下背痛（LBP）是仅次于上呼吸道感染的第二大就医原因。非特异性下背痛与腰部肌肉疲劳及肌肉收缩能力下降有互为因果的关系，因此精准评价下背痛患者肌肉功能状况对其康复和治疗具有关键意义。临床上采用的问卷调查评估病况方法，存在主观性强和较粗略等局限。本项目将围绕下背痛肌肉精细定量评价这一核心目标，以腰部肌肉功能障碍评估和疼痛评估为关键点，以自主研发的基于表面肌电图（EMG）和声肌图（SMG）信息同步获取平台为技术基础，以躯体伸展和弯曲、腹部肌肉单独收缩等多种主动运动训练模式下的生物力学数据融合模式为研究对象，以多块肌肉 (腹横肌、多裂肌、内斜肌) 多数据融合的静态和动态运动分类模式为核心算法，以均方根肌电信号、超声下的肌肉厚度变化和肌肉纹理等时域分析和肌肉形态学特征建立算法模型，探索EMG和SMG量化值与下背痛患者疼痛和功能障碍不同等级的映射关系，进而完成下背痛诊断和康复的精细定量评估方法体系。

Low back pain (LBP) is second to upper respiratory problems as a symptom-related reason for visits to a physician. Nonspecific LBP is associated to lumbar muscle fatigue and decreased contractility. Therefore it is vital to evaluate muscle dysfunction of LBP patients fully for LBP rehabilitation and therapy. So far, most frequently used clinical rehabilitation evaluations based on questionnaires are subjective and absence of refined assessment. The subject focuses on the quantitative assessment of LBP muscle, including pain level assessment and dysfunction assessment. Synchronization acquisition of electromyography (EMG) and sonomyography (SMG) is the basis to analyze static status and motion of lumbar muscles, including transversus abdominis, multifidus and internal oblique muscle. Multi-source biomechanics data fusion based on different motion exercises will be studied, such as trunk flexion, extension and transverses abdominis hollowing. It is investigated that the relationship between EMG/SMG features and different scales of pain/function disability, using time-frequency analysis of EMG root mean square and morphological features such as muscle thickness change and muscle texture. Quantitative assessment would be built to diagnose different scale of LBP and rehabilitate LBP patient.