Related Experiment Video
Updated: Mar 7, 2026

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
Zero-Effort Camera-Assisted Calibration Techniques for Wearable Motion Sensors
1The University of Texas at Dallas, Richardson, Texas, 75080.
Abstract:
Activity recognition using wearable motion sensors plays an important role in pervasive wellness and healthcare monitoring applications. The activity recognition algorithms are often designed to work with a known orientation of sensors on the body. In the case of accidental displacement of the motion sensors, it is important to identify the new sensor location and orientation. This step, often called calibration or recalibration, requires extra effort from the user to either perform a set of known movements, or enter information about the placement of the sensors manually. In this paper, we propose a camera-assisted calibration approach that does not require any extra effort from the user. The calibration is done seamlessly when the user appears in front of the camera (in our case, a Kinect camera) and performs an arbitrary activity of choice (e.g., walking in front of the camera). We provide experimental results supporting the effectiveness of our approach.
More Related Videos
08:24Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
Published on: August 30, 2016
06:52An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
Published on: May 26, 2020