Multi-sensor Modelling for Temporal Gait Analysis: Evaluating IMU and UWB-Based Approaches

Abstract. Wearable sensors are essential for gait analysis outside of traditional laboratory environments. However, selection of the right sensor technology involves several trade-offs. Inertial Measurement Units (IMUs) offer high temporal resolution which are ideal for detecting gait events but they suffer from drift. Ultra-Wideband (UWB) provides stable spatial data, but are less precise for detecting event timing. This paper presents a comparative study of three distinct foot-mounted sensor methodologies for heel strike detection and cadence estimation: (1) IMU-Only approach, (2) UWB-Only approach, and (3) a multi-sensor IMU+UWB fusion approach. Each method is evaluated against a camera-based ground truth system using data from four subjects. Results show the IMU-Only method is inconsistent, with moderate event precision (Avg. F1: 0.798), temporal accuracy (Avg. MAE: 47.99 ms), and subject-dependent cadence accuracy (Avg. Acc: 89.59%). The UWB-Only method provides robust event detection (Avg. F1: 0.811) with similar temporal error (Avg. MAE: 49.0 ms) but is exceptionally accurate for cadence estimation (Avg. Acc: 96.94%). The IMU+UWB fusion approach achieves the highest event precision (Avg. Precision: 0.835) and the best temporal accuracy (Avg. MAE: 46.51 ms), while also maintaining robust cadence accuracy (Avg. Acc: 95.62%). In conclusion, while the UWB-Only method is ideal for cadence-only applications, the IMU+UWB fusion approach provides the best overall balance of high event precision, superior temporal accuracy, and reliable cadence estimation.