Evaluating Parameters of the TUG Test Based on Data from IMU and UWB Sensors

Abstract

The Timed Up and Go (TUG) test is a well-established, standardized test used to assess various aspects of a patient's mobility. Although its reliability is proven, instru-mentation is necessary for acquiring accurate information. This work evaluated the instrumentation of the TUG test using devices based on inertial measurement unit (IMU) and UWB radar sen-sors, and subsequently assessed test-related motion parameters, extracted from their data. To that end, five healthy individuals participated in three sessions of a TUG test, performed in slow, normal and fast speeds, while an IMU-based wearable device, the PDMonitor®, and an ultra-wideband (UWB) radar, the Aria Sensing® LT102, monitored their motion. The sessions were also timed, recorded on video, and annotated as a post-processing step. Results showed that both approaches performed very well in estimating walking duration <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$({R}^{2}=0.9{6}$</tex> for IMU and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R^{2}=0.98$</tex> for UWB) and turning duration <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(R^{2}=0.74$</tex> for IMU and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R^{2}=0.66$</tex> for UWB). Moreover, for the IMU sensors, the test duration had excellent correlation with annotations <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(R^{2}=0.98)$</tex> and results showed that gait kinematic features could be used as predictors <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(AUC=0.9955)$</tex> of detecting a high TUG score <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(T^{\mathbf{TUG}}- &gt; 13.5\mathrm{s})$</tex> , identifying increased fall risk. On the other hand, gait speed estimated using UWB data had excellent correlation (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.95) with speed calculated using annotations. The different characteristics of the two approaches, and their good performance in the TUG test's segmentation and assessment of gait parameters, indicate that they could be fused to augment the resulting information.