Department of Orthopaedics & Rehabilitation, Yale University, New Haven, CT, United States.
Division of Physical Medicine and Rehabilitation, Stanford University, Stanford, CA, United States.
Gait Posture. 2020 Jul;80:96-100. doi: 10.1016/j.gaitpost.2020.05.019. Epub 2020 May 19.
Functional ambulation limitations are features of lumbar spinal stenosis (LSS) and knee osteoarthritis (OA). With numerous validated walking assessment protocols and a vast number of spatiotemporal gait parameters available from sensor-based assessment, there is a critical need for selection of appropriate test protocols and variables for research and clinical applications.
In patients with knee OA and LSS, what are the best sensor-derived gait parameters and the most suitable clinical walking test to discriminate between these patient populations and controls?
We collected foot-mounted inertial measurement unit (IMU) data during three walking tests (fast-paced walk test-FPWT, 6-min walk test- 6MWT, self-paced walk test - SPWT) for subjects with LSS, knee OA and matched controls (N = 10 for each group). Spatiotemporal gait characteristics were extracted and pairwise compared (Omega partial squared - ω) between patients and controls.
We found that normal paced walking tests (6MWT, SPWT) are better suited for distinguishing gait characteristics between patients and controls. Among the sensor-based gait parameters, stance and double support phase timing were identified as the best gait characteristics for the OA population discrimination, whereas foot flat ratio, gait speed, stride length and cadence were identified as the best gait characteristics for the LSS population discrimination.
These findings provide guidance on the selection of sensor-derived gait parameters and clinical walking tests to detect alterations in mobility for people with LSS and knee OA.
功能性步行障碍是腰椎管狭窄症(LSS)和膝骨关节炎(OA)的特征。有许多经过验证的步行评估方案和基于传感器的评估提供的大量时空步态参数,因此迫切需要为研究和临床应用选择合适的测试方案和变量。
在膝骨关节炎和腰椎管狭窄症患者中,哪些是基于传感器的最佳步态参数和最合适的临床步行测试,可以区分这些患者群体和对照组?
我们收集了患有 LSS、膝骨关节炎和匹配对照组(每组 10 名)的受试者在三种步行测试(快步走测试-FPWT、6 分钟步行测试-6MWT、自主步行测试-SPWT)期间的足底惯性测量单元(IMU)数据。提取时空步态特征并在患者和对照组之间进行两两比较(Omega 偏平方 - ω)。
我们发现,正常 paced 步行测试(6MWT、SPWT)更适合区分患者和对照组之间的步态特征。在基于传感器的步态参数中,站立和双支撑相计时被确定为 OA 人群区分的最佳步态特征,而足平比、步速、步长和步频被确定为 LSS 人群区分的最佳步态特征。
这些发现为选择基于传感器的步态参数和临床步行测试提供了指导,以检测 LSS 和膝骨关节炎患者的移动能力变化。