Department of Electrical and Electronic Engineering, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka.
School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6102, Australia.
Sensors (Basel). 2022 Mar 10;22(6):2164. doi: 10.3390/s22062164.
The majority of human gait modeling is based on hip, foot or thigh acceleration. The regeneration accuracy of these modeling approaches is not very high. This paper presents a harmonic approach to modeling human gait during level walking based on gyroscopic signals for a single thigh-mounted Inertial Measurement Unit (IMU) and the flexion-extension derived from a single thigh-mounted IMU. The thigh angle can be modeled with five significant harmonics, with a regeneration accuracy of over 0.999 correlation and less than 0.5° RMSE per stride cycle. Comparable regeneration accuracies can be achieved with nine significant harmonics for the gyro signal. The fundamental frequency of the harmonic model can be estimated using the stride time, with an error level of 0.0479% (±0.0029%). Six commonly observed stride patterns, and harmonic models of thigh angle and gyro signal for those stride patterns, are presented in this paper. These harmonic models can be used to predict or classify the strides of walking trials, and the results are presented herein. Harmonic models may also be used for activity recognition. It has shown that human gait in level walking can be modeled with a harmonic model of thigh angle or gyro signal, using a single thigh-mounted IMU, to higher accuracies than existing techniques.
大多数人类步态建模都是基于髋部、足部或大腿的加速度。这些建模方法的再现精度不是很高。本文提出了一种基于陀螺仪信号的水平行走时人类步态建模的谐波方法，该方法使用单个大腿安装的惯性测量单元 (IMU) 以及从单个大腿安装的 IMU 获得的屈伸来建模。大腿角度可以用五个显著的谐波来建模，每步周期的再现精度超过 0.999 相关度和小于 0.5°均方根误差。对于陀螺仪信号，使用九个显著谐波可以实现类似的再现精度。可以使用步长时间估计谐波模型的基频，误差水平为 0.0479%（±0.0029%）。本文提出了六种常见的步幅模式，以及这些步幅模式的大腿角度和陀螺仪信号的谐波模型。这些谐波模型可用于预测或分类行走试验的步幅，结果在此呈现。谐波模型也可用于活动识别。结果表明，使用单个大腿安装的 IMU，基于大腿角度或陀螺仪信号的谐波模型可以以比现有技术更高的精度来模拟水平行走时的人类步态。
