Detecting and Correcting IMU Movements During Joint Angle Estimation

TL;DR

This paper presents a lightweight online method to detect and correct IMU movements during joint angle estimation, enhancing robustness in wearable sensor systems for real-world applications.

Contribution

It introduces a novel approach to detect and correct IMU movements during joint angle estimation, addressing a key research gap.

Findings

Effective detection of IMU movements using formulated metrics

Optimal thresholds determined through synthetic data experiments

Method successfully tested on synthetic and real-user data

Abstract

Inertial measurement units (IMUs) increasingly function as a basic component of wearable sensor network (WSN)systems. IMU-based joint angle estimation (JAE) is a relatively typical usage of IMUs, with extensive applications. However, the issue that IMUs move with respect to their original placement during JAE is still a research gap, and limits the robustness of deploying the technique in real-world application scenarios. In this study, we propose to detect and correct the IMU movement online in a relatively computationally lightweight manner. Particularly, we first experimentally investigate the influence of IMU movements. Second, we design the metrics for detecting IMU movements by mathematically formulating how the IMU movement affects the IMU measurements. Third, we determine the optimal thresholds of metrics by synthetic IMU data from a significantly amended simulation model. Finally, a correction method is proposed to correct the effects of IMU movements. We demonstrate our method on both synthetic data and real-user data. The results demonstrate our method is a promising solution to detecting and correcting IMU movements during JAE.