Assessment of Upper-Extremity Joint Angles Using Harmony Exoskeleton

Abstract

The biomechanical complexity of the human shoulder, while critical for functionality, poses a challenge for objective assessment during sensorimotor rehabilitation. With built-in sensing capabilities, robotic exoskeletons have the potential to serve as tools for both intervention and assessment. The bilateral upper-extremity Harmony exoskeleton is capable of full shoulder articulation, forearm flexion-extension, and wrist pronationsupination motions. The goal of this paper is to characterize Harmony's anatomical joint angle tracking accuracy towards its use as an assessment tool. We evaluated the agreement between anatomical joint angles estimated from the robot's sensor data and optical motion capture markers attached to the human user. In 9 healthy participants we examined 6 upper-extremity joint angles, including shoulder girdle angles, across 4 different motions, varying active/passive motion of the user and physical constraint of the trunk. We observed mostly good to excellent levels of agreement between measurement systems with CM Cip>0.65 for shoulder and distal joints, magnitudes of average discrepancies varying from 0.43 • to 16.03 • and width of LoAs ranging between 9.44 • and 41.91 • . Slopes were between 1.03 and 1.43 with r>0.9 for shoulder and distal joints. Regression analysis suggested that discrepancies observed between measured robot and human motions were primarily due to relative motion associated with soft tissue deformation. The results suggest that the Harmony exoskeleton is capable of providing accurate measurements of arm and shoulder joint kinematics. These findings may lead to robot-assisted assessment and intervention of one of the most complex joint structures in the human body.

A unified scheme for the benchmarking of upper limb functions in neurological disorders

“…Technologies and sensors, such as optoelectronic systems, inertial measurement units, or EMG devices, can provide valid, reliable, and sensitive assessment tools exploitable in neurorehabilitation to objectively investigate sensorimotor impairments. Moreover, recently, some robotic devices, such as exoskeletons, are demonstrating their potential to be used not only as a complement to conventional therapy but also to assess sensorimotor capabilities in a more objective way and under repeatable conditions [ 13 , 14 ]. There is now a clear need for guidelines for clinicians and researchers to optimize technology-based assessment since standardized international evidence-based guidelines are missing, especially considering the upper limb district [ 22 , 27 , 28 ].…”

“…Sensor-based approaches, considering, for example, optoelectronic systems, inertial measurement units, or EMG sensors, have been shown to apply to various tasks [ 1 , 7 ]. Recently, robotic devices, such as exoskeletons, have emerged as a novel solution for assessing movement behavior during an intervention, exploiting data acquired by the integrated sensors [ 13 , 14 ]. Robots allow recording and analyzing measures concurrently from multiple joints during a well-controlled and highly repeatable task.…”

Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons

“…Recent studies demonstrated that kinematic data can bring meaningful information to clinical assessment in post-stroke rehabilitation ( Bigoni et al, 2016 ). De Oliveira et al (2021) demonstrated that exoskeleton joint angle data are accurate measurements of arm and shoulder kinematics. However, when the robots are operated in active mode for assessment purposes, transparency is a fundamental feature.…”

Upper limb modeling and motion extraction based on multi-space-fusion

“…However, the simplification of the upper limb to six degrees of freedom (DOFs) and below is inconsistent with the physiological properties of the upper limb. Meanwhile, a sizable research has been conducted for modeling upper-limb motion, including dissecting shoulder motion during the design of the upper-limb exoskeleton (ARMin series 39 – 41 , HARMONY 42 , CLEVERarm 43 , WINDER 44 , ChARMin 45 , etc.) and developing Denavit-Hartenberg based models of upper limb forward and reverse kinematics and dynamics 46 , 47 , hybrid twist-based model of shoulder kinematics 48 , rigid body model describing the kinematics of the scapula relative to the sternum 49 , and a musculoskeletal model of the upper limb 50 – 52 , etc.…”