基于表面肌电信号的腰椎功能特性的定量研究

发布时间：2018-01-26 23:10

本文关键词： LBP SEMG 疼痛功能障碍　出处：《南昌航空大学》2017年硕士论文　论文类型：学位论文

【摘要】：下背痛(Low Back Pain,LBP)是一种肌肉骨骼疾病,其终身流行率达84%。临床上,疼痛和功能障碍是表征LBP患者腰椎功能特性常见的两大指标,常采用量表对其进行评估。但疼痛和功能障碍作为一种主观感受,个体差异性大,且容易受外界环境影响,因此采用量表评估则具有一定的缺陷。目前,临床上缺少一种客观的、定量的评估腰椎功能特性的方法,而表面肌电(Surface Electromyography,SEMG)信号可以对肌肉进行客观定量的评估。因此,为寻找一种客观定量的评估腰椎功能特性的方法,同时为可穿戴式脊柱健康检测系统的研发提供理论基础以及LBP的诊断提供辅助参考依据。本文提取了60名LBP患者腰肌SEMG信号的多个特征值,将肌电特征值与腰椎功能特性的临床评估指标进行精细量化,实现了对腰椎功能特性的定量化研究,具有重要的临床应用价值。首先,说明了LBP患者的选取标准,介绍了常用的腰椎功能特性的临床评估量表,为本文后续的LBP患者腰椎功能特性的临床评估提供理论依据。其次,对SEMG信号的预处理方法进行了研究。基于SEMG信号的产生机理,分析了常用数学模型,介绍了SEMG信号采集系统的组成,描述了SEMG信号采集过程,并通过实验采集了30名健康人以及60名LBP患者腰肌的SEMG信号,然后通过切比雪夫I型滤波器对SEMG信号进行预处理。接着,研究了SEMG信号的特征提取方法。对时域、频域以及时频域的特征提取算法做了介绍,结合实验采集的SEMG信号,提取了均方根、积分肌电值、中值功率频率、中值频率、小波系数a4最大值和小波系数a4能量等肌电特征值。最后,基于肌电特征值对LBP患者的腰椎功能特性进行了研究和分析。首先,说明了本次实验对象的来源与一般资料,利用量表评估了本次实验中LBP患者腰椎功能特性。接着,通过统计学方法分析了LBP患者腰肌SEMG信号的肌电特征值的特点,并对腰椎功能特性的量表评估结果进行精细量化,建立了LBP患者疼痛等级与肌电特征值的一元线性回归模型,探究了LBP患者功能障碍等级与肌电特征值的相关性。同时,基于ROC曲线分析了LBP患者肌电特征值的阈值。本文系统定量的研究了基于SEMG信号评估LBP患者的腰椎功能特性。结果表明,SEMG信号可以作为定量评估LBP患者腰椎功能特性的一种客观方法,其均方根、积分肌电值、中值功率频率、中值频率、小波系数a4最大值和小波系数a4能量等特征值可以作为腰椎功能特性评估的有效指标。
[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.
【学位授予单位】：南昌航空大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R681.5;TN911.7

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