Upper Body Pose Estimation Using Wearable Inertial Sensors and Multiplicative Kalman Filter
This provides a cost-effective, occlusion-resistant solution for applications like rehabilitation and gaming, though it is incremental.
The paper tackled the problem of wearable upper body pose estimation by developing a system using inertial sensors and a multiplicative Kalman filter, which achieved effectiveness validated by a high-precision optical tracker.
Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or not wearable/portable. We present a wearable pose estimation system (WePosE), based on inertial measurements units (IMUs), for motion analysis and body tracking. Differently from camera-based approaches, the proposed system does not suffer from occlusion problems and lighting conditions, it is cost effective and it can be used in indoor and outdoor environments. Moreover, since only accelerometers and gyroscopes are used to estimate the orientation, the system can be used also in the presence of iron and magnetic disturbances. An experimental validation using a high precision optical tracker has been performed. Results confirmed the effectiveness of the proposed approach.