Clinical usefulness and validity of robotic measures of reaching movement in hemiparetic stroke patients

Abstract

BackgroundVarious robotic technologies have been developed recently for objective and quantitative assessment of movement. Among them, robotic measures derived from a reaching task in the KINARM Exoskeleton device are characterized by their potential to reveal underlying motor control in reaching movements. The aim of this study was to examine the clinical usefulness and validity of these robot-derived measures in hemiparetic stroke patients.MethodsFifty-six participants with a hemiparetic arm due to chronic stroke were enrolled. The robotic assessment was performed using the Visually Guided Reaching (VGR) task in the KINARM Exoskeleton, which allows free arm movements in the horizontal plane. Twelve parameters were derived based on motor control theory. The following clinical assessments were also administered: the proximal upper limb section in the Fugl-Meyer Assessment (FMA-UE(A)), the proximal upper limb part in the Stroke Impairment Assessment Set (SIAS-KM), the Modified Ashworth Scale for the affected elbow flexor muscles (MAS elbow), and seven proximal upper limb tasks in the Wolf Motor Function Test (WMFT). To explore which robotic measures represent deficits of motor control in the affected arm, the VGR parameters in the paretic arm were compared with those in the non-paretic arm using the Wilcoxon signed rank test. Then, to explore which VGR parameters were related to overall motor control regardless of the paresis, correlations between the paretic and non-paretic arms were examined. Finally, to investigate the relationships between the robotic measures and the clinical scales, correlations between the VGR parameters and clinical scales were investigated. Spearman’s rank correlation coefficients were used for all correlational analyses.ResultsEleven VGR parameters on the paretic side were significantly different from those on the non-paretic side with large effect sizes (|effect size| = 0.76–0.87). Ten VGR parameters correlated significantly with FMA-UE(A) (|r| = 0.32–0.60). Eight VGR parameters also showed significant correlations with SIAS-KM (|r| = 0.42–0.49), MAS elbow (|r| = 0.44–0.48), and the Functional Ability Scale of the WMFT (|r| = 0.52–0.64).ConclusionsThe robot-derived measures could successfully differentiate between the paretic arm and the non-paretic arm and were valid in comparison to the well-established clinical scales.

Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals

“…These results showing moderate correlations between conventional impairment scales and digital health metrics are in general in line with literature, even though the relationships are strongly context-dependent [17,[71][72][73].…”

Effects of robot therapy on upper body kinematics and arm function in persons post stroke: a pilot randomized controlled trial

“…Instrumented analysis is usually performed using quantitative robot-based indexes describing a number of trained and non-trained tasks [28,[40][41][42][43][44]. As summarized in a review by Nordin et al [45], the most common robotbased parameters describing upper limb movement and sensation include the amplitude of robot-generated forces [40,41], temporal and speed metrics [40,43,44,46,47], response latency [46,47], accuracy indexes [40,43,44,46,47], path length and range of motion [41,42,46,47], and movement smoothness [40-44, 46, 47]. The test-retest reliability, the discriminant ability and the concurrent validity of these robot-based indexes have been analyzed in a large number of studies.…”

“…The test-retest reliability, the discriminant ability and the concurrent validity of these robot-based indexes have been analyzed in a large number of studies. Among these studies, those including the largest samples of persons post-stroke [41,[46][47][48][49] found good to excellent reliability [41,48], good discriminant ability [41,47], and moderate to high concurrent validity with clinical scales [41,46,47,49]. The main advantage of the robot-based indexes is that they can be easily obtained during the course of the robotic training, thus providing indications about the gradual progression of the participants' performance [50].…”

High-force Haptic Rehabilitation Robot and Motor Outcomes in Chronic Stroke

“…Robots could transition from intervention to clinically assessing and validating hemiparetic movement [27]. Future robots could incorporate task-oriented training versus gaming, as this subject did, for motivation and interest [28].…”