Robot-Aided Motion Analysis in Neurorehabilitation: Benefits and Challenges

Abstract

In the neurorehabilitation field, robot-aided motion analysis (R-AMA) could be helpful for two main reasons: (1) it allows the registration and monitoring of patients’ motion parameters in a more accurate way than clinical scales (clinical purpose), and (2) the multitude of data produced using R-AMA can be used to build machine learning algorithms, detecting prognostic and predictive factors for better motor outcomes (research purpose). Despite their potential in clinical settings, robotic assessment tools have not gained widespread clinical acceptance. Some barriers remain to their clinical adoption, such as their reliability and validity compared to the existing standardized scales. In this narrative review, we sought to investigate the usefulness of R-AMA systems in patients affected by neurological disorders. We found that the most used R-AMA tools are the Lokomat (an exoskeleton device used for gait and balance rehabilitation) and the Armeo (both Power and Spring, used for the rehabilitation of upper limb impairment). The motion analysis provided by these robotic devices was used to tailor rehabilitation sessions based on the objective quantification of patients’ functional abilities. Spinal cord injury and stroke patients were the most investigated individuals with these common exoskeletons. Research on the use of robotics as an assessment tool should be fostered, taking into account the biomechanical parameters able to predict the accuracy of movements.

The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions

“…On the other hand, the analysis of motion in the neurorehabilitation context allows the instrumental registration and monitoring of patients’ movement parameters ( Table 1 ) in a more objective way than clinical scales (clinical purpose). The multitude of data produced from motion analysis can be used to build machine learning algorithms, detecting prognostic and predictive factors for better motor outcomes (research purpose) [ 5 ].…”

“…These devices may be characterised by an end-effector attached to a set of arms connected by proper joints. Thanks to kinematic calculation methods and integrated measurement devices, the position of the end-effector or the arms can be measured [ 5 ]. In particular, robots integrate measurement devices, called encoders, which record joints angular deviations through optical, mechanical, or magnetic technology.…”

“…During robotic-assisted therapy, the use of kinematic assessment is fundamental to monitor the patient’s progress and to tailor the rehabilitation process to their needs. It is noteworthy that some robotic devices can perform a complete kinematic assessment automatically, as suggested by Bonanno and Calabrò [ 5 ]. In detail, a new category of robotic devices, known as collaborative robots, is growing in popularity in the field of rehabilitation.…”

“…Moreover, the upper limb tasks comprise a wide set of activities, including “non-contact” movements such as gestures, or “contact” movements such as grasping activities [ 7 ]. This assessment can be performed in dedicated environments, like camera-based motion laboratories, or using robot-based measurement systems [ 5 , 8 , 9 ].…”

Can Robotic Feedback and Adaptation Possibilities match Therapeutic Needs? - An Observational Study

“…The Armeo ® Power 1 is one of the promising devices allowing early treatment of motor dysfunction of the upper extremities. Beneficial effects after 20 to 40 sessions of such a robot-assisted therapeutic treatment were demonstrated in several studies [1][2][3][4]. People who receive electro-mechanical and robot-assisted arm training after stroke might improve their activities of daily living, arm function, and arm muscle strength according to a Cochrane review [5].…”