基于MEMS惯性传感器网络的帕金森病姿态监控和评估技术

项目名称： 基于MEMS惯性传感器网络的帕金森病姿态监控和评估技术

项目编号： No.61201391

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 贾方秀

作者单位： 南京理工大学

项目金额： 25万元

中文摘要： 帕金森病(Parkinson disease,PD)是一种常见的神经系统变性疾病，发病率高居世界第二。目前，衡量帕金森病人的患病类型和严重程度的方法主要依靠医生评分，评估的准确程度仍然依赖于医生的经验和主观判断，缺乏量化指标。基于此，本项目构建出基于MEMS惯性传感器网络帕金森姿态监控和评估系统。为了实现对帕金森病人的姿态监控，并在病人发生"跌倒"等意外时报警，提出一种新的行为检测和分类器算法，对人日常生活的行为动作进行正确的分类。为了实现对帕金森病震颤、运动徐缓和运动功能障碍定量评估，拟提取帕金森病运动症状相关参数，建立一种新的帕金森症状评估系统，将被测对象的日常行为与帕金森病运动症状严重性的分析相结合，实现在被测对象日常活动中对帕金森运动症状进行全面、客观的评估。该系统不仅可用于实现帕金森症的临床诊断，也可为帕金森患者提供准确、有效的治疗效果反馈。

中文关键词： 惯性传感器；帕金森病；姿态监控；运动症状评估；

英文摘要： Parkinson's disease (PD) is the second most common neurodegenerative disease in the general population. Functional motor impairment caused by Parkinson's disease and other movement disorders is currently measured with rating scales such as the Unified Parkinson's Disease Rating Scale (UPDRS). Physical examination, interviews with patients and the results of rating scales for movement disturbances are the basis for the assessment of Parkinson's disease (PD). However, subjectivity in the assessment of the symptoms and the short period of observation are disadvantageous. We have designed a new measurement system consisting of four independent, lightweight, autonomous sensing units based on MEMS inertial sensors that can continuously record body movements during daily life.In order to record body movements and alarm when some accidents like "falling" happens, a new classification algorithm are proposed to classify basic body daily posture allocaions. The ambulatory monitoring system that provides a complete motor assessment by simultaneously analyzing current motor activity of the patient and the severity of many aspects related to tremor, bradykinesia, and hypokinesia are proposed. A new PD motor assessment system are designed, and the combined analysis of motor activity and symptom severity by

英文关键词： MEMS inertial sensor；Parkison’s disease；Ambulatory monitoring；Mortor assessment；