ImpactEar: Cross Activity Ground Reaction Force Estimation using Earable IMUs

Ground Reaction Forces (GRFs) are the forces exerted between the foot and the ground during movement. They are key biomechanical indicators for gait monitoring, injury recovery tracking, and sporting performance. Traditional force plates provide gold-standard accuracy but are expensive and confined to laboratories, while leg- or foot-mounted devices require specialised hardware and sacrifice user comfort. Recent work utilising commodity devices such as smartwatches and earphones offer greater accessibility, yet wrist sensors suffer from arm-swing artifacts and existing earable studies remain activity-specific, limited to either walking or running (and never both) as GRF patterns differ drastically across locomotion types. In this paper, we propose ImpactEar, the first system to estimate complete GRF curves across multiple activities using only a pair of earable inertial measurement units (IMUs). Our core insight is to treat the head as a proxy for the body's center of mass and leverage bilateral earable IMUs to capture both translational and rotational dynamics. Combined with temporal context modeling, this enables a cross-activity mapping from head motion to GRF curves with a single model. ImpactEar employs a lightweight encoder-decoder network that reconstructs left-right GRF profiles across walking, running, and jumping in real time. The evaluation on 30 participants shows that ImpactEar achieves 8.6% normalized root mean square error (NRMSE) and 9.5 ms latency on a mobile phone streaming earable IMU data, outperforming state-of-the-art single-activity baselines and remaining robust under practical conditions, such as reduced sampling rates, single earbuds, different ground surfaces, music playback and head and facial motions. We further demonstrate the power of a cross activity model over a range of different downstream applications including gait asymmetry analysis, jump power assessment, and ballet motion evaluation. Finally, we release ImpactEarDS, the first public earable-GRF dataset with synchronised IMU and force-plate ground truth, paving the way for ubiquitous human kinetics and biomechanics research.