Estimating Movement Direction From Body Orientation Using Dual Ultra-Wideband Sensors

Abstract

Accurate short-term prediction of human movement is vital for safety-critical and context-aware applications in dynamic environments. While conventional trajectory prediction methods depend on historical motion data, they often fall short in anticipating sudden directional changes. This study investigates whether body orientation, estimated using a dual ultra-wideband (UWB) sensor configuration, can serve as a reliable predictor of near-future movement direction. A wearable device with two shoulder-mounted UWB tags was used to collect position and orientation data during controlled walking experiments. Eight participants walked freely within a controlled lab environment while data were recorded. Circular cross-correlation was applied to analyze the temporal relationship between body orientation and subsequent movement direction. Results revealed a strong and statistically significant correlation across all participants (mean correlation = 0.7688, p < 0.001), with an average optimal lead time of 200 ms. The relationship remained robust using a standardized 200 ms lag (mean correlation = 0.7453). These findings demonstrate that UWB-derived body orientation can effectively predict short-term movement direction, supporting the use of UWB sensing not only for localization but also as a foundation for predictive on-body systems that enhance real-time safety and mobility monitoring.