Dataset Information

Robot-assisted training of the kinesthetic sense: enhancing proprioception after stroke.

ABSTRACT: Proprioception has a crucial role in promoting or hindering motor learning. In particular, an intact position sense strongly correlates with the chances of recovery after stroke. A great majority of neurological patients present both motor dysfunctions and impairments in kinesthesia, but traditional robot and virtual reality training techniques focus either in recovering motor functions or in assessing proprioceptive deficits. An open challenge is to implement effective and reliable tests and training protocols for proprioception that go beyond the mere position sense evaluation and exploit the intrinsic bidirectionality of the kinesthetic sense, which refers to both sense of position and sense of movement. Modulated haptic interaction has a leading role in promoting sensorimotor integration, and it is a natural way to enhance volitional effort. Therefore, we designed a preliminary clinical study to test a new proprioception-based motor training technique for augmenting kinesthetic awareness via haptic feedback. The feedback was provided by a robotic manipulandum and the test involved seven chronic hemiparetic subjects over 3?weeks. The protocol included evaluation sessions that consisted of a psychometric estimate of the subject's kinesthetic sensation, and training sessions, in which the subject executed planar reaching movements in the absence of vision and under a minimally assistive haptic guidance made by sequences of graded force pulses. The bidirectional haptic interaction between the subject and the robot was optimally adapted to each participant in order to achieve a uniform task difficulty over the workspace. All the subjects consistently improved in the perceptual scores as a consequence of training. Moreover, they could minimize the level of haptic guidance in time. Results suggest that the proposed method is effective in enhancing kinesthetic acuity, but the level of impairment may affect the ability of subjects to retain their improvement in time.

SUBMITTER: De Santis D

PROVIDER: S-EPMC4283673 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Robot-assisted training of the kinesthetic sense: enhancing proprioception after stroke.

De Santis Dalia D Zenzeri Jacopo J Casadio Maura M Masia Lorenzo L Riva Assunta A Morasso Pietro P Squeri Valentina V

Frontiers in human neuroscience 20150105

Proprioception has a crucial role in promoting or hindering motor learning. In particular, an intact position sense strongly correlates with the chances of recovery after stroke. A great majority of neurological patients present both motor dysfunctions and impairments in kinesthesia, but traditional robot and virtual reality training techniques focus either in recovering motor functions or in assessing proprioceptive deficits. An open challenge is to implement effective and reliable tests and tr ...[more]

PMID: 25601833

Similar Datasets

Project description:BackgroundProprioceptive deficits after stroke are associated with poor upper limb function, slower motor recovery, and decreased self-care ability. Improving proprioception should enhance motor control in stroke survivors, but current evidence is inconclusive. Thus, this study examined whether a robot-aided somatosensory-based training requiring increasingly accurate active wrist movements improves proprioceptive acuity as well as motor performance in chronic stroke.MethodsTwelve adults with chronic stroke completed a 2-day training (age range: 42-74 years; median time-after-stroke: 12 months; median Fugl-Meyer UE: 65). Retention was assessed at Day 5. Grasping the handle of a wrist-robotic exoskeleton, participants trained to roll a virtual ball to a target through continuous wrist adduction/abduction movements. During training vision was occluded, but participants received real-time, vibro-tactile feedback on their forearm about ball position and speed. Primary outcome was the just-noticeable-difference (JND) wrist position sense threshold as a measure of proprioceptive acuity. Secondary outcomes were spatial error in an untrained wrist tracing task and somatosensory-evoked potentials (SEP) as a neural correlate of proprioceptive function. Ten neurologically-intact adults were recruited to serve as non-stroke controls for matched age, gender and hand dominance (age range: 44 to 79 years; 6 women, 4 men).ResultsParticipants significantly reduced JND thresholds at posttest and retention (Stroke group: pretest: mean: 1.77° [SD: 0.54°] to posttest mean: 1.38° [0.34°]; Control group: 1.50° [0.46°] to posttest mean: 1.45° [SD: 0.54°]; F[2,37] = 4.54, p = 0.017, ηp2 = 0.20) in both groups. A higher pretest JND threshold was associated with a higher threshold reduction at posttest and retention (r = - 0.86, - 0.90, p ≤ 0.001) among the stroke participants. Error in the untrained tracing task was reduced by 22 % at posttest, yielding an effect size of w = 0.13. Stroke participants exhibited significantly reduced P27-N30 peak-to-peak SEP amplitude at pretest (U = 11, p = 0.03) compared to the non-stroke group. SEP measures did not change systematically with training.ConclusionsThis study provides proof-of-concept that non-visual, proprioceptive training can induce fast, measurable improvements in proprioceptive function in chronic stroke survivors. There is encouraging but inconclusive evidence that such somatosensory learning transfers to untrained motor tasks. Trial registration Clinicaltrials.gov; Registration ID: NCT02565407; Date of registration: 01/10/2015; URL: https://clinicaltrials.gov/ct2/show/NCT02565407 .

Project description:Background: The limitation to the use of ElectroMyoGraphy (sEMG) in rehabilitation services is in contrast with its potential diagnostic capacity for rational planning and monitoring of the rehabilitation treatments, especially the overground Robot-Assisted Gait Training (o-RAGT). Objective: To assess the barriers to the implementation of a sEMG-based assessment protocol in a clinical context for evaluating the effects of o-RAGT in subacute stroke patients. Methods: An observational study was conducted in a rehabilitation hospital. The primary outcome was the success rate of the implementation of the sEMG-based assessment. The number of dropouts and the motivations have been registered. A detailed report on difficulties in implementing the sEMG protocol has been edited for each patient. The educational level and the working status of the staff have been registered. Each member of staff completed a brief survey indicating their level of knowledge of sEMG, using a five-point Likert scale. Results: The sEMG protocol was carried out by a multidisciplinary team composed of Physical Therapists (PTs) and Biomedical Engineers (BEs). Indeed, the educational level and the expertise of the members of staff influenced the fulfillment of the implementation of the study. The PTs involved in the study did not receive any formal education on sEMG during their course of study. The low success rate (22.7%) of the protocol was caused by several factors which could be grouped in: patient-related barriers; cultural barriers; technical barriers; and administrative barriers. Conclusions: Since a series of barriers limited the use of sEMG in the clinical rehabilitative environment, concrete actions are needed for disseminating sEMG in rehabilitation services. The sEMG assessment should be included in health systems regulations and specific education should be part of the rehabilitation professionals' curriculum. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03395717.

Project description:BackgroundLoss 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.MethodsRATULS 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.FindingsBetween 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.InterpretationRobot-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.FundingNational Institute for Health Research Health Technology Assessment Programme.

Project description:Purpose: Robot-assisted training has been widely used in neurorehabilitation, but its effect on facilitating recovery after stroke remains controversial. One possible reason might be lacking consideration of the role of embodiment in robotic systems. Mirror visual feedback is an ideal method to approach embodiment. Thus, we hypothesized that mirror visual feedback priming with subsequent robot-assisted training might provide additional treatment benefits in rehabilitation. Method: This is a prospective, assessor-blinded, randomized, controlled study. Forty subacute stroke patients were randomly assigned into an experimental group (N = 20) or a control group (N = 20). They received either mirror visual feedback or sham-mirror visual feedback prior to robot-assisted training for 1.5 h/day, 5 days/week for 4 weeks. Before and after intervention, the Fugl-Meyer Assessment Upper Limb subscale, the Functional Independence Measure, the modified Barthel Index, and grip strength were measured. Scores of four specified games were recorded pre and post one-time mirror visual feedback priming before intervention in the experimental group. Results: All measurements improved significantly in both groups following interventions. Moreover, the Fugl-Meyer Assessment Upper Limb subscale, self-care subscale of the Functional Independence Measure, and the grip strength were improved significantly in the experimental group after a 4-week intervention, compared with the control group. Significantly higher scores of two games were revealed after one-time priming. Conclusions: Mirror visual feedback prior to robot-assisted training could prompt motor recovery, increase ability of self-care, and potentially enhance grip strength in stroke patients, compared to control treatment. Moreover, mirror visual feedback priming might have the capability to improve the patient's performance and engagement during robot-assisted training, which could prompt the design and development of robotic systems. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: ChiCTR1900023356.

Project description:Stroke is a leading cause of motor disability worldwide, and robot-assisted therapies have been increasingly applied to facilitate the recovery process. However, the underlying mechanism and induced neuroplasticity change remain partially understood, and few studies have investigated this from a multimodality neuroimaging perspective. The current study adopted BCI-guided robot hand therapy as the training intervention and combined multiple neuroimaging modalities to comprehensively understand the potential association between motor function alteration and various neural correlates. We adopted EEG-informed fMRI technique to understand the functional regions sensitive to training intervention. Additionally, correlation analysis among training effects, nonlinear property change quantified by fractal dimension (FD), and integrity of M1-M1 (M1: primary motor cortex) anatomical connection were performed. EEG-informed fMRI analysis indicated that for iM1 (iM1: ipsilesional M1) regressors, regions with significantly increased partial correlation were mainly located in contralesional parietal, prefrontal, and sensorimotor areas and regions with significantly decreased partial correlation were mainly observed in the ipsilesional supramarginal gyrus and superior temporal gyrus. Pearson's correlations revealed that the interhemispheric asymmetry change significantly correlated with the training effect as well as the integrity of M1-M1 anatomical connection. In summary, our study suggested that multiple functional brain regions not limited to motor areas were involved during the recovery process from multimodality perspective. The correlation analyses suggested the essential role of interhemispheric interaction in motor rehabilitation. Besides, the underlying structural substrate of the bilateral M1-M1 connection might relate to the interhemispheric change. This study might give some insights in understanding the neuroplasticity induced by the integrated BCI-guided robot hand training intervention and further facilitate the design of therapies for chronic stroke patients.

Dataset Information

Robot-assisted training of the kinesthetic sense: enhancing proprioception after stroke.

Publications

Robot-assisted training of the kinesthetic sense: enhancing proprioception after stroke.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets