Inertial Motion Capture and Digital Human Modeling for Ergonomic Risk Assessment of Accordion Performance

Reliable ergonomic risk assessment requires methods that capture short, asymmetric, and repetitive postures. We present a wearable, model-based workflow to evaluate posture risk during accordion playing. One experienced right-handed player performed a 10-minute standing piece wearing inertial sensors. Motion data were mapped to a scaled digital human model, the accordion mass was added at the shoulders, and postures were scored using ergonomic methods. Joint-angle exposure and L4/L5 compression, shear, and moments were also measured. The neck and trunk remained mostly near neutral, while the upper limbs showed sustained non-neutral loading, including deep right-elbow flexion and continuous wrist flexion and deviation. Peak L4/L5 compression was around 1750 N, with low shear. Results support strap adjustments, technique coaching, and practice planning to reduce upper-limb risk. This case study shows how IMU data and digital human modeling can provide fast, repeatable risk scoring for performance health.