Search

Summary Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain–computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.

fMRI has been used to characterize the abnormal brain activity after stroke during attempted motor tasks, the change in brain activity accompanying spontaneous motor recovery, and response to interventions. However, many patients after stroke exhibit abnormally high effort during attempted movements, including undesired movements of the supposed quiescent, uninvolved limb, which could confound fMRI measures. We developed a method of identifying the potentially confounded scans, using EMG measures of muscle activity in the supposed quiescent limb. We found that there was no interference in the MRI signal from the EMG data acquisition system, during simultaneous use of both MRI and EMG. For EMG signal acquisition, as expected, we were able to identify EMG signal free of MRI noise contamination during the inter-scan interval between any given scan and its subsequent scan. We tested movement of the involved limb. We determined that when undesired muscle activation was present in the uninvolved, supposed quiescent limb, there was an over-estimation of the number of active voxels ranging from 10 to 11, depending upon the ROI.

Introduction: Loss of somatosensory function after stroke weakens the ability to adequately relate to our environment, thus significantly reduces quality of life. Neuroplastic processes of sensory recovery are poorly understood. The objective of this study was to identify cortical regions that undergo structural changes (measured by change in cortical thickness (CT)) during sensory recovery. The hypothesis was that for subjects who improve sensory acuity, CT change in regions of the bilateral sensory network correlates with change in sensory acuity. Methods: Chronic stroke survivors were treated with 12-weeks rehabilitation. Outcome measures were sensory acuity (monofilament), Fugl-Meyer upper limb coordination and CT (T1 Magnetic Resonance Imaging). CT change was calculated based on T1 images using Freesurfer longitudinal processing stream. General linear regression modeling identified cortical regions where change in CT was associated with change in sensory acuity after controlling for baseline sensory impairment and change in motor function. Cluster-wise correction for multiple comparisons was conducted using Monte-Carlo simulation at p Results: Subjects, who improved in sensory acuity (n=18), were 55.8±13.7 year old; 10% female; 1.8±0.9 years after first ever stroke. Acuity improved from 43.9±14mm to 40.53±13mm (p=0.004). FM improved from 22.4±8 to 34.5±10 (p Conclusion: Rehabilitation produces modality-specific structural brain changes that can be measured by changes in cortical thickness. Improved sensation correlates with increased thickness in bilateral high-order association sensory cortices reflecting a complex nature of sensory rehabilitation.

The Electroencephalogram (EEG) is a non-invasive technique used in the medical field to record and analyze brain activity. In particular, Brain Machine Interfaces (BMI) create this bridge between brain signals and the external world through prosthesis, visual interfaces and other physical devices. This paper investigates the relation between particular hand movement directions while using a BMI and the EEG recordings during such movement. The Common Spatial Pattern method (CSP) over the high-γ frequency band is utilized in order to discriminate opposite hand movement directions. The experiment is performed with three subjects and the average classification accuracy is obtained for two different cases.

The successful application of noninvasive brain-computer interfaces (BCI) to neurological rehabilitation requires examination of low frequency movement artifacts and development of accurate new methods for their correction. To this end, this study applies an adaptive trend extraction method to electroencephalogram (EEG) signals recorded during active and passive center-out reaching tasks. Distinct patterns are discovered, which correlate to arm kinematics, but are shown to be largely artifactual in nature. Notably, these patterns are found to be similar to features currently used for discrimination of movement direction, indicating a necessity for caution and precise signal processing methods when utilizing low frequency content of EEG signals in such applications.

More than 3 million stroke survivors live with residual disabilities and mobility deficits even after rehabilitation. Therefore, it is important to develop new, more effective, gait training methods. The purpose of this study was twofold: (1) testing the feasibility of combining multi-channel functional neuromuscular stimulation (FNS) using intramuscular (IM) electrodes and body weight supported treadmill training (BWSTT) for gait training; and (2) documenting the potential gait practice advantages afforded by combining FNS-IM and BWSTT. Eight subjects with gait deficits in the chronic phase (>12 months) were enrolled. Intramuscular electrodes were placed in the paretic hip abductors, knee flexors and extensors, and ankle dorsiflexors, plantarflexors, and evertors. Subjects were treated with exercise and gait training using the combined technologies 1 1/2 h/week, four times/week, for 12 weeks. Feasibility was tested according to performance of the technologies, clinician skill factors, and subject satisfaction. Impairment, function, and quality of life were measured. Provision of practice for eight gait characteristics was catalogued. We found the following results for the combined technologies: (1) the combined technologies were safe and feasible; (2) clinicians required five training sessions to reach proficiency; (3) subjects were satisfied; (4) there were significant gains in impairment and functional measures; (5) a greater number of gait practice characteristics were provided with the combined technologies than with either alone.

Background.Arm spasticity is a challenge in the care of chronic stroke survivors with motor deficits. In order to advance spasticity treatments, a better understanding of the mechanism of spasticity-related neuroplasticity is needed.Objective.To investigate brain function correlates of spasticity in chronic stroke and to identify specific regional functional brain changes related to rehabilitation-induced mitigation of spasticity.Methods.23 stroke survivors (>6 months) were treated with an arm motor learning and spasticity therapy (5 d/wk for 12 weeks). Outcome measures included Modified Ashworth scale, sensory tests, and functional magnetic resonance imaging (fMRI) for wrist and hand movement.Results.First, at baseline, greater spasticity correlated with poorer motor function (P=0.001) and greater sensory deficits (P=0.003). Second, rehabilitation produced improvement in upper limb spasticity and motor function (P<0.0001). Third, at baseline, greater spasticity correlated with higher fMRI activation in the ipsilesional thalamus (rho=0.49,P=0.03). Fourth, following rehabilitation, greater mitigation of spasticity correlated with enhanced fMRI activation in the contralesional primary motor (r=-0.755,P=0.003), premotor (r=−0.565,P=0.04), primary sensory (r=−0.614,P=0.03), and associative sensory (r=−0.597,P=0.03) regions while controlling for changes in motor function.Conclusions.Contralesional motor regions may contribute to restoring control of muscle tone in chronic stroke.

Following stroke, many patients do not regain a normal, safe gait pattern even after receiving conventional physical therapy. One promising technique is functional neuromuscular stimulation (FNS) with intramuscular (IM) electrodes (FNS-IM). Five subjects were admitted into the study at 3 weeks to 3 months following the stroke. For each subject, electrodes were placed intramuscularly at the motor point of up to seven lower extremity paretic muscles. Subjects were treated for 6 months, twice weekly with FNS-IM for exercise and gait training. The stimulator and software provided individualized stimulation patterns, with flexible stimulus parameters and activation timings of multiple muscles. Outcome measures were active joint movement, coordination (Fugl-Meyer scale), balance (Tinetti scale), gait (Tinetti scale), activities of daily living (functional independence measure), and therapist and subject satisfaction (survey instrument). Subjects tolerated well the placement of IM electrodes with no adverse effects, and subjects lost no conventional rehabilitation time. Therapists and subjects were satisfied with the FNS-IM system as a rehabilitation tool. Post treatment, subjects demonstrated improvements in impairment and disability in active joint movement, coordination, balance, gait and activities of daily living. Considered together with prior research for chronic stroke subjects, this research suggests that FNS-IM can be successfully and efficaciously utilized for gait training for those with acute stroke.

Objective To compare the gains for chronic stroke patients in volitional gait pattern attained from treatment with functional neuromuscular stimulation (FNS) and intramuscular electrodes (IM) with gains attained using conventional therapy, including treatment with FNS using surface electrodes (surface-stim). Design This single-subject research design consisted of a series of two subjects. Three months of conventional therapy and surface-stim were followed by treatment using the FNS-IM system. Two stroke patients had cerebrovascular accident 1 or 4 yr before the study and ambulated with a cane. Interventions consisted of 3 months of conventional exercise and gait training including surface-stim, followed by 7-14 months of treatment with the FNS-IM system. Treatments occurred up to 3 times/wk for 1-hr sessions and a home program. Outcome measures consisted of six kinematic gait components, as measured by a six-camera video-based data-acquisition system. Coordination of isolated joint movement was measured according to the Fugl-Meyer scale. Results Both subjects improved during conventional therapy to some degree. During FNS-IM treatment, gains were made beyond those attained during conventional therapy. Statistically significant differences were found between conventional and FNS-IM therapy. Conclusions For these two subjects, gains in volitional control of gait were made during conventional treatment (including surface-stim); for these two subjects during FNS-IM treatment, additional gains were made in volitional gait pattern, beyond those attained during conventional therapy.

Purpose : The purpose of this study was to investigate the response of muscles with prolonged flaccid paralysis (a year after stroke) to two types of treatment: (1) functional neuromuscular stimulation (FNS) with surface electrodes; and (2) FNS with intramuscular (IM) electrodes (FNS-IM). A second purpose was to compare FNS-gait versus volitional gait (no FNS activation). Method : We used a single case study design; our patient was age 72, with flaccid paralysis of knee flexors and ankle dorsiflexors. Results : Following four months of treatment with surfacestimulation, there was no change in muscle function or gait. Following treatment with FNS-IM, the patient regained partial volitional control of knee flexors and dorsiflexors; untreated muscles did not change. Conclusion : FNS-gait provided more normal knee and ankle dorsiflexion during swing phase versus volitional gait swing phase (no FNS activation).

Problem statement. In rehabilitation for military personnel and veterans with TBI, we currently face two fundamental problems. First, for those with motor and cognitive dysfunction, current treatment does not restore many to normal everyday function and life role participation. Therefore, the purpose of this study is to restore function and life role participation for military personnel and veterans with TBI by customizing, applying, and testing an integrated cognitive and motor training protocol that was successful in other populations with problems similar to TBI. This will be an A-B study design, with subjects serving as control subjects during Phase A (standard care) and as experimental subjects during Phase , during which they will receive 12 weeks of cognitive and motor training, 5 times per week, 5 hours/session.

Background: In chronic stroke, recovery of coordinated reaching is critical to arm function and quality of life. Improvement of motor function can be achieved with intensive rehabilitation even years after stroke, but current methods fall short of restoring normal movement for many stroke survivors. Little is known regarding the change in brain function that is required to improve shoulder/elbow reach function. Therefore, the aim of this study was to characterize the change in brain activity of bilateral motor-sensory brain regions, which may drive recovery of functional reach. Methods: 22 stroke subjects (>6 months post-stroke) with arm motor deficits were enrolled and treated with intensive arm rehabilitation (5 hours/day, 5 days/week for 12 weeks). Outcome measures were: 1) functional magnetic resonance imaging (fMRI) during a shoulder/elbow reach task (paretic arm), 2) skilled motor function (Arm Motor Assessment Test (AMAT)). fMRI activation (voxel count) was calculated for bilateral sensory-motor control regions. Multiple linear regression analysis was conducted to determine the relationship between the change in brain function and recovery of functional reach. Co-variates included pre-treatment AMAT, age and time-since-stroke. Results: Subject characteristics were: age, 56.3 (±12.8years); 41%, female; and 1.8 (±1.1) years post-stroke. AMAT improved from 1636.63 (±668.41) to 1213.67 (±6643.79) seconds (p Conclusions: In chronic stroke, important gain in functional reach is associated with increased activation, not only in the ipsilesional primary motor region, but also in the contralesional motor-sensory regions, which occurred in response to intensive neurorehabilitation. Arm neurorehabilitation methods should be based on principles that engage this brain plasticity, which may drive recovery of arm function.

Intensive gait training can produce improvements in gait and function (6 months after stroke); however, findings are mixed for enhanced life-role participation. Therefore, it is unclear if improved gait and function translate into life-role participation gain. Our objective was to evaluate whether intensive gait therapy can produce improvements in life-role participation for chronic-stroke survivors, according to a comprehensive measure dedicated to life-role participation.In conjunction with a clinical gait-training trial, we conducted a secondary analysis for a 44-member cohort with stroke (6 months). Gait-training interventions included functional neuromuscular stimulation, body-weight supported treadmill training, over-ground gait training and exercise for 1.5 hours/day, 4 days/week for 12 weeks. Study measures included Tinetti Gait (gait impairment), Functional Independence Measure (FIM, function), Stroke Impact Scale subscale of life-role participation (SIS part) and Craig Handicap Assessment and Reporting Technique (CHART, life-role participation). Analysis included Wilcoxon signed rank test and polytomous universal regression model.Gait interventions produced significant improvement in CHART (p = 0.020), SIS part (p = 0.011), FIM (p0.0001), and Tinetti Gait (p0.0001). Age, gender and time since stroke did not predict response to treatment.Intensive gait therapy resulted in significant gain in life-role participation, according to a comprehensive measure, so dedicated.

Background: Spasticity can prevent productive practice of skilled movement that should occur during neurorehabilitation of coordinated arm movements after stroke. Studies showed that spasticity could be reduced following an intervention that inhibited activation of the contralesional primary motor region (M1) using non-invasive transcranial magnetic or electric stimulation. However, there is little understanding of how the mitigation of spasticity might be controlled by the multiple sensorimotor control brain regions. Therefore, the aim of this study was to evaluate the change in activation patterns of multiple sensorimotor regions that predict the mitigation of spasticity, in response to intensive upper limb neurrehabiltiation. Methods: Twenty three stroke subjects (>6 months after stroke) with persistent arm motor deficits were treated with intensive upper extremity rehabilitation (5 hours/day, 5 days/week for 12 weeks). Baseline and post-rehab evaluation consisted of three measures: 1) functional magnetic resonance imaging (fMRI) during a shoulder/elbow reach task for the paretic arm, 2) a skilled motor function (Arm Motor Assessment test (AMAT)), and 3) spasticity (Modified Ashworth Scale(MAS)). Volume of brain activation (voxel count) during the reach task was calculated for sensory and motor control regions using SPM05 (London, UK) and in-house software in MATLAB (Natick, MA). Paired t-test analysis was conducted for pre- vs post-treatment comparisons. Multiple linear regression analysis was conducted, where post-rehab AMAT was the dependent variable, the co-variate was pre-rehab score, and the predictors were change from pre- to post-rehab in voxel count in bilateral M1, somatosensory (SS), posterior parietal (PP), lateral premotor (LPM) and supplementary motor (SMA) areas. Results: Subject characteristics were as follows: mean age, 56.3 ±12.8years; 41%, female; and 1.8±1.1 years after first ever stroke. Change in the activation pattern in a number of regions significantly predicted mitigated spasticity (R2=.86). Specifically, in response to treatment, increased activation, in ipsilesional SMA (p=.002) and contralesional M1 (p=.002), predicted mitigated spasticity. Reduction in activation volume, in ipsilesional PP region (p=.0009), contralesional SS (p=.008) and SMA (p=.006), predicted mitigated spasticity. AMAT score improved from 1636.63±668.41 to 1213.67±6643.79 seconds (p Conclusions: A specific pattern of functional brain change across multiple regions predicted mitigation of spasticity following neurorehabilitation; skill functional recovery occurred, as well. This information could be used in constructing study design for future research that would investigate brain training to mitigate spasticity and improve skilled functional task performance.

Background/Objectives: Gait coordination is not well-studied nor well-described in chronic stroke. Gait coordination can be defined as the simultaneous consideration of spatial and temporal movement characteristics. One aspect of gait coordination is the consistency of relative movements of hip/knee, hip/ankle, and knee/ankle across the gait cycle. Without consistency of relative joint movement from step to step, safety of gait is compromised and function is reduced. Therefore, the hypothesis of this study was that in chronic stroke survivors with persistent gait deficits, consistency of gait coordination is impaired, according to a measure of inter-joint coordination consistency (hip/knee; hip/ankle; and knee/ankle) of movement excursion and timing across the gait cycle from step to step. Methods: Ten healthy adults and thirty-eight subjects with persistnet gait deficits were enrolled (>6mos after stroke). In terms of gait speed, stroke subjects were either household ambulators (HA; Conclusions: Inconsistent relative joint movement between hip, knee, and ankle across the gait cycle, could be a source of falls, poor walking endurance, and dysfunction. The presence of this impairment should be noted in assessment and targeted during treatment.

Zimbelman J, Daly JJ, Roenigk KL, Butler K, Burdsall R, Holcomb JP. Capability of 2 gait measures for detecting response to gait training in stroke survivors: Gait Assessment and Intervention Tool and the Tinetti Gait Scale. Objective To characterize the performance of 2 observational gait measures, the Tinetti Gait Scale (TGS) and the Gait Assessment and Intervention Tool (G.A.I.T.), in identifying improvement in gait in response to gait training. Design In secondary analysis from a larger study of multimodal gait training for stroke survivors, we measured gait at pre-, mid-, and posttreatment according to G.A.I.T. and TGS, assessing their capability to capture recovery of coordinated gait components. Setting Large medical center. Participants Cohort of stroke survivors (N=44) greater than 6 months after stroke. Interventions All subjects received 48 sessions of a multimodal gait-training protocol. Treatment consisted of 1.5 hours per session, 4 sessions per week for 12 weeks, receiving these 3 treatment aspects: (1) coordination exercise, (2) body weight–supported treadmill training, and (3) overground gait training, with 46% of subjects receiving functional electrical stimulation. Main Outcome Measures All subjects were evaluated with the G.A.I.T. and TGS before and after completing the 48-session intervention. An additional evaluation was performed at midtreatment (after session 24). Results For the total subject sample, there were significant pre-/post-, pre-/mid-, and mid-/posttreatment gains for both the G.A.I.T. and the TGS. According to the G.A.I.T., 40 subjects (91%) showed improved scores, 2 (4%) no change, and 2 (4%) a worsening score. According to the TGS, only 26 subjects (59%) showed improved scores, 16 (36%) no change, and 1 (2%) a worsening score. For 1 treatment group of chronic stroke survivors, the TGS failed to identify a significant treatment response to gait training, whereas the G.A.I.T. measure was successful. Conclusions The G.A.I.T. is more sensitive than the TGS for individual patients and group treatment response in identifying recovery of volitional control of gait components in response to gait training.

The purpose was to determine timing characteristics of leg muscle latencies for patients following stroke (>12 months) who had persistent coordination and gait deficits, and to determine the relationships among abnormal latencies, dyscoordination, and gait deficits. We compared nine healthy controls and 27 stroke survivors. Surface electromyography measured activation and deactivation latencies of knee flexor and extensor muscles during a ballistic knee flexion task, consistency of latencies across repetitions, and close coupling between agonist and antagonist muscle latencies. We measured Fugl-Meyer (FM) coordination and the functional gait measure, six minute walk test (6MWT). For stroke subjects, there were significant delays of muscle activation and deactivation, abnormal inconsistency, and abnormal decoupled agonist and antagonist activations. There was good correlation between activation latencies and FM and 6MWT. Results suggest abnormal timing characteristics underlie coordination impairment and dysfunctional gait. These abnormal muscle activation and deactivation timing characteristics are important targets for rehabilitation.

After stroke rehabilitation, many survivors of stroke exhibit persistent gait deficits. In previous work, we demonstrated significant gains in gait kinematics for survivors of chronic stroke using multichannel functional electrical stimulation with intramuscular electrodes (FES-IM). For this study, we tested the feasibility of combining FES-IM and gait robot technologies for treating persistent gait deficits after stroke. Six subjects, >or= 6 months after stroke, received 30-minute intervention sessions of combined FES-IM and gait robotics 4 days a week for 12 weeks. Feasibility was assessed according to three factors: (1) performance of the interface of the two technologies during intervention sessions, (2) clinicians' success in using two technologies simultaneously, and (3) subject satisfaction. FES-IM system hardware and software design features combined with the gait robot technology proved feasible to use. Each technology alone provided unique advantages and disadvantages of gait practice characteristics. Because of the unique advantages and disadvantages of each technology, gait deficits need to be accurately identified and a judicious treatment plan properly targeted before FES-IM, a gait robot, or both combined are selected.

Recent neuroscience methods have provided the basis upon which to develop effective gait training methods for recovery of the coordinated components of gait after neural injury. We determined that there was not an existing observational measure that was, at once, adequately comprehensive, scored in an objectively-based manner, and capable of assessing incremental improvements in the coordinated components of gait. Therefore, the purpose of this work was to use content valid procedures in order to develop a relatively inexpensive, more comprehensive measure, scored with an objectively-based system, capable of incrementally scoring improvements in given items, and that was both reliable and capable of discriminating treatment response for those who had a stroke. Eight neurorehabilitation specialists developed criteria for the gait measure, item content, and scoring method. In subjects following stroke (>12 months), the new measure was tested for intra- and inter-rater reliability using the Intraclass Correlation Coefficient; capability to detect treatment response using Wilcoxon Signed Ranks Test; and discrimination between treatment groups, using the Plum Ordinal Regression. The Gait Assessment and Intervention Tool (G.A.I.T.) is a 31-item measure of the coordinated movement components of gait and associated gait deficits. It exhibited the following advantages: comprehensive, objective-based scoring method, incremental measurement of improvement within given items. The G.A.I.T. had good intra- and inter-rater reliability (ICC=.98, p=.0001, 95% CI=.95, .99; ICC=.83, p=.007, 95% CI=.32, .96, respectively. The inexperienced clinician who had training, had an inter-rater reliability with an experienced rater of ICC=.99 (p=.0001, CI=.97, .999). The G.A.I.T. detected improvement in response to gait training for two types of interventions: comprehensive gait training (z=-2.93, p=.003); and comprehensive gait training plus functional electrical stimulation (FES; z=-3.3, p=.001). The G.A.I.T. was capable of discriminating between two gait training interventions, showing an additive advantage of FES to otherwise comparable comprehensive gait training (parameter estimate=1.72, p=.021; CI, .25, 3.1).

This work presents a means to automatically synchronize two promising gait training technologies to address gait deficits in stroke survivors: functional electrical stimulation using intramuscular electrodes (FES-IM) and the Lokomat robotic gait orthosis. A system of hardware and software was developed to achieve the automatic synchronization. A series of bench tests were performed to verify the feasibility and reliability of automatic synchronization. The bench tests showed that automatic synchronization of FES-IM to the Lokomat gait cycle was feasible and reliable. Automatic synchronization was more consistent than manually triggered stimulation (10-fold smaller standard deviation of latency), and produced no early or missed stimulations across 634 strides. Automatic synchronization had greater accuracy than manually triggered stimulation, producing stimulation timed to an accuracy of 2.5% of one gait cycle duration (heel strike to heel strike = 100).

Brain injury resulting from stroke often causes upper-extremity motor deficits that limit activities of daily living. Several therapies being developed for motor rehabilitation after stroke focus on increasing time spent using the extremity to promote motor relearning. Providing a novel system for user-worn therapy may increase the amount and rate of functional motor recovery. A user-worn system comprising accelerometers, gyroscopes, and electromyography amplifiers was used to wirelessly transmit motion and muscle activity from normal and stroke subjects to a computer as they completed five upper-extremity rehabilitation tasks. An algorithm was developed to automatically detect the therapy task a subject performed based on the gyroscope and electromyography data. The system classified which task a subject was attempting to perform with greater than 80% accuracy despite the fact that those with severe impairment produced movements that did not resemble the goal tasks and were visually indistinguishable from different tasks. This developed system could potentially be used for home-therapy compliance monitoring, real-time patient feedback and to control therapy interventions.

Electroencephalogram (EEG) recordings are highly susceptible to noise from electromyogram (EMG) signals of the frontalis and temporalis muscles. In this paper, we propose and evaluate a new method for detecting frontalis and temporalis muscle EMG contamination in EEG signals based on recent findings on topographic and spectral characteristics of cranial EMG.

Functional recovery after brain damage or disease is dependent on the neuroplastic capability of the cortex and the nonaffected brain. Following cortical injury in the motor and sensory regions, the adjacent spared neural tissues and related areas undergo modifications that are required in order to drive more normal motor control. Current rehabilitation models seek to stimulate functional recovery by capitalizing on the inherent potential of the brain for positive reorganization after neurological injury or disease. This article discusses how neuroimaging and electrophysiological data can inform clinical practice; representative data from the modalities of functional magnetic resonance imaging, diffusion tensor imaging, magnetoencephalography, electroencephalography, and positron emission tomography are cited. Data from a variety of central nervous system disease and damage models are presented to illustrate how rehabilitation practices are beginning to be shaped and informed by neuroimaging and electrophysiological data.

Persistent gait deficits after stroke can cause falls, elevated energy cost and poor endurance. Coordination impairment is an underlying cause of gait deficits. Few efficacious interventions have been described that have targeted and measured restoration of coordinated gait components. Neuromuscular electrical stimulation can provide the critical gait practice characteristic of close-to-normal movements, by electrically inducing muscle contractions and coordinated movements that are not possible under volitional effort. Two-channel, surface neuromuscular electrical stimulation can be synchronized with phases of gait and can provide faster, more symmetrical neuromuscular electrical stimulation-assisted gait than gait with no neuromuscular electrical stimulation. Difficulties encountered during the use of surface neuromuscular electrical stimulation for gait training led to the development of neuromuscular electrical stimulation with implanted technologies. Implanted electrodes and/or stimulators proved to be feasible for gait training in stroke survivors. Gait training with a multichannel neuromuscular electrical stimulation system with implanted electrodes proved more advantageous than gait training without neuromuscular electrical stimulation, according to measures of volitional coordinated gait components (neuromuscular electrical stimulation deactivated).

Purpose Cortical function is not well understood in stroke survivors with persistent dyscoordination. The study purpose was two-fold: 1) characterize cognitive planning time and cognitive effort level for a circle-drawing motor task in stroke survivors using shoulder/elbow muscles and 2) identify the relationship between cognitive effort level and movement smoothness. Methods Twelve stroke survivors with shoulder/elbow coordination deficits (> 12 mo) and eight controls were enrolled. The motor task was to draw a circle on a horizontal surface using only shoulder/elbow muscles. Outcome measures were: EEG-derived cognitive planning time, cognitive effort level, and movement smoothness. Comparisons between stroke and controls were made using t -tests. The Pearson's correlation model was analyzed to determine the relationship between movement smoothness and cognitive effort level. Results Stroke subjects showed a statistically significant prolonged motor planning time versus controls for both lesion and non-lesion sides ( p = 0.013 and 0.049, respectively). They also showed a statistically significant elevated effort level versus controls for both sides ( p = 0.016 and 0.013). The patients exhibited statistically significant poor movement smoothness in the medial/lateral and forward/backward movement directions versus controls ( p = 0.035 and 0.037, respectively). For stroke, there was a significant correlation between cognitive effort level on the non-lesion side and smoothness of movement in the medial/lateral and forward/backward directions ( r = 0.54, p = 0.036 and r = 0.76, p = 0.002, respectively). On the lesion side, results were mixed ( r = 0.268, p = 0.2 r = 0.59, p = 0.023, respectively). Conclusions Stroke survivors with upper limb motor deficits exhibit a longer cognitive planning time and elevated cognitive effort for performance of a complex shoulder/elbow motor coordination task. The elevated cognitive effort level was associated with poor (jerky) motor performance, suggesting a potential role of the CNS in controlling movement smoothness of the arm.

Understanding cortical function can provide accurately targeted interventions after stroke. Initially, stroke survivors had prolonged cognitive planning time and elevated cognitive effort, highly correlated with motor control impairments. Exploratory results suggest that neurorehabilitation, accurately targeted to dyscoordination, weakness, and dysfunctional task component execution, can improve cognitive processes controlling motor function.

Twelve moderately to severely involved chronic stroke survivors (12 mo) were randomized to one of two treatments: robotics and motor learning (ROB-ML) or functional neuromuscular stimulation and motor learning (FNS-ML). Treatment was 5 h/d, 5 d/wk for 12 wk. ROB-ML group had 1.5 h per session devoted to robotics shoulder and elbow (S/E) training. FNS-ML had 1.5 h per session devoted to functional neuromuscular stimulation (surface electrodes) for wrist and hand (W/H) flexors/extensors. The primary outcome measure was the functional measure Arm Motor Ability Test (AMAT). Secondary measures were AMAT-S/E and AMAT-W/H, Fugl-Meyer (FM) upper-limb coordination, and the motor control measures of target accuracy (TA) and smoothness of movement (SM). ROB-ML produced significant gains in AMAT, AMAT-S/E, FM upper-limb coordination, TA, and SM. FNS-ML produced significant gains in AMAT-W/H and FM upper-limb coordination.

Purpose Purpose one was to characterize the consistency of intra-limb hip/knee (H/K) coordination according to a measure of average coefficient of correspondence (ACC) across strides. Purpose two was to investigate H/K ACC validity and ability to discriminate pre-/post-treatment change in stroke survivors. Methods Five healthy controls and 32 chronic (>12 mos) stroke survivors were enrolled, and H/K ACC was calculated for both groups. Comparison between controls and stroke was made using the Mann–Whitney Test. Convergent validity of H/K ACC was tested using the Pearson Correlation model with gait speed and the 6 min Walk Test (6MWT). Stroke survivors were randomized to either: (1) gait training with functional neuromuscular stimulation (FNS) using intramuscular (IM) electrodes or (2) gait training without FNS. Both groups had treatment 1.5 h/day, 5 days/week, for 12weeks, including .5 h coordination exercise, .5 h body weight supported treadmill training (BWSTT), and .5 h over ground gait training. The FNS-IM group used FNS-IM for all treatment components; the No-FNS group did not. Pre-/post-treatment comparisons were made using ANOVA. Results H/K ACC detected a significant difference between controls versus stroke involved limb (p = .0001) and controls versus stroke uninvolved limb (p = .042). The H/K ACC measure was well-correlated with gait speed (r = .70) and 6MWT (r = .69). H/K ACC showed a significant treatment response to FNS-IM (p = .003), but not No-FNS (p = .747). Conclusions H/K ACC sensitively discriminated between controls versus stroke involved or uninvolved limbs. H/K ACC was valid, with significant correlations with both walking speed and 6MWT. FNS-IM produced a significant gain in H/K ACC, and No-FNS did not.

Background and Purpose— Conventional therapies fail to restore normal gait to many patients after stroke. The study purpose was to test response to coordination exercise, overground gait training, and weight-supported treadmill training, both with and without functional neuromuscular stimulation (FNS) using intramuscular (IM) electrodes (FNS-IM). Methods— In a randomized controlled trial, 32 subjects (>1 year after stroke) were assigned to 1 of 2 groups: FNS-IM or No-FNS. Inclusion criteria included ability to walk independently but inability to execute a normal swing or stance phase. All subjects were treated 4 times per week for 12 weeks. The primary outcome measure, obtained by a blinded evaluator, was gait component execution, according to the Tinetti gait scale. Secondary measures were coordination, balance, and 6-minute walking distance. Results— Before treatment, there were no significant differences between the 2 groups for age, time since stroke, stroke severity, and each study measure. FNS-IM produced a statistically significant greater gain versus No-FNS for gait component execution ( P =0.003; parameter estimate 2.9; 95% CI, 1.2 to 4.6) and knee flexion coordination ( P =0.049). Conclusion— FNS-IM can have a significant advantage versus No-FNS in improving gait components and knee flexion coordination after stroke.

After stroke, persistent gait deficits cause debilitating falls and poor functional mobility. Gait restoration can preclude these outcomes. Sixteen subjects (>12 months poststroke) were randomized to two gait training groups. Group 1 received 12 weeks of treatment, 4 times a week, 90 min per session, including 30 min strengthening and coordination, 30 min over-ground gait training, and 30 min weight-supported treadmill training. Group 2 received the same treatment, but also used functional neuromuscular stimulation (FNS) with intramuscular (IM) electrodes (FNS-IM) for each aspect of treatment. Outcome measures were kinematics of gait swing phase. Both groups showed no significant pre-/posttreatment gains in peak swing hip flexion. Group 1 (no FNS) had no significant gains in other gait components at posttreatment or at follow-up. Group 2 (FNS-IM) had significant gains in peak swing knee flexion and mid-swing ankle dorsiflexion (p < 0.05) that were maintained for 6 months.

INTRODUCTION The Gait Coordination Protocol (GCP) was successful in producing clinically and statistically significant gains in impairment, function, and life-role participation for those in the chronic phase after stroke who had exhibited persistent moderate to severe gait deficits [1-3]. The GCP was initially developed to test response to functional electrical stimulation (FES); notably, the GCP produced enhanced coordinated gait regardless of whether FES was used [1]. (The Video shows gait recovery in response to the GCP for a participant from the "No-FES group.") In response to national and state presentations, there was a strong call for description of the details of the GCP and its clinical implementation. Therefore, the purpose here is to detail the implementation of this treatment protocol. We constructed the GCP based on the phenomenon of brain plasticity and associated motor learning principles that included task-specific practice (practice as close-to-normal movement as possible [4-7] with continual progression toward normal), high repetition of the desired movement pattern [8-10], focused attention on the part of the learner [11], training specificity [9,12-14], and awareness and feedback [15]. The GCP, described subsequently, was provided 1.5 h/d, 4 d/wk, and for at least 48 visits (12 weeks) [1-2]. Before treatment, the initial assessment included muscle strength, coordination, muscle tone, balance, gait coordination, gait speed, function, and quality of life. Critical aspects of the assessment included the ability to generate normal movement at the hip, knee, and ankle for the motor tasks listed in Figure 1: A-J. For those movements that were impaired, assessment included not only the ability to volitionally generate each of these movements, but also the ability to move in conjunction with an array of assistive movement devices (body-weight support [BWS], bodyweight supported treadmill training [BWSTT], FES) and gait support devices (parallel bars, walker, cane). Each motor task (Figure 1) was assessed for the following characteristics: * Percentage of the normal range of movement that could be executed, volitionally and independently. * Percentage of the motor task that could be executed with the support of verbal or tactile facilitation. * Percentage of the normal range of movement that could be executed along with an assistive movement device. * Normality of effort level during the task (e.g., holding breath, abnormal co-contraction of muscles distant from the targeted task joints or antagonist muscle contractions). * Compensatory strategies employed during execution of the motor task. * Percentage of the task for which compensatory strategies were employed. * Number of repetitions of the motor task that could be performed with only a "beat" between repetitions before the motor task was performed in an abnormal fashion. In this manner, the assessment was used to identify the initial training level in the hierarchy schema of difficulty (Figure 1). For those motor tasks that could not be volitionally performed, an array of motor learning tools were employed (Figure 2). The GCP utilized an array of tools to optimally apply the principles of motor learning. These tools included selective body positioning (Figure 2: B.1-B.1.1), awareness training (Figure 2: B.2), and practice-assist devices (Figure 2: B.3). The position for motor task practice was selected to satisfy practice of both the most normal movement possible and also the most challenging body position, both of which are required for motor skill acquisition [16-19] (Figure 2: B.1). Practice included the standing position (Figure 2: B.1.1) and dynamic walking, of course, to satisfy the learning principle of task specificity (Figure 2: B.1.2). [FIGURE 2 OMITTED] Awareness training (Figure 2: B.2) consisted of learning to identify and differentiate between normal coordinated movement and the abnormal movement, learning to monitor oneself during practice, assessing how close one's movement was to the normal movement pattern, and assessing the frequency of execution of the more normal movement pattern during a series of practice trials [15]. …

Twelve moderately to severely involved chronic stroke survivors (>12 mo) were randomized to one of two treatments: robotics and motor learning (ROB-ML) or functional neuromuscular stimulation and motor learning (FNS-ML). Treatment was 5 h/d, 5 d/wk for 12 wk. ROB-ML group had 1.5 h per session devoted to robotics shoulder and elbow (S/E) training. FNS-ML had 1.5 h per session devoted to functional neuromuscular stimulation (surface electrodes) for wrist and hand (W/H) flexors/extensors. The primary outcome measure was the functional measure Arm Motor Ability Test (AMAT). Secondary measures were AMAT-S/E and AMAT-W/H, Fugl-Meyer (FM) upper-limb coordination, and the motor control measures of target accuracy (TA) and smoothness of movement (SM). ROB-ML produced significant gains in AMAT, AMAT-S/E, FM upper-limb coordination, TA, and SM. FNS-ML produced significant gains in AMAT-W/H and FM upper-limb coordination.

In this paper several methods are investigated for feature extraction and classification of mu features from electroencephalographic (EEG) readings of subjects engaged in motor tasks. EEG features are extracted by autoregressive (AR) filtering, mu-matched filtering, and wavelet decomposition (WD) methods, and the resulting features are classified by a linear classifier whose weights are set by an expert using a-priori knowledge, as well as support vector machines (SVM) using various kernels. The classification accuracies are compared to each other. SVMs are shown to offer a potential improvement over the simple linear classifier, and wavelets and mu-matched filtering are shown to offer potential improvement over AR filtering.