Wearable Sensors & Performance Analysis
UWB and IMU-based human motion tracking and performance analysis
Overview
Research into wearable sensor systems combining UWB (Ultra-Wideband) and IMU (Inertial Measurement Unit) technologies for precise human motion tracking, fall detection, and sports performance analysis. This project spans controlled lab environments and real-world field experiments.
Controlled Localization Test Setup
A structured indoor test environment was established to validate UWB-based localization accuracy under controlled conditions. Multiple anchor nodes were positioned in a calibrated grid, enabling sub-decimeter positional accuracy measurements. IMU data was synchronized to provide complementary inertial measurements for motion state classification.
Data Driven Motion Evaluation
Collected sensor data was processed through machine learning pipelines to classify motion states, detect anomalies such as falls, and evaluate athletic performance metrics. The fusion of UWB positional data and IMU acceleration/gyroscope readings enables robust discrimination between normal activity and fall events with high sensitivity and specificity.
Field Experiments
Real-world trials were conducted in sports and healthcare settings to validate system performance outside controlled laboratory conditions. Field experiments tested the system's robustness to multipath propagation, body occlusion, and varying environmental conditions, demonstrating reliable fall detection and performance analysis in practical deployments.
Overview
K. A. Cinar, T. Soner Tekin, O. Dik, and A. Gunes, “Fall Detection Using UWB Data,” 2025 33rd Signal Processing and Communications Applications Conference (SIU), Sile, Istanbul, Turkiye: IEEE, 2025, pp. 1–4.
DOI: 10.1109/SIU66497.2025.11112503