A Comparative Evaluation of Open-Source Gait Event Detection Methods Using a Single Sacrum-Mounted IMU

Inertial measurement units (IMUs) provide a potential reliable alternative for out-of-the-lab gait analysis, particularly when the setup is simple, as in the case of a single sacrum-mounted sensor.However, estimating spatio-temporal gait parameters from inertial signals requires accurate detection of gait events (GEs), which allow to subdivide gait into cycles.This study benchmarks two open-source IMU-based GE detection algorithms (SensorMotion and SciKit-Digital-Health) using a public dataset of healthy adults walking at slow, comfortable, and fast speeds.Reference timings were obtained by comparing marker-derived events to force plate data using two vertical ground reaction force thresholds (20 N and 100 N), highlighting the influence of this parameter on GE timings.Across all trials, both IMU based methods managed to detect initial contacts within 40 ms, with detection rates up to 83%.In contrast, final contact (FC) detection was substantially less reliable, particularly at higher speeds, with lower detection rates and larger mean absolute errors.Although no algorithm was consistently superior across all metrics, our results favoured SKDH overall.These findings confirm that IMU-based algorithms are still suboptimal, and FC detection remains the primary limitation for sacrum-mounted IMU GE detection.