Reward During Arm Training Improves Impairment and Activity After Stroke: A Randomized Controlled Trial.

BACKGROUND: Learning and learning-related neuroplasticity in motor cortex are potential mechanisms mediating recovery of movement abilities after stroke. These mechanisms depend on dopaminergic projections from midbrain that may encode reward information. Likewise, therapist experience confirms the role of feedback/reward for training efficacy after stroke. OBJECTIVE: To test the hypothesis that rehabilitative training can be enhanced by adding performance feedback and monetary rewards. METHODS: This multicentric, assessor-blinded, randomized controlled trial used the ArmeoSenso virtual reality rehabilitation system to train 37 first-ever subacute stroke patients in arm-reaching to moving targets. The rewarded group (n = 19) trained with performance feedback (gameplay) and contingent monetary reward. The control group (n = 18) used the same system without monetary reward and with graphically minimized performance feedback. Primary outcome was the change in the two-dimensional reaching space until the end of the intervention period. Secondary clinical assessments were performed at baseline, after 3 weeks of training (15 1-hour sessions), and at 3 month follow-up. Duration and intensity of the interventions as well as concomitant therapy were comparable between groups. RESULTS: The two-dimensional reaching space showed an overall improvement but no difference between groups. The rewarded group, however, showed significantly greater improvements from baseline in secondary outcomes assessing arm activity (Box and Block Test at post-training: 6.03±2.95, P = .046 and 3 months: 9.66±3.11, P = .003; Wolf Motor Function Test [Score] at 3 months: .63±.22, P = .007) and arm impairment (Fugl-Meyer Upper Extremity at 3 months: 8.22±3.11, P = .011). CONCLUSIONS: Although neutral in its primary outcome, the trial signals a potential facilitating effect of reward on training-mediated improvement of arm paresis. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT02257125).

The influence of skill and task complexity on perception of nested affordances.

This study investigated how skill level and task complexity influence the calibration of perception-action and particularly how close an individual acts relative to his or her maximal action capabilities. Complexity was manipulated between two (Touch, Grasp) and more than two (Removing, Moving Up) nested affordance conditions. For all conditions, we examined whether advanced climbers had greater maximal action capabilities than intermediate climbers or whether they better scaled their action (i.e., acted nearer to their maximal action capabilities) or both. Eleven intermediate and 11 advanced male climbers were first asked to estimate the maximum distance that they could reach a climbing hold. The hold was moved along a slide and fixed once requested by the participant; subsequently, the distance to the starting hold was measured. After each estimation, the participant was required to execute the climbing action. After four estimation-action trials in each of the four conditions, the maximal action capability (i.e., actual maximal reaching distance) was determined. Advanced climbers demonstrated greater actual maximal reaching distances than intermediate climbers for all conditions, but they only estimated greater maximal reaching distances for the more complex conditions, which featured more than two nested affordances. When estimated maximal reaching distances were scaled to actual maximal reaching distances, advanced climbers did not differ from intermediate climbers for any condition, and there were no differences between conditions. Our findings indicate that expertise was a function of greater action capabilities, but not due to the accuracy of calibration.

Magnetometer-Based Drift Correction During Rest inIMU Arm Motion Tracking.

Real-time motion capture of the human arm in the home environment has many usecases, such as video game and therapy applications. The required tracking can be based onoff-the-shelf Inertial Measurement Units (IMUs) with integrated three-axis accelerometers, gyroscopes,and magnetometers. However, this usually requires a homogeneous magnetic field to correctfor orientation drift, which is often not available inside buildings. In this paper, RPMC (RestPose Magnetometer-based drift Correction), a novel method that is robust to long term drift inenvironments with inhomogeneous magnetic fields, is presented. The sensor orientation is estimatedby integrating the angular velocity measured by the gyroscope and correcting drift around the pitchand roll axes with the acceleration information. This commonly leads to short term drift aroundthe gravitational axis. Here, during the calibration phase, the local magnetic field direction for eachsensor, and its orientation relative to the inertial frame, are recorded in a rest pose. It is assumed thatarm movements in free space are exhausting and require regular rest. A set of rules is used to detectwhen the user has returned to the rest pose, to then correct for the drift that has occurred with themagnetometer. Optical validations demonstrated accurate (root mean square error RMS = 6.1), lowlatency (61 ms) tracking of the user's wrist orientation, in real time, for a full hour of arm movements.The reduction in error relative to three alternative methods implemented for comparison was between82.5% and 90.7% for the same movement and environment. Therefore, the proposed arm trackingmethod allows for the correction of orientation drift in an inhomogeneous magnetic field by exploitingthe user's need for frequent rest.

Missing depth cues in virtual reality limit performance and quality of three dimensional reaching movements.

BACKGROUND: Goal-directed reaching for real-world objects by humans is enabled through visual depth cues. In virtual environments, the number and quality of available visual depth cues is limited, which may affect reaching performance and quality of reaching movements. METHODS: We assessed three-dimensional reaching movements in five experimental groups each with ten healthy volunteers. Three groups used a two-dimensional computer screen and two groups used a head-mounted display. The first screen group received the typically recreated visual depth cues, such as aerial and linear perspective, occlusion, shadows, and texture gradients. The second screen group received an abstract minimal rendering lacking those. The third screen group received the cues of the first screen group and absolute depth cues enabled by retinal image size of a known object, which realized with visual renderings of the handheld device and a ghost handheld at the target location. The two head-mounted display groups received the same virtually recreated visual depth cues as the second or the third screen group respectively. Additionally, they could rely on stereopsis and motion parallax due to head-movements. RESULTS AND CONCLUSION: All groups using the screen performed significantly worse than both groups using the head-mounted display in terms of completion time normalized by the straight-line distance to the target. Both groups using the head-mounted display achieved the optimal minimum in number of speed peaks and in hand path ratio, indicating that our subjects performed natural movements when using a head-mounted display. Virtually recreated visual depth cues had a minor impact on reaching performance. Only the screen group with rendered handhelds could outperform the other screen groups. Thus, if reaching performance in virtual environments is in the main scope of a study, we suggest applying a head-mounted display. Otherwise, when two-dimensional screens are used, achievable performance is likely limited by the reduced depth perception and not just by subjects' motor skills.

Does motivation matter in upper-limb rehabilitation after stroke? ArmeoSenso-Reward: study protocol for a randomized controlled trial.

BACKGROUND: Fifty percent of all stroke survivors remain with functional impairments of their upper limb. While there is a need to improve the effectiveness of rehabilitative training, so far no new training approach has proven to be clearly superior to conventional therapy. As training with rewarding feedback has been shown to improve motor learning in humans, it is hypothesized that rehabilitative arm training could be enhanced by rewarding feedback. In this paper, we propose a trial protocol investigating rewards in the form of performance feedback and monetary gains as ways to improve effectiveness of rehabilitative training. METHODS: This multicentric, assessor-blinded, randomized controlled trial uses the ArmeoSenso virtual reality rehabilitation system to train 74 first-ever stroke patients (< 100 days post stroke) to lift their impaired upper limb against gravity and to improve the workspace of the paretic arm. Three sensors are attached to forearm, upper arm, and trunk to track arm movements in three-dimensional space while controlling for trunk compensation. Whole-arm movements serve as input for a therapy game. The reward group (n = 37) will train with performance feedback and contingent monetary reward. The control group (n = 37) uses the same system but without monetary reward and with reduced performance feedback. Primary outcome is the change in the hand workspace in the transversal plane. Standard clinical assessments are used as secondary outcome measures. DISCUSSION: This randomized controlled trial will be the first to directly evaluate the effect of rewarding feedback, including monetary rewards, on the recovery process of the upper limb following stroke. This could pave the way for novel types of interventions with significantly improved treatment benefits, e.g., for conditions that impair reward processing (stroke, Parkinson's disease). TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT02257125 . Registered on 30 September 2014.

Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system.

BACKGROUND: The effect of rehabilitative training after stroke is dose-dependent. Out-patient rehabilitation training is often limited by transport logistics, financial resources and a lack of motivation/compliance. We studied the feasibility of an unsupervised arm therapy for self-directed rehabilitation therapy in patients' homes. METHODS: An open-label, single group study involving eleven patients with hemiparesis due to stroke (27 ± 31.5 months post-stroke) was conducted. The patients trained with an inertial measurement unit (IMU)-based virtual reality system (ArmeoSenso) in their homes for six weeks. The self-selected dose of training with ArmeoSenso was the principal outcome measure whereas the Fugl-Meyer Assessment of the upper extremity (FMA-UE), the Wolf Motor Function Test (WMFT) and IMU-derived kinematic metrics were used to assess arm function, training intensity and trunk movement. Repeated measures one-way ANOVAs were used to assess differences in training duration and clinical scores over time. RESULTS: All subjects were able to use the system independently in their homes and no safety issues were reported. Patients trained on 26.5 ± 11.5 days out of 42 days for a duration of 137 ± 120 min per week. The weekly training duration did not change over the course of six weeks (p = 0.146). The arm function of these patients improved significantly by 4.1 points (p = 0.003) in the FMA-UE. Changes in the WMFT were not significant (p = 0.552). ArmeoSenso based metrics showed an improvement in arm function, a high number of reaching movements (387 per session), and minimal compensatory movements of the trunk while training. CONCLUSIONS: Self-directed home therapy with an IMU-based home therapy system is safe and can provide a high dose of rehabilitative therapy. The assessments integrated into the system allow daily therapy monitoring, difficulty adaptation and detection of maladaptive motor patterns such as trunk movements during reaching. TRIAL REGISTRATION: Unique identifier: NCT02098135 .