Di Bacco Vincenzo E, Gage William H
School of Kinesiology and Health Science, York University, Toronto, ON, Canada.
School of Kinesiology and Health Science, York University, Toronto, ON, Canada.
J Biomech. 2023 Apr;151:111527. doi: 10.1016/j.jbiomech.2023.111527. Epub 2023 Mar 7.
The accelerometers embedded within smartphones may be a promising tool to capture gait patterns outside the laboratory and for extended periods of time. The current study evaluated the agreement and reliability of gait measures derived from a smartphone accelerometer system, compared to reference motion capture and footswitch systems during treadmill walking. Seventeen healthy young adults visited the laboratory on three separate days and completed three 8-minute treadmill walking trials, during each visit, at their preferred walking speed. The inter-stride interval series was calculated as the time difference between consecutive right heel contacts, located within the signals of the smartphone accelerometer, motion capture, and footswitch systems. The inter-stride interval series was used to estimate common linear gait measures and nonlinear measures, including fractal scaling index, approximate entropy, and sample entropy. Bland Altman plots with 95% limits of agreement and intraclass correlation coefficients assessed agreement and reliability, respectively. The smartphone system was found to be within the acceptable limits of agreement when compared to either reference system. The intraclass correlation coefficients values revealed moderate-to-excellent reliability for the smartphone system, with greater reliability found for linear compared to nonlinear measures and were similar to both reference systems, except for the fractal scaling index. These findings suggest the smartphone accelerometer system is a valid and reliable method for estimating linear and nonlinear gait measures during treadmill walking.
智能手机内置的加速度计可能是一种很有前景的工具，可用于在实验室外长时间捕捉步态模式。本研究评估了在跑步机行走过程中，与参考动作捕捉和脚踏开关系统相比，智能手机加速度计系统得出的步态测量值的一致性和可靠性。17名健康的年轻成年人在三个不同的日子到访实验室，每次到访时以他们偏好的步行速度完成三次8分钟的跑步机行走试验。步幅间隔序列计算为智能手机加速度计、动作捕捉和脚踏开关系统信号中连续右足跟接触之间的时间差。步幅间隔序列用于估计常见的线性步态测量值和非线性测量值，包括分形缩放指数、近似熵和样本熵。分别使用具有95%一致性界限的布兰德-奥特曼图和组内相关系数来评估一致性和可靠性。与任一参考系统相比，发现智能手机系统在可接受的一致性范围内。组内相关系数值显示智能手机系统具有中度到高度的可靠性，线性测量值的可靠性高于非线性测量值，并且除分形缩放指数外，与两个参考系统相似。这些发现表明，智能手机加速度计系统是一种在跑步机行走过程中估计线性和非线性步态测量值的有效且可靠的方法。
