학술논문

Evaluating Parameters of the TUG Test Based on Data from IMU and UWB Sensors
Document Type
Conference
Source
2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) Wireless and Mobile Computing, Networking and Communications (WiMob), 2022 18th International Conference on. :142-147 Oct, 2022
Subject
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Performance evaluation
Legged locomotion
Correlation
Instruments
Kinematics
Sensor phenomena and characterization
Turning
IMU sensors
UWB radars
TUG test
Motion analysis
Kinematic analysis
Language
ISSN
2160-4894
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 $({R}^{2}=0.9{6}$ for IMU and $R^{2}=0.98$ for UWB) and turning duration $(R^{2}=0.74$ for IMU and $R^{2}=0.66$ for UWB). Moreover, for the IMU sensors, the test duration had excellent correlation with annotations $(R^{2}=0.98)$ and results showed that gait kinematic features could be used as predictors $(AUC=0.9955)$ of detecting a high TUG score $(T^{\mathbf{TUG}}- > 13.5\mathrm{s})$, identifying increased fall risk. On the other hand, gait speed estimated using UWB data had excellent correlation (R 2 = 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.