Kinematic Parameters for Tracking Patient Progress during Upper Limb Robot-Assisted Rehabilitation: An Observational Study on Subacute Stroke Subjects

Abstract

Background Upper limb robot-assisted therapy (RT) provides intensive, repetitive, and task-specific treatment, and its efficacy for stroke survivors is well established in literature. Biomechanical data from robotic devices has been widely employed for patient's assessment, but rarely it has been analysed for tracking patient progress during RT. The goal of this retrospective study is to analyse built-in kinematic data registered by a planar end-effector robot for assessing the time course of motor recovery and patient's workspace exploration skills. A comparison of subjects having mild and severe motor impairment has been also conducted. For that purpose, kinematic data recorded by a planar end-effector robot have been processed for investigating how motor performance in executing point-to-point trajectories with different directions changes during RT. Methods Observational retrospective study of 68 subacute stroke patients who conducted 20 daily sessions of upper limb RT with the InMotion 2.0 (Bionik Laboratories, USA): planar point-to-point reaching tasks with an “assist as needed” strategy. The following kinematic parameters (KPs) were computed for each subject and for each point-to-point trajectory executed during RT: movement accuracy, movement speed, number of peak speed, and task completion time. The Wilcoxon signed-rank tests were used with clinical outcomes. the Friedman test and post hoc Conover's test (Bonferroni's correction) were applied to KPs. A secondary data analysis has been conducted by comparing patients having different severities of motor impairment. The level of significance was set at p value < 0.05. Results At the RT onset, the movements were less accurate and smoothed, and showed higher times of execution than those executed at the end of treatment. The analysis of the time course of KPs highlighted that RT seems to improve the motor function mainly in the first sessions of treatment: most KPs show significant intersession differences during the first 5/10 sessions. Afterwards, no further significant variations occurred. The ability to perform movements away from the body and from the hemiparetic side remains more challenging. The results obtained from the data stratification show significant differences between subjects with mild and severe motor impairment. Conclusion Significant improvements in motor performance were registered during the time course of upper limb RT in subacute stroke patients. The outcomes depend on movement direction and motor impairment and pave the way to optimize healthcare resources and to design patient-tailored rehabilitative protocols.

Accurate prediction of clinical stroke scales and improved biomarkers of motor impairment from robotic measurements

“…We chose to investigate the use of robotic systems because of their growing adoption in stroke wards to deliver therapy. However, many robotic devices, such as the InMotion Arm [3], afford not only the possibility to promote faster and better rehabilitation, but also the potential to track an individual's progress [4][5][6].…”

Sensor Network for Analyzing Upper Body Strategies in Parkinson’s Disease versus Normative Kinematic Patterns

“…People who undergo rehabilitation treatments of the upper limb are generally assessed using functional and motor scales [ 1 , 2 , 3 , 4 ] in order to characterize the efficacy of a specific therapy or the evolution of the disease over time. The performance related to dexterity, strength, upper limb function, and Activities of Daily Living (ADLs) is typically evaluated via a set of validated clinical tests [ 5 , 6 ].…”

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

“…Traditionally, the effects of ulRT are reported by using standardized clinical assessments [such as, the upper extremity subscale of the Fugl-Meyer Assessment (15), the upper limb Motricity Index (16,17), or the Action Research Arm Test (18)] and biomechanical measurements of upper limb movements (19)(20)(21)(22). Specifically, a multiplicity of kinematic parameters has been applied for upper limb evaluations, such as movement accuracy, speed, and smoothness, and some of them have been correlated to the clinical outcome measures (21,23).…”

“…Specifically, a multiplicity of kinematic parameters has been applied for upper limb evaluations, such as movement accuracy, speed, and smoothness, and some of them have been correlated to the clinical outcome measures (21,23). Interestingly, a number of publications analyzed the Robot Measured Kinematic (RMK) data (i.e., the trajectories for movements) registered by the robot (20,(24)(25)(26)(27)(28) assessing the biomechanical changes induced by ulRT, and thus the patient progress, in terms of motor control and coordination. Moreover, these robotic measurements allow monitoring the time course of motor recovery during ulRT (24)(25)(26)(27), showing that it is movement direction-dependent (20,28).…”

“…Interestingly, a number of publications analyzed the Robot Measured Kinematic (RMK) data (i.e., the trajectories for movements) registered by the robot (20,(24)(25)(26)(27)(28) assessing the biomechanical changes induced by ulRT, and thus the patient progress, in terms of motor control and coordination. Moreover, these robotic measurements allow monitoring the time course of motor recovery during ulRT (24)(25)(26)(27), showing that it is movement direction-dependent (20,28). The robot-measured data have been processed not only for assessing the efficacy of ulRT, but also for predicting the clinical scales (29)(30)(31).…”