PDF(Pubmed)
Abstract：
OBJECTIVE: To avoid deviation caused by the traditional scale method, the present study explored the accuracy, advantages, and disadvantages of different objective detection methods in evaluating lower extremity motor function in elderly individuals.
METHODS: Studies on lower extremity motor function assessment in elderly individuals published in the PubMed, Web of Science, Cochrane Library and EMBASE databases in the past five years were searched. The methodological quality of the included trials was assessed using RevMan 5.4.1 and Stata, followed by statistical analyses.
RESULTS: In total, 19 randomized controlled trials with a total of 2626 participants, were included. The results of the meta-analysis showed that inertial measurement units (IMUs), motion sensors, 3D motion capture systems, and observational gait analysis had statistical significance in evaluating the changes in step velocity and step length of lower extremity movement in elderly individuals (P < 0.00001), which can be used as a standardized basis for the assessment of motor function in elderly individuals. Subgroup analysis showed that there was significant heterogeneity in the assessment of step velocity [SMD=-0.98, 95%CI(-1.23, -0.72), I2 = 91.3%, P < 0.00001] and step length [SMD=-1.40, 95%CI(-1.77, -1.02), I2 = 86.4%, P < 0.00001] in elderly individuals. However, the sensors (I2 = 9%, I2 = 0%) and 3D motion capture systems (I2 = 0%) showed low heterogeneity in terms of step velocity and step length. The sensitivity analysis and publication bias test demonstrated that the results were stable and reliable.
CONCLUSIONS: observational gait analysis, motion sensors, 3D motion capture systems, and IMUs, as evaluation means, play a certain role in evaluating the characteristic parameters of step velocity and step length in lower extremity motor function of elderly individuals, which has good accuracy and clinical value in preventing motor injury. However, the high heterogeneity of observational gait analysis and IMUs suggested that different evaluation methods use different calculation formulas and indicators, resulting in the failure to obtain standardized indicators in clinical applications. Thus, multimodal quantitative evaluation should be integrated.
METHODS: Studies on lower extremity motor function assessment in elderly individuals published in the PubMed, Web of Science, Cochrane Library and EMBASE databases in the past five years were searched. The methodological quality of the included trials was assessed using RevMan 5.4.1 and Stata, followed by statistical analyses.
RESULTS: In total, 19 randomized controlled trials with a total of 2626 participants, were included. The results of the meta-analysis showed that inertial measurement units (IMUs), motion sensors, 3D motion capture systems, and observational gait analysis had statistical significance in evaluating the changes in step velocity and step length of lower extremity movement in elderly individuals (P < 0.00001), which can be used as a standardized basis for the assessment of motor function in elderly individuals. Subgroup analysis showed that there was significant heterogeneity in the assessment of step velocity [SMD=-0.98, 95%CI(-1.23, -0.72), I2 = 91.3%, P < 0.00001] and step length [SMD=-1.40, 95%CI(-1.77, -1.02), I2 = 86.4%, P < 0.00001] in elderly individuals. However, the sensors (I2 = 9%, I2 = 0%) and 3D motion capture systems (I2 = 0%) showed low heterogeneity in terms of step velocity and step length. The sensitivity analysis and publication bias test demonstrated that the results were stable and reliable.
CONCLUSIONS: observational gait analysis, motion sensors, 3D motion capture systems, and IMUs, as evaluation means, play a certain role in evaluating the characteristic parameters of step velocity and step length in lower extremity motor function of elderly individuals, which has good accuracy and clinical value in preventing motor injury. However, the high heterogeneity of observational gait analysis and IMUs suggested that different evaluation methods use different calculation formulas and indicators, resulting in the failure to obtain standardized indicators in clinical applications. Thus, multimodal quantitative evaluation should be integrated.
摘要：
目的：为避免传统量表法造成的偏差，本研究探索了准确性，优势,不同客观检测方法在评价老年人下肢运动功能中的不足。
方法：发表在PubMed上的老年人下肢运动功能评估研究，WebofScience,搜索了过去五年的CochraneLibrary和EMBASE数据库。使用RevMan5.4.1和Stata评估纳入试验的方法学质量，其次是统计分析。
结果：总计，19项随机对照试验，共有2626名参与者，包括在内。荟萃分析的结果表明，惯性测量单元(IMU)，运动传感器，3D运动捕捉系统，和观察性步态分析在评估老年人下肢运动步速和步长的变化方面具有统计学意义（P<0.00001），可作为评估老年人运动功能的标准化依据。亚组分析显示，阶梯速度评估存在显著异质性[SMD=-0.98，95CI（-1.23，-0.72），I2=91.3%，P<0.00001]和步长[SMD=-1.40,95CI(-1.77,-1.02),I2=86.4%，P<0.00001]在老年人中。然而,传感器(I2=9%，I2=0％）和3D运动捕获系统（I2=0％）在步进速度和步长方面表现出较低的异质性。敏感性分析和发表偏倚检验表明，结果稳定可靠。
结论：观察性步态分析，运动传感器，3D运动捕捉系统，和IMU，作为评估的手段，步速和步长的特征参数对老年人下肢运动功能的评价具有一定作用,对预防运动损伤具有较好的准确性和临床价值。然而,观察步态分析和IMU的高度异质性表明，不同的评价方法采用不同的计算公式和指标，导致在临床应用中无法获得标准化指标。因此，多模态定量评价应整合。
方法：发表在PubMed上的老年人下肢运动功能评估研究，WebofScience,搜索了过去五年的CochraneLibrary和EMBASE数据库。使用RevMan5.4.1和Stata评估纳入试验的方法学质量，其次是统计分析。
结果：总计，19项随机对照试验，共有2626名参与者，包括在内。荟萃分析的结果表明，惯性测量单元(IMU)，运动传感器，3D运动捕捉系统，和观察性步态分析在评估老年人下肢运动步速和步长的变化方面具有统计学意义（P<0.00001），可作为评估老年人运动功能的标准化依据。亚组分析显示，阶梯速度评估存在显著异质性[SMD=-0.98，95CI（-1.23，-0.72），I2=91.3%，P<0.00001]和步长[SMD=-1.40,95CI(-1.77,-1.02),I2=86.4%，P<0.00001]在老年人中。然而,传感器(I2=9%，I2=0％）和3D运动捕获系统（I2=0％）在步进速度和步长方面表现出较低的异质性。敏感性分析和发表偏倚检验表明，结果稳定可靠。
结论：观察性步态分析，运动传感器，3D运动捕捉系统，和IMU，作为评估的手段，步速和步长的特征参数对老年人下肢运动功能的评价具有一定作用,对预防运动损伤具有较好的准确性和临床价值。然而,观察步态分析和IMU的高度异质性表明，不同的评价方法采用不同的计算公式和指标，导致在临床应用中无法获得标准化指标。因此，多模态定量评价应整合。
