Inverse Modeling of Human Knee Joint Based on Geometry and Vision Systems for Exoskeleton Applications

Abstract

Current trends in Robotics aim to close the gap that separates technology and humans, bringing novel robotic devices in order to improve human performance. Although robotic exoskeletons represent a breakthrough in mobility enhancement, there are design challenges related to the forces exerted to the users’ joints that result in severe injuries. This occurs due to the fact that most of the current developments consider the joints as noninvariant rotational axes. This paper proposes the use of commercial vision systems in order to perform biomimetic joint design for robotic exoskeletons. This work proposes a kinematic model based on irregular shaped cams as the joint mechanism that emulates the bone-to-bone joints in the human body. The paper follows a geometric approach for determining the location of the instantaneous center of rotation in order to design the cam contours. Furthermore, the use of a commercial vision system is proposed as the main measurement tool due to its noninvasive feature and for allowing subjects under measurement to move freely. The application of this method resulted in relevant information about the displacements of the instantaneous center of rotation at the human knee joint.

Vision System-Based Design and Assessment of a Novel Shoulder Joint Mechanism for an Enhanced Workspace Upper Limb Exoskeleton

“…This paper extends the work presented in [ 18 ] for the shoulder joint, hereby is presented a novel design and assessment method for the mechanical architecture of upper limb exoskeletons. The paper is organized as follows: Section 2 includes a motion study of the human arm, determines its skeletal structure, and proposes a method for its comparison with exoskeletal structures.…”

“…This configuration shows a proper noise reduction, leading to an overall accuracy increase. Moreover, the marker plate use allows to assess data reliability, typically showing accumulated squared errors between 3 and 6 mm 2 for every marker relative position as shown in previous work [ 18 ]. Figures 8(a) and 8(b) show the VICON cameras setup and its virtual representation in NEXUS, respectively.…”

“…Placing markers directly over a subject body (skin or clothes) produce positioning errors due to the common uncertainties given by the relative motion between the markers and the user or its interface. A solution to this problem is to place the markers over rigid bodies worn by the subject [ 18 ]. Two marker plates are designed to act as rigid bodies in order to ease the subsequent data processing: (i) the static reference frame and (ii) the reference for the trajectories creation.…”

“…This analysis is further explored with motion tracking technology [ 17 ], where daily task movements are analyzed in order to construct an appropriate kinematic model of the upper limb. The work presented in this paper combines state-of-the-art motion tracking techniques that were then used by Piña-Martínez and Rodriguez-Leal [ 18 ] to analyze the knee mobility with novel kinematic models. This allows to characterize the mobility of the human joints as seen from an external structure (e.g., exoskeleton), which eases the subsequent task of biomimetic design for the development of exoskeletal mechanisms, and can be used for joints with complex CR behavior (e.g., the shoulder).…”

Command Filter Backstepping Sliding Model Control for Lower‐Limb Exoskeleton

“…From the modeling point of view, it has been proved that some methods used now are effective such as NewtonEuler equations and Lagrange dynamics [9,10]. Based on aforementioned work, series of improvements have been proposed to increase the accuracy of human-robot system model.…”