發(fā)布時間：2018-02-26 10:07

  本文關鍵詞： 帕金森病 震顫 信號檢測 MEMS 功率譜分析　出處：《重慶理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：帕金森病(Parkinson’s disease,PD)是一種常見的神經系統(tǒng)變性疾病,起病隱襲,進展緩慢。老年人多見,平均發(fā)病年齡為60歲左右,該病會使患者逐漸喪失生活自理能力,對家庭對社會造成極大負擔。約70%的帕金森病患者以震顫為首發(fā)癥狀,而震顫是神經科最常見的癥狀之一,是許多疾病或綜合征的首發(fā)表現(xiàn),疾病早期臨床上很難鑒別。臨床上醫(yī)生主要憑主觀判斷診斷分類震顫,缺乏客觀評價標準,容易造成誤診。震顫的準確判斷和分類可為診斷治療震顫類疾病提供有價值信息,所以有必要對震顫進行分類和一定的量化評估。震顫的分類量化問題主要有震顫檢測和震顫分析兩方面工作。震顫檢測為獲取震顫信號,震顫分析則是分析震顫信號特征,為識別分類震顫提供相關參數(shù)。在震顫檢測方面加速度慣性傳感器檢測方法以其方便、快捷、無創(chuàng)、實時監(jiān)護等優(yōu)點成為近幾年震顫檢測的研究熱點。震顫分析方面頻域往往能提供更多的信號特征。因此本課題在參考前人研究的基礎上,選擇基于慣性加速度傳感器方法進行震顫檢測,通過分析震顫加速度信號功率譜特征,尋找相關特征參數(shù)來區(qū)別帕金森病震顫。本課題以輔助醫(yī)生客觀識別評價帕金森病震顫為目的,圍繞帕金森病震顫檢測方法及其震顫信號分析方法進行相關研究,主要完成了工作概括為以下兩個方面:一是設計制作完成了震顫信號檢測系統(tǒng),該系統(tǒng)包括震顫信號采集端和震顫信號檢測操作系統(tǒng)。震顫信號采集端基于微機電系統(tǒng)(MEMS)技術的慣性傳感器制作而成,具備小巧便攜的特點。震顫信號檢測操作系統(tǒng)基于VB.NET開發(fā)環(huán)境開發(fā)完成,操作界面簡潔。整個檢測系統(tǒng)以無創(chuàng)檢測方法實現(xiàn)了對震顫的實時監(jiān)測。二是通過制作的震顫信號檢測系統(tǒng)完成了30例震顫數(shù)據(jù)采集(20例病理性震顫和10例生理性震顫),對所得震顫數(shù)據(jù)進行功率譜分析得出結論:1、震顫加速度信號幅度值可作為震顫程度劃分參數(shù),利用該參數(shù)對震顫的量化有可能為醫(yī)生在治療過程中判斷患者的用藥劑量提供幫助;2、發(fā)現(xiàn)帕金森病震顫、帕金森綜合征震顫和特發(fā)性震顫的功率譜能量集中頻率范圍有重疊,難以區(qū)分。而帕金森病靜止性震顫功率譜峰值頻率具有倍數(shù)關系特征,該特征可識別帕金森病靜止性震顫,有希望用于輔助診斷早期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.
【學位授予單位】：重慶理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN911.6;R742.5

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