Accuracy and Inter-Subject Variability of Gait Event Detection Methods Based on Optical and Inertial Motion Capture

Gait events (instant of heel strikes and instant of toe-offs) are essential for extracting spatiotemporal parameters and segmenting biological signals (electromyography (EMG) and electroencephalography (EEG)) based on gait cycle. While force platforms and optical motion capture (OMC) are ideal for identifying GE, inertial measurement units (IMUs) are more applicable. This study compared the accuracy and variability from IMU- and OMC-based gait event detection methods compared with gold-standard ground reaction force (GRF) detection. Seventeen healthy adults (31 ± 8 years) walked along a 10 m walkway instrumented with force plates. Foot kinematics were recorded using two retro-reflective markers on each foot and an IMU on the sacrum. Gait events were identified using two OMC-based (OMC1, OMC2) and two IMU-based (IMU1, IMU2) algorithms. Accuracy was evaluated using root-mean-square error (RMSE) relative to GRF, and within-subject variability was assessed using coefficient of variation (CoV). The results from the instant of heel strikes, OMC1 yielded a lower RMSE (14 ms) than IMU1 (50 ms) and IMU2 (61 ms) (p < 0.001). For the instant of toe-offs, OMC1 demonstrated a lower RMSE (17 ms), differing from IMU1 (54 ms) and IMU2 (74 ms) (p < 0.001). IMU2 exhibited greatest variability (CoV = 24 ms) compared with OMC1 (7 ms) and IMU1 (9 ms) (p < 0.001). Our results highlight lower accuracy and higher variability in gait event detection using sacrum-mounted IMUs. Despite its convenience, researchers should consider the limitations of using IMUs for EMG/EEG data segmentation. Future studies validating gait event detection methods should report some type of variability metric.