Verification of the Self-Load Assessment Capability of Inertial Measurement Units via Lumbar Musculoskeletal Simulation

Abstract

This study aims to validate the capability of inertial measurement units (IMUs) combined with surface electromyography (sEMG) sensors for assessing lumbar self-load. Lumbar biomechanical simulation was performed using OpenSim software, and data collected by IMUs and sEMG sensors were integrated into the simulation to evaluate the system’s performance in assessing lumbar load under static postures in real environments. In the experiment, 15 IMUs were fixed at human anatomical landmarks, and motion data and sEMG signals were synchronously collected during isometric tests of lumbar muscles. IMU data were converted into an OpenSim-compatible format through a self-developed processing workflow to realize musculoskeletal dynamic and kinematic analysis. The experiment included four types of static posture tests, and six sets of isometric test motion data were collected. The results showed that under different static postures, the L1–L5 lumbar joints remained stable, the distribution of joint driving torque showed a regular pattern, and the muscle driving forces were different and basically consistent with physiological reality; sEMG signal analysis verified the evaluation capability of the system, and the muscle fatigue characteristics were consistent with expectations. This study confirms the methodological effectiveness of the combination of IMU and sEMG sensors for static lumbar load assessment in real environments, providing a potential methodological reference for the clinical evaluation of nonspecific low back pain. Received: 21 November 2025 | Revised: 7 January 2026 | Accepted: 26 January 2026



Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.



Data Availability Statement

Data are available from the corresponding author upon reasonable request.



Author Contribution Statement

Zhong Wang: Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Visualization. Xiaohuan Yuan: Writing – review & editing, Supervision. Yuanliang Tang: Conceptualization, Resources, Writing – review & editing, Supervision. Shaohui Zhang: Conceptualization, Resources, Writing – review & editing, Supervision, Project administration, Funding acquisition.