Detecting and Correcting IMU Movements During Joint Angle Estimation

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. CCS CONCEPTS• Computer systems organization → Sensors and actuators; • Human-centered computing → Ubiquitous and mobile computing systems and tools.

D-H Parameter Method-based Wearable Motion Tracking

“…Data processing algorithms are currently studied [3][4][5], including the Kalman filter algorithm for the random drift of the gyroscope and accelerometer, the threshold method to solve the magnetometer disturbance, etc. ; in data fusion, Kalman filtering and complementary filtering are currently used as Representative; in the posture fitting algorithm, there are only forward kinematics [6], inverse kinematics and genetic algorithm for human body motion posture solution [7]. The innovation of this paper lies in the geometric modeling of the human body model and the creatively proposed method of human body model estimation based on the Denavic-Hartenberg (D-H) parameter method in the field of human body posture fitting.…”