Robotic Kinematic measures of the arm in chronic Stroke: part 1 - Motor Recovery patterns from tDCS preceding intensive training.

BACKGROUND: Effectiveness of robotic therapy and transcranial direct current stimulation is conventionally assessed with clinical measures. Robotic metrics may be more objective and sensitive for measuring the efficacy of interventions on stroke survivor's motor recovery. This study investigated if robotic metrics detect a difference in outcomes, not seen in clinical measures, in a study of transcranial direct current stimulation (tDCS) preceding robotic therapy. Impact of impairment severity on intervention response was also analyzed to explore optimization of outcomes by targeting patient sub-groups. METHODS: This 2020 study analyzed data from a double-blind, sham-controlled, randomized multi-center trial conducted from 2012 to 2016, including a six-month follow-up. 82 volunteers with single chronic ischemic stroke and right hemiparesis received anodal tDCS or sham stimulation, prior to robotic therapy. Robotic therapy involved 1024 repetitions, alternating shoulder-elbow and wrist robots, for a total of 36 sessions. Shoulder-elbow and wrist kinematic and kinetic metrics were collected at admission, discharge, and follow-up. RESULTS: No difference was detected between the tDCS or sham stimulation groups in the analysis of robotic shoulder-elbow or wrist metrics. Significant improvements in all metrics were found for the combined group analysis. Novel wrist data showed smoothness significantly improved (P < ·001) while submovement number trended down, overlap increased, and interpeak interval decreased. Post-hoc analysis showed only patients with severe impairment demonstrated a significant difference in kinematics, greater for patients receiving sham stimulation. CONCLUSIONS: Robotic data confirmed results of clinical measures, showing intensive robotic therapy is beneficial, but no additional gain from tDCS. Patients with severe impairment did not benefit from the combined intervention. Wrist submovement characteristics showed a delayed pattern of motor recovery compared to the shoulder-elbow, relevant to intensive intervention-related recovery of upper extremity function in chronic stroke. TRIAL REGISTRATION: http://www.clinicaltrials.gov . Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663 .

Robotic Kinematic measures of the arm in chronic Stroke: part 2 - strong correlation with clinical outcome measures.

BACKGROUND: A detailed sensorimotor evaluation is essential in planning effective, individualized therapy post-stroke. Robotic kinematic assay may offer better accuracy and resolution to understand stroke recovery. Here we investigate the added value of distal wrist measurement to a proximal robotic kinematic assay to improve its correlation with clinical upper extremity measures in chronic stroke. Secondly, we compare linear and nonlinear regression models. METHODS: Data was sourced from a multicenter randomized controlled trial conducted from 2012 to 2016, investigating the combined effect of robotic therapy and transcranial direct current stimulation (tDCS). 24 kinematic metrics were derived from 4 shoulder-elbow tasks and 35 metrics from 3 wrist and forearm evaluation tasks. A correlation-based feature selection was performed, keeping only features substantially correlated with the target attribute (R > 0.5.) Nonlinear models took the form of a multilayer perceptron neural network: one hidden layer and one linear output. RESULTS: Shoulder-elbow metrics showed a significant correlation with the Fugl Meyer Assessment (upper extremity, FMA-UE), with a R = 0.82 (P < 0.001) for the linear model and R = 0.88 (P < 0.001) for the nonlinear model. Similarly, a high correlation was found for wrist kinematics and the FMA-UE (R = 0.91 (P < 0.001) and R = 0.92 (P < 0.001) for the linear and nonlinear model respectively). The combined analysis produced a correlation of R = 0.91 (P < 0.001) for the linear model and R = 0.91 (P < 0.001) for the nonlinear model. CONCLUSIONS: Distal wrist kinematics were highly correlated to clinical outcomes, warranting future investigation to explore our nonlinear wrist model with acute or subacute stroke populations. TRIAL REGISTRATION: http://www.clinicaltrials.gov . Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663 .

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

OBJECTIVE: One of the greatest challenges in clinical trial design is dealing with the subjectivity and variability introduced by human raters when measuring clinical end-points. We hypothesized that robotic measures that capture the kinematics of human movements collected longitudinally in patients after stroke would bear a significant relationship to the ordinal clinical scales and potentially lead to the development of more sensitive motor biomarkers that could improve the efficiency and cost of clinical trials. MATERIALS AND METHODS: We used clinical scales and a robotic assay to measure arm movement in 208 patients 7, 14, 21, 30 and 90 days after acute ischemic stroke at two separate clinical sites. The robots are low impedance and low friction interactive devices that precisely measure speed, position and force, so that even a hemiparetic patient can generate a complete measurement profile. These profiles were used to develop predictive models of the clinical assessments employing a combination of artificial ant colonies and neural network ensembles. RESULTS: The resulting models replicated commonly used clinical scales to a cross-validated R2 of 0.73, 0.75, 0.63 and 0.60 for the Fugl-Meyer, Motor Power, NIH stroke and modified Rankin scales, respectively. Moreover, when suitably scaled and combined, the robotic measures demonstrated a significant increase in effect size from day 7 to 90 over historical data (1.47 versus 0.67). DISCUSSION AND CONCLUSION: These results suggest that it is possible to derive surrogate biomarkers that can significantly reduce the sample size required to power future stroke clinical trials.

Evaluation of the enhanced upper limb therapy programme within the Robot-Assisted Training for the Upper Limb after Stroke trial: descriptive analysis of intervention fidelity, goal selection and goal achievement.

OBJECTIVE: To report the fidelity of the enhanced upper limb therapy programme within the Robot-Assisted Training for the Upper Limb after stroke (RATULS) randomized controlled trial, the types of goals selected and the proportion of goals achieved. DESIGN: Descriptive analysis of data on fidelity, goal selection and achievement from an intervention group within a randomized controlled trial. SETTING: Out-patient stroke rehabilitation within four UK NHS centres. SUBJECTS: 259 participants with moderate-severe upper limb activity limitation (Action Research Arm Test 0-39) between one week and five years post first stroke. INTERVENTION: The enhanced upper limb therapy programme aimed to provide 36 one-hour sessions, including 45 minutes of face-to-face therapy focusing on personal goals, over 12 weeks. RESULTS: 7877/9324 (84%) sessions were attended; a median of 34 [IQR 29-36] per participant. A median of 127 [IQR 70-190] repetitions were achieved per participant per session attended. Based upon the Canadian Occupational Performance Measure, goal categories were: self-care 1449/2664 (54%); productivity 374/2664 (14%); leisure 180/2664 (7%) and 'other' 661/2664 (25%). For the 2051/2664 goals for which data were available, 1287 (51%) were achieved, ranging between 27% by participants more than 12 months post stroke with baseline Action Research Arm Test scores 0-7, and 88% by those less than three months after stroke with scores 8-19. CONCLUSIONS: Intervention fidelity was high. Goals relating to self-care were most commonly selected. The proportion of goals achieved varied, depending on time post stroke and baseline arm activity limitation.

Identification of Gait Events in Healthy Subjects and With Parkinson's Disease Using Inertial Sensors: An Adaptive Unsupervised Learning Approach.

Automatic identification of gait events is an essential component of the control scheme of assistive robotic devices. Many available techniques suffer limitations for real-time implementations and in guaranteeing high performances when identifying events in subjects with gait impairments. Machine learning algorithms offer a solution by enabling the training of different models to represent the gait patterns of different subjects. Here our aim is twofold: to remove the need for training stages using unsupervised learning, and to modify the parameters according to the changes within a walking trial using adaptive procedures. We developed two adaptive unsupervised algorithms for real-time detection of four gait events, using only signals from two single-IMU foot-mounted wearable devices. We evaluated the algorithms using data collected from five healthy adults and seven subjects with Parkinson's disease (PD) walking overground and on a treadmill. Both algorithms obtained high performance in terms of accuracy ( F1 -score ≥ 0.95 for both groups), and timing agreement using a force-sensitive resistors as reference (mean absolute differences of 66 ± 53 msec for the healthy group, and 58 ± 63 msec for the PD group). The proposed algorithms demonstrated the potential to learn optimal parameters for a particular participant and for detecting gait events without additional sensors, external labeling, or long training stages.

Robot-assisted training compared with an enhanced upper limb therapy programme and with usual care for upper limb functional limitation after stroke: the RATULS three-group RCT.

BACKGROUND: Loss of arm function is common after stroke. Robot-assisted training may improve arm outcomes. OBJECTIVE: The objectives were to determine the clinical effectiveness and cost-effectiveness of robot-assisted training, compared with an enhanced upper limb therapy programme and with usual care. DESIGN: This was a pragmatic, observer-blind, multicentre randomised controlled trial with embedded health economic and process evaluations. SETTING: The trial was set in four NHS trial centres. PARTICIPANTS: Patients with moderate or severe upper limb functional limitation, between 1 week and 5 years following first stroke, were recruited. INTERVENTIONS: Robot-assisted training using the Massachusetts Institute of Technology-Manus robotic gym system (InMotion commercial version, Interactive Motion Technologies, Inc., Watertown, MA, USA), an enhanced upper limb therapy programme comprising repetitive functional task practice, and usual care. MAIN OUTCOME MEASURES: The primary outcome was upper limb functional recovery 'success' (assessed using the Action Research Arm Test) at 3 months. Secondary outcomes at 3 and 6 months were the Action Research Arm Test results, upper limb impairment (measured using the Fugl-Meyer Assessment), activities of daily living (measured using the Barthel Activities of Daily Living Index), quality of life (measured using the Stroke Impact Scale), resource use costs and quality-adjusted life-years. RESULTS: A total of 770 participants were randomised (robot-assisted training, n = 257; enhanced upper limb therapy, n = 259; usual care, n = 254). Upper limb functional recovery 'success' was achieved in the robot-assisted training [103/232 (44%)], enhanced upper limb therapy [118/234 (50%)] and usual care groups [85/203 (42%)]. These differences were not statistically significant; the adjusted odds ratios were as follows: robot-assisted training versus usual care, 1.2 (98.33% confidence interval 0.7 to 2.0); enhanced upper limb therapy versus usual care, 1.5 (98.33% confidence interval 0.9 to 2.5); and robot-assisted training versus enhanced upper limb therapy, 0.8 (98.33% confidence interval 0.5 to 1.3). The robot-assisted training group had less upper limb impairment (as measured by the Fugl-Meyer Assessment motor subscale) than the usual care group at 3 and 6 months. The enhanced upper limb therapy group had less upper limb impairment (as measured by the Fugl-Meyer Assessment motor subscale), better mobility (as measured by the Stroke Impact Scale mobility domain) and better performance in activities of daily living (as measured by the Stroke Impact Scale activities of daily living domain) than the usual care group, at 3 months. The robot-assisted training group performed less well in activities of daily living (as measured by the Stroke Impact Scale activities of daily living domain) than the enhanced upper limb therapy group at 3 months. No other differences were clinically important and statistically significant. Participants found the robot-assisted training and the enhanced upper limb therapy group programmes acceptable. Neither intervention, as provided in this trial, was cost-effective at current National Institute for Health and Care Excellence willingness-to-pay thresholds for a quality-adjusted life-year. CONCLUSIONS: Robot-assisted training did not improve upper limb function compared with usual care. Although robot-assisted training improved upper limb impairment, this did not translate into improvements in other outcomes. Enhanced upper limb therapy resulted in potentially important improvements on upper limb impairment, in performance of activities of daily living, and in mobility. Neither intervention was cost-effective. FUTURE WORK: Further research is needed to find ways to translate the improvements in upper limb impairment seen with robot-assisted training into improvements in upper limb function and activities of daily living. Innovations to make rehabilitation programmes more cost-effective are required. LIMITATIONS: Pragmatic inclusion criteria led to the recruitment of some participants with little prospect of recovery. The attrition rate was higher in the usual care group than in the robot-assisted training or enhanced upper limb therapy groups, and differential attrition is a potential source of bias. Obtaining accurate information about the usual care that participants were receiving was a challenge. TRIAL REGISTRATION: Current Controlled Trials ISRCTN69371850. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 54. See the NIHR Journals Library website for further project information.

Many people who have arm weakness following a stroke feel that insufficient attention is paid by rehabilitation services to recovery of their arm. Unfortunately, it is currently unclear how best to provide rehabilitation to optimise recovery, but robot-assisted training and therapy programmes that focus on practising functional tasks are promising and require further evaluation. The Robot-Assisted Training for the Upper Limb after Stroke (RATULS) trial evaluated three approaches to rehabilitation for people with moderate or severe difficulty using their arm. These approaches were robot-assisted training using the Massachusetts Institute of Technology-Manus robotic gym system (InMotion commercial version, Interactive Motion Technologies, Inc., Watertown, MA, USA), an enhanced upper limb therapy programme based on repetitive practice of functional tasks and usual care. Robot-assisted training and the enhanced upper limb therapy programme were provided in an outpatient setting for 45 minutes per session, three times per week, for 12 weeks, in addition to usual care. The Massachusetts Institute of Technology-Manus robotic gym system was selected as it was felt to be the best available technology. The participant sits at a table, places their affected arm onto the Massachusetts Institute of Technology-Manus arm support and attempts to move their arm to play a game on the computer screen. Movements are assisted by the Massachusetts Institute of Technology-Manus if the patient cannot perform the movements themselves. The results of the RATULS trial show that robot-assisted training did not result in additional improvement in stroke survivors' arm use when compared with the enhanced upper limb therapy programme or usual care. Stroke survivors who received enhanced upper limb therapy experienced meaningful improvements in undertaking activities of daily living, when compared with those participants who received either robot-assisted training or usual care. Participants who received enhanced upper limb therapy also experienced benefits in their mobility, compared with usual care participants. Participants and therapists found both therapies acceptable, and described various benefits. A health economic analysis found that neither robot-assisted training nor the enhanced upper limb therapy programme was a cost-effective treatment for the NHS.

Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice.

Background. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor improvement has been shown at the joints trained, but generalization to real-world function has not been profound. Objective. To investigate the efficacy of robot-assisted therapy combined with therapist-assisted task training versus robot-assisted therapy alone on motor outcomes and use in participants with moderate to severe chronic stroke-related arm disability. Methods. This was a single-blind randomized controlled trial of two 12-week robot-assisted interventions; 45 participants were stratified by Fugl-Meyer (FMA) impairment (mean 21 ± 1.36) to 60 minutes of robot therapy (RT; n = 22) or 45 minutes of RT combined with 15 minutes therapist-assisted transition-to-task training (TTT; n = 23). The primary outcome was the mean FMA change at week 12 using a linear mixed-model analysis. A subanalysis included the Wolf Motor Function Test (WMFT) and Stroke Impact Scale (SIS), with significance P <.05. Results. There was no significant 12-week difference in FMA change between groups, and mean FMA gains were 2.87 ± 0.70 and 4.81 ± 0.68 for RT and TTT, respectively. TTT had greater 12-week secondary outcome improvements in the log WMFT (-0.52 ± 0.06 vs -0.18 ± 0.06; P = .01) and SIS hand (20.52 ± 2.94 vs 8.27 ± 3.03; P = .03). Conclusion. Chronic UE motor deficits are responsive to intensive robot-assisted therapy of 45 or 60 minutes per session duration. The replacement of part of the robotic training with nonrobotic tasks did not reduce treatment effect and may benefit stroke-affected hand use and motor task performance.

Robot assisted training for the upper limb after stroke (RATULS): a multicentre randomised controlled trial.

BACKGROUND: Loss of arm function is a common problem after stroke. Robot-assisted training might improve arm function and activities of daily living. We compared the clinical effectiveness of robot-assisted training using the MIT-Manus robotic gym with an enhanced upper limb therapy (EULT) programme based on repetitive functional task practice and with usual care. METHODS: RATULS was a pragmatic, multicentre, randomised controlled trial done at four UK centres. Stroke patients aged at least 18 years with moderate or severe upper limb functional limitation, between 1 week and 5 years after their first stroke, were randomly assigned (1:1:1) to receive robot-assisted training, EULT, or usual care. Robot-assisted training and EULT were provided for 45 min, three times per week for 12 weeks. Randomisation was internet-based using permuted block sequences. Treatment allocation was masked from outcome assessors but not from participants or therapists. The primary outcome was upper limb function success (defined using the Action Research Arm Test [ARAT]) at 3 months. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN69371850. FINDINGS: Between April 14, 2014, and April 30, 2018, 770 participants were enrolled and randomly assigned to either robot-assisted training (n=257), EULT (n=259), or usual care (n=254). The primary outcome of ARAT success was achieved by 103 (44%) of 232 patients in the robot-assisted training group, 118 (50%) of 234 in the EULT group, and 85 (42%) of 203 in the usual care group. Compared with usual care, robot-assisted training (adjusted odds ratio [aOR] 1·17 [98·3% CI 0·70-1·96]) and EULT (aOR 1·51 [0·90-2·51]) did not improve upper limb function; the effects of robot-assisted training did not differ from EULT (aOR 0·78 [0·48-1·27]). More participants in the robot-assisted training group (39 [15%] of 257) and EULT group (33 [13%] of 259) had serious adverse events than in the usual care group (20 [8%] of 254), but none were attributable to the intervention. INTERPRETATION: Robot-assisted training and EULT did not improve upper limb function after stroke compared with usual care for patients with moderate or severe upper limb functional limitation. These results do not support the use of robot-assisted training as provided in this trial in routine clinical practice. FUNDING: National Institute for Health Research Health Technology Assessment Programme.

Clinical improvement with intensive robot-assisted arm training in chronic stroke is unchanged by supplementary tDCS.

BACKGROUND: Intensive robot-assisted arm training in the chronic phase of stroke recovery can lead to clinical improvement. Combinatorial therapeutic approaches are sought to further optimize stroke recovery. Transcranial direct current stimulation (tDCS) is one candidate to combine with robotic training, as transient increases in excitability and improvements in motor behavior have separately been reported. OBJECTIVE: To determine whether tDCS, delivered prior to robotic training, could augment clinical improvement. METHODS: We conducted a dual-site, randomized controlled trial in 82 chronic ischemic stroke patients (inclusion > 6 m post-injury, dominant hemisphere, first stroke; residual hemiparesis) who were split into two groups to receive tDCS (M1-SO montage, anode ipsilesional, 5×7 cm electrodes, 2 mA, 20 mins) or sham tDCS, prior to robotic upper-limb training (12 weeks; 36 sessions; shoulder-elbow robot or wrist robot on alternating sessions). The primary end-point was taken after 12 weeks of training, and assessed with the Upper Extremity Fugl-Meyer impairment scale (FM). Corticomotor conduction was assessed with transcranial magnetic stimulation (TMS). RESULTS: For the combined group (n = 82; post-training) robotic training increased the FM by 7.36 points compared to baseline (p < 0.0001). There was no difference in the FM increase between the tDCS and sham groups (6.97 and 7.73 respectively, p = 0.46). In both groups, clinically meaningful improvement (≥5 points) from baseline was evident in the majority of patients (56/77), was sustained six months later (54/72), and could be attained in severe, moderate and mild baseline hemiparesis. Clinical improvement was associated with increased excitability in the affected hemisphere as assessed by resting motor threshold (pre-post p = 0.029; pre-post 6 months p = 0.029), but not with threshold-adjusted assessment of MEP amplitude (pre-post p = 0.09; pre-post 6 months p = 0.15). Participants with motor evoked potentials were more likely to improve clinically than those without (17/18, 94%, versus 39/59, 66%, p = 0.018). CONCLUSIONS: Our study confirms the benefit of intensive robot-assisted training in stroke recovery, and indicates that conventional tDCS does not confer further advantage to robotic training. We also showed that corticospinal integrity, as assessed by TMS, is a predictor of clinically meaningful response to intensive arm therapy in chronic stroke.

MIT-Skywalker: On the use of a markerless system.

This paper describes our efforts to employ the Microsoft Kinect as a low cost vision control system for the MIT-Skywalker, a robotic gait rehabilitation device. The Kinect enables an alternative markerless solution to control the MIT-Skywalker and allows a more user-friendly set-up. A study involving eight healthy subjects and two stroke survivors using the MIT-Skywalker device demonstrates the advantages and challenges of this new proposed approach.

MIT-Skywalker: Evaluating comfort of bicycle/saddle seat.

The MIT-Skywalker is a robotic device developed for the rehabilitation of gait and balance after a neurological injury. This device has been designed based on the concept of a passive walker and provides three distinct training modes: discrete movement, rhythmic movement, and balance training. In this paper, we present our efforts to evaluate the comfort of a bicycle/saddle seat design for the system's novel actuated body weight support device. We employed different bicycle and saddle seats and evaluated comfort using objective and subjective measures. Here we will summarize the results obtained from a study of fifteen healthy subjects and one stroke patient that led to the selection of a saddle seat design for the MIT-Skywalker.

Compensating for telecommunication delays during robotic telerehabilitation.

Rehabilitation robotic systems may afford better care and telerehabilitation may extend the use and benefits of robotic therapy to the home. Data transmissions over distance are bound by intrinsic communication delays which can be significant enough to deem the activity unfeasible. Here we describe an approach that combines unilateral robotic telerehabilitation and serious games. This approach has a modular and distributed design that permits different types of robots to interact without substantial code changes. We demonstrate the approach through an online multiplayer game. Two users can remotely interact with each other with no force exchanges, while a smoothing and prediction algorithm compensates motions for the delay in the Internet connection. We demonstrate that this approach can successfully compensate for data transmission delays, even when testing between the United States and Brazil. This paper presents the initial experimental results, which highlight the performance degradation with increasing delays as well as improvements provided by the proposed algorithm, and discusses planned future developments.

Task-specific ankle robotics gait training after stroke: a randomized pilot study.

BACKGROUND: An unsettled question in the use of robotics for post-stroke gait rehabilitation is whether task-specific locomotor training is more effective than targeting individual joint impairments to improve walking function. The paretic ankle is implicated in gait instability and fall risk, but is difficult to therapeutically isolate and refractory to recovery. We hypothesize that in chronic stroke, treadmill-integrated ankle robotics training is more effective to improve gait function than robotics focused on paretic ankle impairments. FINDINGS: Participants with chronic hemiparetic gait were randomized to either six weeks of treadmill-integrated ankle robotics (n = 14) or dose-matched seated ankle robotics (n = 12) videogame training. Selected gait measures were collected at baseline, post-training, and six-week retention. Friedman, and Wilcoxon Sign Rank and Fisher's exact tests evaluated within and between group differences across time, respectively. Six weeks post-training, treadmill robotics proved more effective than seated robotics to increase walking velocity, paretic single support, paretic push-off impulse, and active dorsiflexion range of motion. Treadmill robotics durably improved gait dorsiflexion swing angle leading 6/7 initially requiring ankle braces to self-discarded them, while their unassisted paretic heel-first contacts increased from 44 % to 99.6 %, versus no change in assistive device usage (0/9) following seated robotics. CONCLUSIONS: Treadmill-integrated, but not seated ankle robotics training, durably improves gait biomechanics, reversing foot drop, restoring walking propulsion, and establishing safer foot landing in chronic stroke that may reduce reliance on assistive devices. These findings support a task-specific approach integrating adaptive ankle robotics with locomotor training to optimize mobility recovery. CLINICAL TRIAL IDENTIFIER: NCT01337960. https://clinicaltrials.gov/ct2/show/NCT01337960?term=NCT01337960&rank=1.

Movement-generated afference paired with transcranial magnetic stimulation: an associative stimulation paradigm.

BACKGROUND: A peripheral nerve stimulus can enhance or suppress the evoked response to transcranial magnetic stimulation (TMS) depending on the latency of the preceding peripheral nerve stimulation (PNS) pulse. Similarly, somatosensory afference from the passively moving limb can transiently alter corticomotor excitability, in a phase-dependent manner. The repeated association of PNS with TMS is known to modulate corticomotor excitability; however, it is unknown whether repeated passive-movement associative stimulation (MAS) has similar effects. METHODS: In a proof-of-principal study, using a cross-over design, seven healthy subjects received in separate sessions: (1) TMS (120% of the resting motor threshold-RMT, optimal site for Flexor Carpi Radialis) with muscle at rest; (2) TMS paired with cyclic passive movement during extension cyclic passive movement (400 pairs, 1 Hz), with the intervention order randomly assigned. Normality was tested using the Kolmogorov-Smirnov test, then compared to pre-intervention baseline using repeated measures ANOVA with a Dunnet multiple comparisons test. RESULTS: MAS led to a progressive and significant decrease in the motor evoked potential (MEP) amplitude over the intervention (R(2) = 0.6665, P < 0.0001), which was not evident with TMS alone (R(2) = 0.0068, P = 0.641). Post-intervention excitability reduction, only present with MAS intervention, remained for 20 min (0-10 min = 68.2 ± 4.9%, P < 0.05; 10-20 min = 73.3 ± 9.7%, P < 0.05). CONCLUSION: The association of somatosensory afference from the moving limb with TMS over primary motor cortex in healthy subjects can be used to modulate corticomotor excitability, and may have therapeutic implications.

Spatiotemporal dynamics of online motor correction processing revealed by high-density electroencephalography.

The ability to control online motor corrections is key to dealing with unexpected changes arising in the environment with which we interact. How the CNS controls online motor corrections is poorly understood, but evidence has accumulated in favor of a submovement-based model in which apparently continuous movement is segmented into distinct submovements. Although most studies have focused on submovements' kinematic features, direct links with the underlying neural dynamics have not been extensively explored. This study sought to identify an electroencephalographic signature of submovements. We elicited kinematic submovements using a double-step displacement paradigm. Participants moved their wrist toward a target whose direction could shift mid-movement with a 50% probability. Movement kinematics and cortical activity were concurrently recorded with a low-friction robotic device and high-density electroencephalography. Analysis of spatiotemporal dynamics of brain activation and its correlation with movement kinematics showed that the production of each kinematic submovement was accompanied by (1) stereotyped topographic scalp maps and (2) frontoparietal ERPs time-locked to submovements. Positive ERP peaks from frontocentral areas contralateral to the moving wrist preceded kinematic submovement peaks by 220-250 msec and were followed by positive ERP peaks from contralateral parietal areas (140-250 msec latency, 0-80 msec before submovement peaks). Moreover, individual subject variability in the latency of frontoparietal ERP components following the target shift significantly predicted variability in the latency of the corrective submovement. Our results are in concordance with evidence for the intermittent nature of continuous movement and elucidate the timing and role of frontoparietal activations in the generation and control of corrective submovements.

Robotic measurement of arm movements after stroke establishes biomarkers of motor recovery.

BACKGROUND AND PURPOSE: Because robotic devices record the kinematics and kinetics of human movements with high resolution, we hypothesized that robotic measures collected longitudinally in patients after stroke would bear a significant relationship to standard clinical outcome measures and, therefore, might provide superior biomarkers. METHODS: In patients with moderate-to-severe acute ischemic stroke, we used clinical scales and robotic devices to measure arm movement 7, 14, 21, 30, and 90 days after the event at 2 clinical sites. The robots are interactive devices that measure speed, position, and force so that calculated kinematic and kinetic parameters could be compared with clinical assessments. RESULTS: Among 208 patients, robotic measures predicted well the clinical measures (cross-validated R(2) of modified Rankin scale=0.60; National Institutes of Health Stroke Scale=0.63; Fugl-Meyer=0.73; Motor Power=0.75). When suitably scaled and combined by an artificial neural network, the robotic measures demonstrated greater sensitivity in measuring the recovery of patients from day 7 to day 90 (increased standardized effect=1.47). CONCLUSIONS: These results demonstrate that robotic measures of motor performance will more than adequately capture outcome, and the altered effect size will reduce the required sample size. Reducing sample size will likely improve study efficiency.

Changes in passive ankle stiffness and its effects on gait function in people with chronic stroke.

Mechanical impedance of the ankle is known to influence key aspects of ankle function. We investigated the effects of robot-assisted ankle training in people with chronic stroke on the paretic ankle's passive stiffness and its relationship to overground gait function. Over 6 wk, eight participants with residual hemiparetic deficits engaged in a visuomotor task while seated that required dorsiflexion (DF) or plantar flexion (PF) of their paretic ankle with an ankle robot ("anklebot") assisting as needed. Passive ankle stiffness (PAS) was measured in both the trained sagittal and untrained frontal planes. After 6 wk, the PAS decreased in both DF and PF and reverted into the variability of age-matched controls in DF. Changes in PF PAS correlated strongly with gains in paretic step lengths (Spearman rho = -0.88, p = 0.03) and paretic stride lengths (Spearman rho = -0.82, p = 0.05) during independent floor walking. Moreover, baseline PF PAS were correlated with gains in paretic step lengths (Spearman rho = 0.94, p = 0.01), paretic stride lengths (Spearman rho = 0.83, p = 0.05), and single-support stance duration (Spearman rho = 0.94, p = 0.01); and baseline eversion PAS were correlated with gains in cadence (Spearman rho = -0.88, p = 0.03). These findings suggest that ankle robot-assisted, visuomotor-based, isolated ankle training has a positive effect on paretic ankle PAS that strongly influences key measures of gait function.

The passive stiffness of the wrist and forearm.

Because wrist rotation dynamics are dominated by stiffness (Charles SK, Hogan N. J Biomech 44: 614-621, 2011), understanding how humans plan and execute coordinated wrist rotations requires knowledge of the stiffness characteristics of the wrist joint. In the past, the passive stiffness of the wrist joint has been measured in 1 degree of freedom (DOF). Although these 1-DOF measurements inform us of the dynamics the neuromuscular system must overcome to rotate the wrist in pure flexion-extension (FE) or pure radial-ulnar deviation (RUD), the wrist rarely rotates in pure FE or RUD. Instead, understanding natural wrist rotations requires knowledge of wrist stiffness in combinations of FE and RUD. The purpose of this report is to present measurements of passive wrist stiffness throughout the space spanned by FE and RUD. Using a rehabilitation robot designed for the wrist and forearm, we measured the passive stiffness of the wrist joint in 10 subjects in FE, RUD, and combinations. For comparison, we measured the passive stiffness of the forearm (in pronation-supination), as well. Our measurements in pure FE and RUD agreed well with previous 1-DOF measurements. We have linearized the 2-DOF stiffness measurements and present them in the form of stiffness ellipses and as stiffness matrices useful for modeling wrist rotation dynamics. We found that passive wrist stiffness was anisotropic, with greater stiffness in RUD than in FE. We also found that passive wrist stiffness did not align with the anatomical axes of the wrist; the major and minor axes of the stiffness ellipse were rotated with respect to the FE and RUD axes by ∼20°. The direction of least stiffness was between ulnar flexion and radial extension, a direction used in many natural movements (known as the "dart-thrower's motion"), suggesting that the nervous system may take advantage of the direction of least stiffness for common wrist rotations.

Motor learning characterizes habilitation of children with hemiplegic cerebral palsy.

BACKGROUND: This study tested in children with cerebral palsy (CP) whether motor habilitation resembles motor learning. METHODS: Twelve children with hemiplegic CP ages 5 to 12 years with moderate to severe motor impairments underwent a 16-session robot-mediated planar therapy program to improve upper limb reach, with a focus on shoulder and elbow movements. Participants were trained to execute point-to-point movements (with robot assistance) with the affected arm and were evaluated (without robot assistance) in trained (point-to-point) and untrained (circle-drawing) conditions. Outcomes were measured at baseline, midpoint, immediately after the program, and 1 month postcompletion. Outcome measures were the Fugl-Meyer (FM), Quality of Upper Extremity Skills Test (QUEST), and Modified Ashworth Scale (MAS) scores; parent questionnaire; and robot-based kinematic metrics. To assess whether learning best characterizes motor habilitation in CP, the authors quantified (a) improvement on trained tasks at completion of training (acquisition) and 1 month following completion (retention) and (b) quantified generalization of improvement to untrained tasks. RESULTS: After robotic intervention, the authors found significant gains in the FM, QUEST, and parent questionnaire. Robot-based evaluations demonstrated significant improvement in trained movements and that improvement was sustained at follow-up. Furthermore, children improved their performance in untrained movements indicating generalization. CONCLUSIONS: Motor habilitation in CP exhibits some traits of motor learning. Optimal treatment may not require an extensive repertoire of tasks but rather a select set to promote generalization.

Effect of gravity on robot-assisted motor training after chronic stroke: a randomized trial.

OBJECTIVES: To determine the efficacy of 2 distinct 6-week robot-assisted reaching programs compared with an intensive conventional arm exercise program (ICAE) for chronic, stroke-related upper-extremity (UE) impairment. To examine whether the addition of robot-assisted training out of the horizontal plane leads to improved outcomes. DESIGN: Randomized controlled trial, single-blinded, with 12-week follow-up. SETTING: Research setting in a large medical center. PARTICIPANTS: Adults (N=62) with chronic, stroke-related arm weakness stratified by impairment severity using baseline UE motor assessments. INTERVENTIONS: Sixty minutes, 3 times a week for 6 weeks of robot-assisted planar reaching (gravity compensated), combined planar with vertical robot-assisted reaching, or intensive conventional arm exercise program. MAIN OUTCOME MEASURE: UE Fugl-Meyer Assessment (FMA) mean change from baseline to final training. RESULTS: All groups showed modest gains in the FMA from baseline to final with no significant between group differences. Most change occurred in the planar robot group (mean change ± SD, 2.94 ± 0.77; 95% confidence interval [CI], 1.40-4.47). Participants with greater motor impairment (n=41) demonstrated a larger difference in response (mean change ± SD, 2.29 ± 0.72; 95% CI, 0.85-3.72) for planar robot-assisted exercise compared with the intensive conventional arm exercise program (mean change ± SD, 0.43 ± 0.72; 95% CI, -1.00 to 1.86). CONCLUSIONS: Chronic UE deficits because of stroke are responsive to intensive motor task training. However, training outside the horizontal plane in a gravity present environment using a combination of vertical with planar robots was not superior to training with the planar robot alone.