Randomized trial demonstrates real-time gait analysis in healthy adults, suggesting potential for rehabilitation monitoring.
To address limited segment coverage and integration drift in wearable inertial gait analysis, this work proposes a real-time multi-segment gait analysis method using seven MEMS-IMUs deployed on the pelvis and lower limbs. The method employs parameter adaptive nonlinear complementary filtering and foot-based event detection to calculate spatiotemporal parameters and joint angles. Validation against optical motion capture (OMC) showed sagittal joint angle RMSEs below 2.37°, pelvic angle RMSEs below 0.96°, and correlation coefficients above 0.89 during normal walking in healthy adults. Supported by real-time 3D skeletal visualization, the proposed system provides a low-cost and portable solution for quantitative gait assessment under controlled walking conditions, with potential for future rehabilitation monitoring after further clinical validation.
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Wang et al. (2026) studied this question.
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