Upper Limb Posture Estimation in Robotic and Virtual Reality-Based Rehabilitation

Abstract

New motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation.

A Virtual Reality-Cycling Training System for Lower Limb Balance Improvement

“…Virtual Reality (VR) provides patients with a more realistic, varied, and enhanced sensory perception experience and also facilitates motor learning based on various feedback mechanisms [ 22 , 23 ]. It can simulate body movements of daily life, making rehabilitation more entertaining.…”

Inverse Kinematics for Upper Limb Compound Movement Estimation in Exoskeleton-Assisted Rehabilitation

“…This circumstance makes the method in [ 21 ] difficult to apply. For extended discussion, see [ 22 , 23 ].…”

“…Acknowledging different kinematic structures in limb and Exoskeleton, [ 23 ] introduces the EIKPE (Extended Inverse Kinematics Posture Estimation) method. EIKPE considers the parallel kinematic chains limb and Exoskeleton as related through the cuff constraints that fix them together.…”

“…The real-time EIKPE accuracy (circa 3-degree RMS) is reported for (1) wrist flexion-extension, (2) elbow flexion-extension, and (3) forearm pronation-supination. Limitations of [ 23 ] are (a) restriction to 1-DOF movements due to constraints in the ground-truth reading equipment and (b) elbow and wrist angle estimations.…”

A self-aligning end-effector robot for individual joint training of the human arm

“…The current results show that with the level of noise expected from rotary sensors, the human limb parameters can be estimated with relatively small bias and variance. There has been prior work on estimating human limb posture when connected to an exoskeleton robot [16], and to plan the robot's trajectory for a given human limb trajectory [15]. However, the authors are unaware of any prior work on estimating the location of the human joint and limb length using the human and robot joint kinematic data.…”