Sensor-Movement-Robust Angle Estimation for 3-DoF Lower Limb Joints Without Calibration

TL;DR

This paper introduces a novel IMU-based method for 3-DoF lower limb joint angle estimation that is robust to sensor movement and does not require calibration, validated through experiments with promising accuracy and stability.

Contribution

It presents the first experimental IMU-based 3-DoF joint angle estimation method that operates without calibration and is robust to sensor movement, using a real-time optimization and error compensation strategy.

Findings

Root mean square error below 2 degrees during level walking

84.9% accuracy improvement with reference frame calibration

Stable performance over 2-minute level walking sessions

Abstract

Inertial measurement unit (IMU)-based 3-DoF angle estimation methods for lower limb joints have been studied for decades, however the calibration motions and/or careful sensor placement are still necessary due to challenges of real-time application. This study proposes a novel sensormovement-robust 3-DoF method for lower-limb joint angle estimation without calibration. A realtime optimization process, which is based on a feedback iteration progress to identify three joint axes of a 3-DoF joint, has been presented with a reference frame calibration algorithm, and a safe-guarded strategy is proposed to detect and compensate for the errors caused by sensor movements. The experimental results obtained from a 3-DoF gimbal and ten healthy subjects demonstrate a promising performance on 3-DoF angle estimation. Specially, the experiments on ten subjects are performed with three gait modes and a 2-min level walking. The root mean square error is below 2 deg for level walking and 5 deg for other two gait modes. The result of 2-min level walking shows our algorithms stability under long run. The robustness against sensor movement are demonstrated through data from multiple sets of IMUs. In addition, results from the 3-DoF gimbal indicate that the accuracy of 3-DoF angle estimation could be improved by 84.9% with our reference frame calibration algorithm. In conclusion, our study proposes and validates a sensor-movement-robust 3-DoF angle estimation for lowerlimb joints based on IMU. To the best of our knowledge, our approach is the first experimental implementation of IMUbased 3-DoF angle estimation for lower-limb joints without calibration.