Mantashloo Zahed, Abbasi Ali, Tazji Mehdi Khaleghi, Pedram Mir Mohsen
Department of Biomechanics and Sports Injuries, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran, Iran.
Department of Biomechanics and Sports Injuries, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran, Iran.
J Biomech. 2023 Apr;151:111548. doi: 10.1016/j.jbiomech.2023.111548. Epub 2023 Mar 17.
Measuring and predicting accurate joint angles are important to developing analytical tools to gauge users' progress. Such measurement is usually performed in laboratory settings, which is difficult and expensive. So, the aim of this study was continuous estimation of lower limb joint angles during walking using an accelerometer and random forest (RF). Thus, 73 subjects (26 women and 47 men) voluntarily participated in this study. The subjects walked at the slow, moderate, and fast speeds on a walkway, which was covered with 10 Vicon camera. Acceleration was used as input for a RF to estimate ankle, knee, and hip angles (in transverse, frontal, and sagittal planes). Pearson correlation coefficient (r) and Mean Square Error (MSE) were computed between the experimental and estimated data. Paired statistical parametric mapping (SPM) t-test was used to compare the experimental and estimated data throughout gait cycle. The results of this study showed that the MSE of joint angles between the experimental and estimated data ranged from 0.04 to 24.29 and r > 0.91. Moreover, the findings of SPM indicated that there was no significant difference between the experimental and estimated data of ankle, knee, and hip angles in all three planes throughout gait cycle. The results of our research developed a more accessible, portable procedure to quantifying lower limb joint angles by an accelerometer and RF. So, such wearable-based joint angles have the potential to be used in outside-laboratory settings to measure walking kinematics.
测量和预测准确的关节角度对于开发评估用户进展的分析工具非常重要。这种测量通常在实验室环境中进行，既困难又昂贵。因此，本研究的目的是使用加速度计和随机森林（RF）连续估计步行过程中的下肢关节角度。于是，73名受试者（26名女性和47名男性）自愿参与了本研究。受试者在覆盖有10台Vicon摄像机的人行道上以慢、中、快三种速度行走。加速度被用作随机森林的输入，以估计踝关节、膝关节和髋关节的角度（在横断面、额状面和矢状面）。计算实验数据和估计数据之间的皮尔逊相关系数（r）和均方误差（MSE）。使用配对统计参数映射（SPM）t检验来比较整个步态周期内的实验数据和估计数据。本研究结果表明，实验数据和估计数据之间关节角度的均方误差范围为0.04至24.29，且r>0.91。此外，SPM的结果表明，在整个步态周期的所有三个平面中，踝关节、膝关节和髋关节角度的实验数据和估计数据之间没有显著差异。我们的研究结果开发了一种更便捷、便携的程序，通过加速度计和随机森林来量化下肢关节角度。因此，这种基于可穿戴设备的关节角度有潜力用于实验室外环境中测量步行运动学。
