[ARTICLE] An innovative equivalent kinematic model of the human upper limb to improve the trajectory planning of exoskeleton rehabilitation robots – Full Text

Abstract

Upper limb exoskeleton rehabilitation robots have been attracting significant attention by researchers due to their adaptive training, highly repetitive motion, and ability to enhance the self-care capabilities of patients with disabilities. It is a key problem that the existing upper limb exoskeletons cannot stay in line with the corresponding human arm during exercise. The aim is to evaluate whether the existing upper limb exoskeleton movement is in line with the human movement and to provide a design basis for the future exoskeleton. This paper proposes a new equivalent kinematic model for human upper limb, including the shoulder joint, elbow joint, and wrist joint, according to the human anatomical structure and sports biomechanical characteristics. And this paper analyzes the motion space according to the normal range of motion of joints for building the workspace of the proposed model. Then, the trajectory planning for an upper limb exoskeleton is evaluated and improved based on the proposed model. The evaluation results show that there were obvious differences between the exoskeleton prototype and human arm. The deviation between the human body and the exoskeleton of the improved trajectory is decreased to 41.64 %. In conclusion, the new equivalent kinematics model for the human upper limb proposed in this paper can effectively evaluate the existing upper limb exoskeleton and provide suggestions for structural improvements in line with human motion.

1 Introduction

Upper limb exoskeleton rehabilitation robots have become more popular because they can not only provide adaptive training and highly repetitive motion but also enhance the self-care capabilities of patients with a loss of motor function (Jarrasse et al., 2010; Côté-Allard et al., 2018; Zhang et al., 2018). The design of upper limb exoskeletons should be especially considered because they interact directly with the human body (Esmaeili et al., 2011; Gopura et al., 2011). The number of degrees of freedom (DOF), range of motion (ROM) of joints, safety, comfort, low inertia, and adaptability to the human body should be especially considered in the design of these exoskeletons (Meng et al., 2018; Maciejasz et al., 2014). In particular, it is necessary that the movement of the exoskeleton should stay in line with the human arm. Misalignment may cause many problems, such as the external force between the exoskeleton and the arm, the inaccurate control output caused by the error of the measurement position, and decreased safety (Lo and Xie, 2012; Schiele and Helm, 2006; Rocon et al., 2007).

The design of the upper limb exoskeleton is generally based on the movement of the human arm. The number of DOF is defined according to the shoulder joint, elbow joint, and wrist joint as usual, which are 3 DOF for the shoulder joint (flexion/extension, abduction/adduction, and internal/external rotation), 2 DOF for the elbow joint (flexion/extension and pronation/supination), and 2 DOF for the wrist joint (radial/ulnar deviation and flexion/extension). Other existing models of exoskeletons for the human arm include, for instance, ETS-MARSE (Rahman et al., 2015), CADEN-7 (Perry et al., 2007; Perry and Rosen, 2006), and SUEFUL-7 (Gopura et al., 2009). In addition, there are also some researchers that decreased the number of DOF at the elbow joint and wrist joint, such as RETRAINER (Ambrosini et al., 2017), HAMEXO-I (Huang et al., 2014), and some other exoskeletons (Mahdavian et al., 2015; Wong and Mir-Nasiri, 2012; Wu et al., 2014), in order to simplify the design. The DOF at the shoulder joint are retained to ensure the moveability in these designs. However, these articulated exoskeletons still cannot stay in line with human movement. The main reason, as shown in Fig. 1, is that the shoulder abduction of 180^∘ is added to the 60^∘ scapulothoracic (SH) joint upward rotation and the 120^∘ glenohumeral (GH) joint abduction. In addition, the 60^∘ SH upward rotation is depicted as being the summation of the 25^∘ of sternoclavicular (SC) joint elevation and the 35^∘ of acromioclavicular (AC) joint upward rotation. The red arrow in Fig. 1 indicates the change in the axis of the GH joint when the shoulder joint is abducted from 0 to 180^∘. It is the change in the rotation center of the shoulder complex during the movement that causes the misalignment between the exoskeleton and human arm (Neumann, 2013). Therefore, the shoulder joint is a compound joint, and its movement should consider the roles of the clavicle and the scapula in addition to the humerus.

Figure 1Rear view of the right shoulder complex (the shoulder abduction 180^∘; Neumann, 2013).

There are a large number of researchers who have proposed the equivalent kinematic model of the upper limb to find the kinematic characteristics of human arm. Bertomeu-Motos et al. (2018) and Fang et al. (2019) simplified the human arm into a 7 DOF model, connected through two links, namely the upper arm and forearm. However, the model did not consider the contribution of the AC, SH, and SC joints. Eduardo et al. (2018) proposed a biomimetic kinematics model for upper extremity exoskeletons to simulate the contribution of the clavicle movement to the shoulder complex in the coronal plane. The proposed exoskeleton design based on the upper limb kinematic model shows a 17.1 % increase in the motion workspace on the coronal plane with the clavicle compared to non-clavicle designs. The kinematic characteristics in the sagittal plane and horizontal plane were not analyzed. Klopcar and Lenarcic (2006) researched kinematic shoulder complex characteristics on healthy subjects and proposed a model composed of an inner and outer shoulder joint. The inner shoulder joint has two rotations, with the center in the origin of the reference coordinate, and the outer has three rotations, with axes intersecting in the center of the GH joint. The advantage of the model is the inclusion of the shoulder girdle kinematics obtained as functions of the humeral elevation angle. Klopcar and Lenarcic (2005) reported an improved kinematic model of the human arm including the shoulder complex and elbow complex. The kinematic model is appropriate for computing and visualizing the human arm’s reachable workspace. However, the kinematic model did not contain the wrist joint and simplified AC, SH, and SC joints into an universal joint and one slider, which ignored the motion characteristics of human arm too much, such as the scapula extension/retraction (Neumann, 2013). The kinematic model for workspace determination also did not contain the internal/external rotation of the elbow joint. In addition, Laitenberger et al. (2014) refined the upper limb model by means of a forearm closed-loop kinematic chain and personalized joint parameters to quantify kinematics and dynamics of the forearm joint. The wrist joint was simplified into a universal joint (Duprey et al., 2016). In order to understand the kinematic characteristics of the upper limb, the equivalent kinematic model should include not only the GH, elbow, and wrist joints but also the AC, SH, and SC joints.

The challenges of exoskeleton design include motion control and posture determination of its multiple DOF robotic components. In addition, the highly complex mechanical and redundant structures of human joints represent current research objects (Eduardo et al., 2018). The upper limb equivalent kinematic model is a common ground in these two fields, which can provide a reference for the structural design, posture determination, and motion trajectory of the upper limb exoskeleton. This key application promotes the further development of the upper extremity exoskeleton to provide more effective rehabilitation training and motion assistance for stroke patients. Various equivalent kinematic models of the upper limb have been proposed. However, most of the models simplify the DOF of human upper limbs and cannot fully describe the movement of upper limbs, and there are few studies on the application of these models in exoskeleton design. Therefore, the goal of this paper is to propose a new equivalent kinematic model for the human upper limb that will describe the movement characteristics of the human upper limbs as fully as possible and explain how the model can be used to evaluate and improve the design of upper limb exoskeleton rehabilitation robots.

The remainder of this paper is organized as follows. We present, in the next two sections, the proposed method for the equivalent kinematic model of human arm, kinematic analysis, motion space, and evaluation method. In Sect. 4, the results are presented. The discussion is conducted in Sect. 5, and we summarize and conclude this paper in Sect. 6.[…]

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[Abstract] An extended kinematic model for arm rehabilitation training and assessment

Abstract

In the rehabilitation training and assessment of upper limbs, the conventional kinematic model treats the arm as a serial manipulator and maps the rotations in the joint space to movements in the Cartesian space. While this model brings simplicity and convenience, and thus has been overwhelming used, its accuracy is limited, especially for the distal parts of the upper limb that execute dexterous movements.

In this paper, a novel kinematic model of the arm has been proposed, which has been inspired by the biomechanical analysis of the forearm and wrist anatomy. One additional parameter is introduced into the conventional arm model, and then both the forward and inverse kinematic models of five parameters are derived for the motion of upper arm medial/lateral rotation, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. Then, experiments with an advanced haptic interface have been designed and performed to examine the presented arm kinematic model. Data analysis revealed that accuracy and robustness can be significantly improved with the new model.

This extended arm kinematic model will help device development, movement training and assessment of upper limb rehabilitation.

Published in: Advanced Robotics and Mechatronics (ICARM), International Conference on

Source: An extended kinematic model for arm rehabilitation training and assessment – IEEE Xplore Document

[ARTICLE] Quantitative Analysis of the Human Upper-Limp Kinematic Model for Robot-based Rehabilitation Applications – Full Text PDF

Abstract—Upper-limb robotic rehabilitation systems should inform the therapists for their patients status. Such therapy systems must be developed carefully by taking into consideration real life uncertainties that associate with sensor error. In our paper, we describe a system which is composed of a depth camera that tracks the motion of the patients upper limb, and a robotic manipulator that challenges the patient with repetitive exercises. The goal of this study is to propose a motion analysis system that improves the readings of the depth camera, through the use of a kinematic model that describes the motion of the human arm. In our current experimental set-up we are using the Kinect v2 to capture a participant who performs rehabilitation exercises with the Barrett WAM robotic manipulator. Finally, we provide a numerical comparison among the stand alone measurements from the Kinect v2, the estimated motion parameters of our system and the VICON, which we consider as an error-free ground truth apparatus.

I. INTRODUCTION

It is generally accepted that the role of modern physical rehabilitation is essential for the enhancement or restoration of inherent or incidental motor skills disorders. Such disorders may result from a variety of different causes such as amputation, spinal cord injury, musculoskeletal impairment and even brain injury. In light of this phenomenon, robotic rehabilitation augments classical rehabilitation techniques, from the scope that adaptable robotic devices, such as mechanical manipulators, can be used to complement the training routines of a physiatrist or occupational therapist. In this paper we describe and evaluate a novel system that can be used by physicians and therapists to monitor the state of the upper limbs of a patient who performs exercises. The system emphasizes the use of the Microsoft Kinect v2 as opposed to wearable sensors, such as embedded accelerometers, gyroscopes and EMGs. In the following sections we present, analyze and evaluate the proposed system. Specifically, in section 2 we discuss how related studies manage to tackle the problem of pose estimation with vision based or wearable sensors. Furthermore, we discuss how our system exploits the kinematic formulas that originate from the area of robotic mechanics and describe the motion or rigid bodies that can be abstracted via a kinematic chain. We also illustrate an overview of the system, address its core processes and state certain assumptionsthatleadtothesystemsrealization.Asexpected, in the last sections of the paper we detail the physical experimental setup for the assessment of the system and we consider possible avenues for future work.

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