Validation of Real-Time Gait Event Detection between In-Shoe IMUs and Force Plates During Walking

The effectiveness of lower limb mobility assistance heavily relies on accurate gait pattern detection. Optimal sup- port is achieved when sensors reliably detect gait information. This study aims to evaluate the accuracy of gait event detection using force plates compared to in-shoe IMUs under real-time conditions. Despite favorable sensor placement for real-time data collection, several challenges arose in assessing the system’s accuracy. Four healthy adults participated, performing self- paced walking on force plates while wearing in-shoe IMUs. Sagittal angular velocity (ωsagittal) is the rate of rotational movement around the sagittal plane. As these measures demon- strated the most importance to accurate event identification, we concentrated on them in our investigation, together with the norm of jerk (J), as key characteristics for recognizing gait events using IMU data. We found that accurate gait event detection of initial contact and toe-off was achieved when the ωsagittal was within the range of -300 to -340 [deg/sec] and the J fell between 100 and 440 [G/sec]. These specific parameter ranges were effective in providing precise gait event detection. The accuracy of these measurements was approximately 25 msec, with no misclassified events detected for the specified parameter ranges.