Print Email Facebook Twitter Observing the state of balance with a single upper-body sensor Title Observing the state of balance with a single upper-body sensor Author Paiman (student), Charlotte Lemus Perez, D.S. (TU Delft OLD Biorobotics) Short Sotero, D.M. (SENAI Innovation Institute for Automation, Salvador) Vallery, H. (TU Delft OLD Biorobotics; ETH Zürich) Date 2016 Abstract The occurrence of falls is an urgent challenge in our aging society. For wearable devices that actively prevent falls or mitigate their consequences, a critical prerequisite is knowledge on the user’s current state of balance. To keep such wearable systems practical and to achieve high acceptance, only very limited sensor instrumentation is possible, often restricted to inertial measurement units at waist level. We propose to augment this limited sensor information by combining it with additional knowledge on human gait, in the form of an observer concept. The observer contains a combination of validated concepts to model human gait: a spring-loaded inverted pendulum model with articulated upper body, where foot placement and stance leg are controlled via the extrapolated center of mass (XCoM) and the virtual pivot point (VPP), respectively. State estimation is performed via an Additive Unscented Kalman Filter (Additive UKF). We investigated sensitivity of the proposed concept to model uncertainties, and we evaluated observer performance with real data from human subjects walking on a treadmill. Data were collected from an Inertial Measurement Unit (IMU) placed near the subject’s center of mass (CoM), and observer estimates were compared to the ground truth as obtained via infrared motion capture. We found that the root mean squared deviation did not exceed 13 cm on position, 22 cm/s on velocity (0.56–1.35 m/s), 1.2° on orientation, and 17°/s on angular velocity. Subject human gait and balancewearable sensorsstate estimationvirtual pivot pointextrapolated center of masscapture pointadditive unscented kalman filterfall detectionOA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:6a5b1649-f1ec-4470-8d21-0d35b061e403 DOI https://doi.org/10.3389/frobt.2016.00011 ISSN 2296-9144 Source Frontiers In Robotics and AI, 3 Part of collection Institutional Repository Document type journal article Rights © 2016 Charlotte Paiman (student), D.S. Lemus Perez, D.M. Short Sotero, H. Vallery Files PDF frobt_03_00011.pdf 1.61 MB Close viewer /islandora/object/uuid:6a5b1649-f1ec-4470-8d21-0d35b061e403/datastream/OBJ/view