州大学弗朗西斯科分校记忆中心的目的是建立一个研究这些条件的合作，使用最新的评估方法，将学术和临床工作人员的团队很好地整合在一起。

项目成果

Evolving Computational Dynamical Systems to Recognise Abnormal Human Motor Function

不断发展的计算动力学系统来识别异常的人类运动功能

• 发表时间: 2012
• 作者: Jane E Alty

How slow is too slow? Objective measurement of bradykinesia in Parkinson's disease using novel non-invasive devices

慢到什么程度算太慢？

• 发表时间: 2012
• 作者: Jane E Alty