A Multi-IMU System for Assessing Human Walking Dynamics Balance Using the Compass Gait Model

Assessing walking balance is crucial for identifying fall risks in older adults and optimizing rehabilitation strategies for patients with walking impairments. However, current laboratory-based methods for assessing dynamic walking balance are hard to use in daily life scenarios. To address this issue, we proposed a walking balance analysis method based on a self-developed inertial measurement unit (IMU) system consisting of 17 low-cost IMUs. This method collects motion data from key segments of the human body using the IMUs, then uses OpenSim to reconstruct human motion and extract gait parameters, and finally, analyzes walking stability through an improved compass gait model. For validation, we recruited 20 subjects to perform normal and perturbed walking experiments, and the optical motion capture system was used as the reference system. Results indicated that the root mean square error (RMSE) of the gait cycle was 0.158 seconds, and RMSEs of step length and maximum foot clearance were 0.025 m and 0.045 m, respectively. Under normal walking conditions, we calculated the balance indicator, the minimum Euclidean distance, and its RMSE was 0.027. In the perturbed walking experiment, we found that the state point significantly exceeded the balance boundary, then gradually converged and returned to the steady state, showing the effectiveness of the proposed balance stability assessment method. The developed system and the proposed method have the advantages of lightweight design, flexible application scenarios, and low power consumption, which provide a novel technical approach for daily monitoring and assessing walking balance in patients with walking impairments.