本文關(guān)鍵詞： LBP SEMG 疼痛 功能障礙　出處：《南昌航空大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：下背痛(Low Back Pain,LBP)是一種肌肉骨骼疾病,其終身流行率達(dá)84%。臨床上,疼痛和功能障礙是表征LBP患者腰椎功能特性常見的兩大指標(biāo),常采用量表對(duì)其進(jìn)行評(píng)估。但疼痛和功能障礙作為一種主觀感受,個(gè)體差異性大,且容易受外界環(huán)境影響,因此采用量表評(píng)估則具有一定的缺陷。目前,臨床上缺少一種客觀的、定量的評(píng)估腰椎功能特性的方法,而表面肌電(Surface Electromyography,SEMG)信號(hào)可以對(duì)肌肉進(jìn)行客觀定量的評(píng)估。因此,為尋找一種客觀定量的評(píng)估腰椎功能特性的方法,同時(shí)為可穿戴式脊柱健康檢測(cè)系統(tǒng)的研發(fā)提供理論基礎(chǔ)以及LBP的診斷提供輔助參考依據(jù)。本文提取了60名LBP患者腰肌SEMG信號(hào)的多個(gè)特征值,將肌電特征值與腰椎功能特性的臨床評(píng)估指標(biāo)進(jìn)行精細(xì)量化,實(shí)現(xiàn)了對(duì)腰椎功能特性的定量化研究,具有重要的臨床應(yīng)用價(jià)值。首先,說明了LBP患者的選取標(biāo)準(zhǔn),介紹了常用的腰椎功能特性的臨床評(píng)估量表,為本文后續(xù)的LBP患者腰椎功能特性的臨床評(píng)估提供理論依據(jù)。其次,對(duì)SEMG信號(hào)的預(yù)處理方法進(jìn)行了研究。基于SEMG信號(hào)的產(chǎn)生機(jī)理,分析了常用數(shù)學(xué)模型,介紹了SEMG信號(hào)采集系統(tǒng)的組成,描述了SEMG信號(hào)采集過程,并通過實(shí)驗(yàn)采集了30名健康人以及60名LBP患者腰肌的SEMG信號(hào),然后通過切比雪夫I型濾波器對(duì)SEMG信號(hào)進(jìn)行預(yù)處理。接著,研究了SEMG信號(hào)的特征提取方法。對(duì)時(shí)域、頻域以及時(shí)頻域的特征提取算法做了介紹,結(jié)合實(shí)驗(yàn)采集的SEMG信號(hào),提取了均方根、積分肌電值、中值功率頻率、中值頻率、小波系數(shù)a4最大值和小波系數(shù)a4能量等肌電特征值。最后,基于肌電特征值對(duì)LBP患者的腰椎功能特性進(jìn)行了研究和分析。首先,說明了本次實(shí)驗(yàn)對(duì)象的來源與一般資料,利用量表評(píng)估了本次實(shí)驗(yàn)中LBP患者腰椎功能特性。接著,通過統(tǒng)計(jì)學(xué)方法分析了LBP患者腰肌SEMG信號(hào)的肌電特征值的特點(diǎn),并對(duì)腰椎功能特性的量表評(píng)估結(jié)果進(jìn)行精細(xì)量化,建立了LBP患者疼痛等級(jí)與肌電特征值的一元線性回歸模型,探究了LBP患者功能障礙等級(jí)與肌電特征值的相關(guān)性。同時(shí),基于ROC曲線分析了LBP患者肌電特征值的閾值。本文系統(tǒng)定量的研究了基于SEMG信號(hào)評(píng)估LBP患者的腰椎功能特性。結(jié)果表明,SEMG信號(hào)可以作為定量評(píng)估LBP患者腰椎功能特性的一種客觀方法,其均方根、積分肌電值、中值功率頻率、中值頻率、小波系數(shù)a4最大值和小波系數(shù)a4能量等特征值可以作為腰椎功能特性評(píng)估的有效指標(biāo)。
[Abstract]:Low Back pain is a musculoskeletal disease with a lifetime prevalence rate of 84. Pain and dysfunction are two common indicators to characterize the functional characteristics of lumbar vertebrae in patients with LBP, and they are often evaluated with a scale. However, as a subjective feeling, pain and dysfunction are very different from each other. And easy to be affected by the external environment, so the use of scale evaluation has certain defects. At present, there is a lack of objective, quantitative evaluation of lumbar functional characteristics in clinical methods. The surface electromyography (SEMG) signal can be used to evaluate muscle objectively and quantitatively. In order to find an objective and quantitative method to evaluate the functional characteristics of lumbar vertebrae. At the same time to provide a theoretical basis for the development of wearable spine health detection system and provide an auxiliary reference for the diagnosis of LBP. In this paper, we extracted multiple characteristic values of SEMG signal of psoas muscle in 60 patients with LBP. The electromyography characteristic value and the clinical evaluation index of the lumbar vertebrae function characteristic are carefully quantified to realize the quantitative research of the lumbar vertebrae function characteristic, which has the important clinical application value. First of all. Explain the selection criteria of LBP patients, introduce the commonly used clinical evaluation scale of lumbar functional characteristics, and provide a theoretical basis for the follow-up clinical evaluation of lumbar functional characteristics of LBP patients. Secondly. The preprocessing method of SEMG signal is studied. Based on the generation mechanism of SEMG signal, the common mathematical model is analyzed, and the composition of SEMG signal acquisition system is introduced. The process of SEMG signal acquisition was described and the SEMG signals of psoas muscle of 30 healthy persons and 60 LBP patients were collected experimentally. Then the SEMG signal is preprocessed by Chebyshev filter. Then, the feature extraction method of SEMG signal is studied. The feature extraction algorithms in time domain and frequency domain are introduced. Combined with the SEMG signal collected from the experiment, the EMG eigenvalues such as root mean square, integral myoelectric value, median power frequency, median frequency, maximum wavelet coefficient A4 and wavelet coefficient A4 energy were extracted. Finally. The functional characteristics of lumbar vertebrae in patients with LBP were studied and analyzed based on the EMG eigenvalues. Firstly, the origin and general data of the subjects were explained. The functional characteristics of lumbar vertebrae in LBP patients were evaluated by using the scale. Then, the characteristics of electromyography (EMG) characteristic value of SEMG signal of psoas muscle in patients with LBP were analyzed by statistical method. The evaluation results of lumbar functional characteristics were carefully quantified, and a single linear regression model of pain grade and EMG characteristic value of LBP patients was established. To explore the correlation between the grade of dysfunction and the characteristic value of electromyography in patients with LBP. The threshold of EMG eigenvalue of LBP patients was analyzed based on ROC curve. The evaluation of lumbar vertebrae function of LBP patients based on SEMG signals was systematically and quantitatively studied in this paper. SEMG signal can be used as an objective method for quantitative evaluation of lumbar vertebrae function in LBP patients, including root mean square, integral myoelectric value, median power frequency and median frequency. The eigenvalues such as the maximum value of wavelet coefficient a4 and the energy of wavelet coefficient a4 can be used as an effective index to evaluate the functional characteristics of lumbar vertebrae.
【學(xué)位授予單位】：南昌航空大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R681.5;TN911.7

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