帕金森震颤检测分析关键技术研究

发布时间：2018-02-26 10:07

本文关键词： 帕金森病震颤信号检测 MEMS 功率谱分析　出处：《重庆理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：帕金森病(Parkinson’s disease,PD)是一种常见的神经系统变性疾病,起病隐袭,进展缓慢。老年人多见,平均发病年龄为60岁左右,该病会使患者逐渐丧失生活自理能力,对家庭对社会造成极大负担。约70%的帕金森病患者以震颤为首发症状,而震颤是神经科最常见的症状之一,是许多疾病或综合征的首发表现,疾病早期临床上很难鉴别。临床上医生主要凭主观判断诊断分类震颤,缺乏客观评价标准,容易造成误诊。震颤的准确判断和分类可为诊断治疗震颤类疾病提供有价值信息,所以有必要对震颤进行分类和一定的量化评估。震颤的分类量化问题主要有震颤检测和震颤分析两方面工作。震颤检测为获取震颤信号,震颤分析则是分析震颤信号特征,为识别分类震颤提供相关参数。在震颤检测方面加速度惯性传感器检测方法以其方便、快捷、无创、实时监护等优点成为近几年震颤检测的研究热点。震颤分析方面频域往往能提供更多的信号特征。因此本课题在参考前人研究的基础上,选择基于惯性加速度传感器方法进行震颤检测,通过分析震颤加速度信号功率谱特征,寻找相关特征参数来区别帕金森病震颤。本课题以辅助医生客观识别评价帕金森病震颤为目的,围绕帕金森病震颤检测方法及其震颤信号分析方法进行相关研究,主要完成了工作概括为以下两个方面:一是设计制作完成了震颤信号检测系统,该系统包括震颤信号采集端和震颤信号检测操作系统。震颤信号采集端基于微机电系统(MEMS)技术的惯性传感器制作而成,具备小巧便携的特点。震颤信号检测操作系统基于VB.NET开发环境开发完成,操作界面简洁。整个检测系统以无创检测方法实现了对震颤的实时监测。二是通过制作的震颤信号检测系统完成了30例震颤数据采集(20例病理性震颤和10例生理性震颤),对所得震颤数据进行功率谱分析得出结论:1、震颤加速度信号幅度值可作为震颤程度划分参数,利用该参数对震颤的量化有可能为医生在治疗过程中判断患者的用药剂量提供帮助;2、发现帕金森病震颤、帕金森综合征震颤和特发性震颤的功率谱能量集中频率范围有重叠,难以区分。而帕金森病静止性震颤功率谱峰值频率具有倍数关系特征,该特征可识别帕金森病静止性震颤,有希望用于辅助诊断早期PD。
[Abstract]:Parkinsonian disease (PDD) is a common neurodegenerative disease, which begins quietly and progresses slowly. It is common in the elderly, with an average onset age of about 60 years, and the disease will gradually deprive patients of their ability to take care of themselves. About 70% people with Parkinson's disease start with tremor, one of the most common symptoms in neurology, and it is the first symptom of many diseases or syndromes. It is very difficult to distinguish the disease in the early clinical. In clinic, doctors mainly use subjective judgment to diagnose classified tremor, lack of objective evaluation standard, easy to cause misdiagnosis. The accurate judgment and classification of tremor can provide valuable information for diagnosis and treatment of tremor like disease. So it is necessary to classify and evaluate the tremor. The problem of classifying and quantifying the tremor mainly includes two aspects: tremor detection and tremor analysis. Tremor detection is to obtain the tremor signal, and the tremor analysis is to analyze the characteristics of the tremor signal. To identify the classification of tremor to provide relevant parameters. In tremor detection, acceleration inertial sensor detection method is convenient, fast, non-invasive, The advantages of real-time monitoring have become a hot topic in recent years. The frequency domain of tremor analysis can often provide more signal characteristics. The method based on inertial acceleration sensor is selected to detect tremor. The characteristics of power spectrum of vibration acceleration signal are analyzed. In order to identify and evaluate Parkinson's disease tremor objectively with the objective of assisting doctors to identify and evaluate the tremor, this study focused on the methods of detecting and analyzing the tremor signal of Parkinson's disease. The main work is summarized as follows: first, the tremor signal detection system is designed and manufactured. The system includes a tremor signal acquisition terminal and a tremor signal detection operating system. The tremor signal acquisition terminal is made from an inertial sensor based on the micro electromechanical system (MEMS) technology. Small portable features. Tremor signal detection operating system based on VB.NET development environment development, The operation interface is simple. The whole detection system realizes the real-time monitoring of tremor by non-invasive method. Second, 30 cases of pathological tremor and 10 cases of physiologic tremor are collected by the system. Conclusion: 1: 1, the amplitude of the tremor acceleration signal can be used as the parameter of the degree of tremor. The quantification of tremor by this parameter may be helpful for doctors to judge the dosage of drug used in patients during the course of treatment. It is found that the frequency range of power spectrum energy concentration in Parkinson's disease tremor, Parkinson's syndrome tremor and idiopathic tremor is overlapped. It is difficult to distinguish the peak frequency of power spectrum of static tremor in Parkinson's disease, which can be used to identify static tremor in Parkinson's disease and may be used to assist in early diagnosis of PD.
【学位授予单位】：重庆理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.6;R742.5

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