基于穿戴式步态分析的脊髓型颈椎病的评价研究

Due to the lack of objective evaluation method to quantify the severity of Cervical Spondylotic Myelopathy (CSM) in clinical trial, this study will apply body sensor network based gait analysis technique to detect and evaluate the severity of CSM. This study will build a gait information collection and analysis platform based on body sensor network, propose a quantitative evaluation method of CSM based on gait parameters, provide a surveillance and evaluation method for the progression of preoperative and postoperative treatment of CSM patients, screening asymptomatic CSM patients in early subclinical stage (ASCCE), and provide clinicians with an objective detection and quantitative evaluation method. It can assist the clinicians' diagnosis and treatment decisions, and provide the theoretical method for personalized treatment for each CSM patient.

由于在临床中缺少对脊髓型颈椎病的严重程度进行客观检测和量化评价的方法，本课题将开展应用基于体感网的步态分析技术，检测和量化评价脊髓型颈椎病严重程度的研究。建立基于体感网的步态信息采集分析平台，提出基于步态参数的脊髓型颈椎病病情的量化评价方法，提供脊髓型颈椎病术前病情进展和术后治疗效果的监测手段和评价方法，筛查自身无症状察觉的脊髓型颈椎病早期亚临床阶段（ASCCE）病人，为临床医生提供一种对脊髓型颈椎病病情的客观检测和量化评价方法，可以辅助医生的诊断和治疗决策，为实现每位患者量体裁衣地进行个性化的治疗提供理论方法。

本项目应用基于体感网的步态分析技术，进行检测和量化评价脊髓型颈椎病严重程度的研究。构建了基于体感网的步态信息采集分析平台，提出基于步态参数的脊髓型颈椎病病情的量化评价方法，开展了基于人体步态分析和体感网的脊髓型颈椎病监测的临床实验研究。提供脊髓型颈椎病术前病情进展和术后治疗效果的监测手段和评价方法，为临床医生提供一种对脊髓型颈椎病病情的客观检测和量化评价方法，有助于医生的诊断和治疗决策。