3DArm – Inertial sensor-based 3D upper limb motion tracking and trajectories reconstruction

Description:

Continuous long-term capture of upper limb movement and trajectories can be used to assess performance in the workplace and rehabilitation at home. Wearable Inertial Measurement Units (IMUs) are an attractive solution for measuring orientation and movement of the arm because of their low cost, lightweight and small size. However, the accurate tracking of the upper limb motion can be quite challenging, due to the complexity of the upper limb bio-mechanical structure and movement.

This project aims at creating a new wearable motion tracking system based on inertial sensors to estimate orientation and find the motion trajectories of the human upper limb. To that purpose, IMUs will be placed on the upper and lower arm, enabling the measurement of each arm segment orientation. Motion trajectories will be estimated by combining sensor fusion and orientation tracking with bio-mechanical models of the upper limbs, which will take into account the relationships between each arm segment and the human motion limitations. To avoid the burden of manually aligning the sensors to each other and with the mounted arm segment, a simple calibration process must be developed.

The goal of the project is to create a motion tracking framework for the upper limb, which will enable the reconstruction of the position trajectories of the elbow and wrist joints from the orientation of each arm segment. A visualization tool reproducing in a model the movement of the arm must be developed as a Proof of Concept.

 

Main Outcomes:

A new wearable motion tracking system for the upper limb motion and trajectories tracking will be developed. Two IMUs will be required to estimate the orientation of each arm segment and, considering the bio-mechanical properties of the upper limb movement, motion trajectories of the upper limb joints will be reconstructed. To avoid the burden of manually aligning the sensors to each other and with the mounted arm segment, a simple calibration process will be created. The developed framework will enable the monitoring of complex arm movements with applications in rehabilitation and daily life monitoring.

 

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