Research note on gravity artifact reduction in IMU signals using Madgwick orientation estimation

Objective: Gravitational artifacts bias Inertial Measurement Unit (IMU) signals, complicating applications such as Seismocardiography (SCG). As part of the ARTIFACTS project, which investigates gravity-related artifacts under varying gravitational conditions, this study aimed to validate a gravity-artifact reduction algorithm using Madgwick orientation estimation in a controlled, physics-based simulation. Results: A computational phantom was developed using the PyBullet physics engine to generate paired datasets of ground-truth acceleration (without gravity) and simulated IMU signals (with gravitational artifacts). The Madgwick Attitude and Heading Reference System (AHRS) filter was applied to estimate the sensor orientation, followed by a low-pass-filtered gravity projection to subtract artifacts. The gravity-corrected acceleration closely matched the ground truth across all axes. Absolute mean differences were consistently below 0.006 m/s2, and Pearson correlation coefficients exceeded 0.98. Cross-correlation analysis revealed zero temporal lag, while Bland-Altman analysis showed no proportional bias. The highest precision was observed along the gravitational z-axis. The algorithm effectively isolates and removes the gravitational component while preserving the underlying dynamic translational acceleration.