首页> 外文OA文献 >Discriminating Healthy Control and Two Clinical Subgroups of Nonspecific Chronic Low Back Pain Patients Using Trunk Muscle Activation and Lumbosacral Kinematics of Postures and Movements
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Discriminating Healthy Control and Two Clinical Subgroups of Nonspecific Chronic Low Back Pain Patients Using Trunk Muscle Activation and Lumbosacral Kinematics of Postures and Movements

机译:使用躯干肌肉激活和姿势和运动的腰ac运动学来区分健康控制和非特异性慢性下腰痛患者的两个临床亚组

摘要

Study Design. Statistical Classification Model for nonspecificchronic low back pain (NS-CLBP) patients andcontrols based on parameters of motor control.Objective. Develop a Statistical Classification Model todiscriminate between 2 subgroups of NS-CLBP (FlexionPattern [FP] and Active Extension Pattern [AEP]) and acontrol group using biomechanical variables quantifyingparameters of motor control.Summary of Background Data. It has been well documentedthat many CLBP patients have motor control impairmentsof their lumbar spine. O’Sullivan proposed amechanism-based classification system for NS-CLBP withmotor control impairments based on a comprehensivesubjective and physical examination to establish the relationshipbetween pain provocation and spinal motorcontrol. For the FP and AEP s, 2 groups defined byO’Sullivan and under investigation is this study, the motorcontrol impairment is considered to be the mechanismmaintaining their CLBP. No previous studies haveused a Statistical Model with measurements of motorcontrol impairment to subclassify NS-CLBP patients.Methods. Thirty-three NS-CLBP patients (20 FP and 13AEP) and 34 asymptomatic subjects had synchronizedlumbosacral kinematics and trunk muscle activation recordedduring commonly reported aggravating posturesand movements. Biomechanical variables were quantifiedand a Statistical Classification Model was developed.Results. The Statistical Model used 5 kinematic and 2electromyography variables. The model correctly classified96.4% of cases.Conclusion. Selected biomechanical variables werepredictors for subgroup membership and were able todiscriminate the 3 subgroups. This study adds furthersupport toward the validation of the proposed classificationsystem.Key words: low back pain, subclassification, electromyography,motion analysis, posture, motor control impairment.Spine 2009;34:1610–1618
机译:学习规划。基于运动控制参数的非特异性慢性下背痛(NS-CLBP)患者和控制的统计分类模型。利用运动控制的生物力学变量量化参数,建立一个统计分类模型来区分NS-CLBP的两个亚组(FlexionPattern [FP]和主动扩展模式[AEP])与一个对照组。背景数据概述。已有大量文献证明,许多CLBP患者的腰椎运动控制障碍。奥沙利文(O’Sullivan)基于综合的主观和身体检查,提出了一种基于运动机理的NS-CLBP运动控制障碍分类系统,以建立疼痛激发与脊柱运动控制之间的关系。对于FP和AEP来说,由O’Sullivan定义的2个小组正在接受研究,这项研究正在研究中,运动控制障碍被认为是维持其CLBP的机制。以前没有研究使用统计模型来测量运动控制障碍,从而将NS-CLBP患者分类为亚型。 33例NS-CLBP患者(20 FP和13AEP)和34例无症状受试者在通常报道的加重姿势和运动过程中记录了腰s运动学和躯干肌肉激活。量化生物力学变量并建立统计分类模型。统计模型使用了5个运动学变量和2个肌电图变量。该模型正确分类了96.4%的案例。选定的生物力学变量是亚组成员资格的预测因子,能够区分3个亚组。这项研究为拟议的分类系统的验证提供了进一步的支持。关键词:下背痛,亚分类,肌电图,运动分析,姿势,运动控制障碍。脊柱2009; 34:1610–1618

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