In this paper, we propose a ROS-based system to reconstruct the motion of human upper limb based on data collected with two Myo armbands in a hybrid manner. The inertial sensors' information are fused to reconstruct shoulder and elbow kinematics. Electromyographic (EMG) signals are used to estimate wrist kinematics, to fully capture the motion of the 5-DoF (degree of freedom) user's arm. The system shows a good pose estimation accuracy compared to the XSens suit with an average RMSE of 6.61 ° ±3.31 ° and a R 2 of 0.90±0.07.

Dual-Myo Real-Time Control of a Humanoid Arm for Teleoperation

TORTORA, STEFANO
Writing – Original Draft Preparation
;
Moro, Michele
Supervision
;
Menegatti, Emanuele
Supervision
2019

Abstract

In this paper, we propose a ROS-based system to reconstruct the motion of human upper limb based on data collected with two Myo armbands in a hybrid manner. The inertial sensors' information are fused to reconstruct shoulder and elbow kinematics. Electromyographic (EMG) signals are used to estimate wrist kinematics, to fully capture the motion of the 5-DoF (degree of freedom) user's arm. The system shows a good pose estimation accuracy compared to the XSens suit with an average RMSE of 6.61 ° ±3.31 ° and a R 2 of 0.90±0.07.
2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
978-1-5386-8555-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3297574
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