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There is a great need to develop new approaches for rehabilitation of the upper limb after stroke. Robotic therapy is a promising form of neurorehabilitation that can be delivered in higher doses than conventional therapy. Here we sought to determine whether the reported effects of robotic therapy, which have been based on clinical measures of impairment and function, are accompanied by improved motor control. Patients with chronic hemiparesis were trained for 3 wk, 3 days a week, with titrated assistive robotic therapy in two and three dimensions. Motor control improvements (i.e., skill) in both arms were assessed with a separate untrained visually guided reaching task. We devised a novel PCA-based analysis of arm trajectories that is sensitive to changes in the quality of entire movement trajectories without needing to prespecify particular kinematic features. Robotic therapy led to skill improvements in the contralesional arm. These changes were not accompanied by changes in clinical measures of impairment or function. There are two possible interpretations of these results. One is that robotic therapy only leads to small task-specific improvements in motor control via normal skill-learning mechanisms. The other is that kinematic assays are more sensitive than clinical measures to a small general improvement in motor control.
- stroke
- neurorehabilitation
- robotic therapy
- kinematics
- motor control
robotic therapy has emerged as a promising modality for stroke rehabilitation, as it has the advantage of being able to deliver therapy at a much higher intensity and dosage than conventional therapy. The largest study of robotic therapy conducted to date is the VA ROBOTICS study, a randomized control trial of robotic therapy of the upper limb for patients with chronic stroke using the MIT-Manus device (Lo et al. 2010). It was shown that, after 12 wk of therapy, the patients who received robotic training had slightly larger reductions in arm impairment compared with those who received usual care, but this difference in Fugl-Meyer Upper Extremity (FM) score was a clinically negligible 2.2 points. More recently, a study was conducted with a robot that allows three-dimensional (3D) movements compared with the two-dimensional (2D) planar movements of the MIT-Manus. As in the VA ROBOTICS study, there were significant but negligible effect sizes on the FM score (Klamroth-Marganska et al. 2014). Several other smaller studies have also shown that patients with chronic stroke undergoing robotic therapy have similar, if not better, gains than conventional therapy (Housman et al. 2009; Liao et al. 2012; Lum et al. 2002; Page et al. 2012; Volpe et al. 2008), with mean FM changes ranging from 2–7 points. These results suggest that robotic therapy does have the potential to elicit improvements at the level of impairment, but the effect is consistently small (Kwakkel et al. 2008).
Although the FM is a widely used measure of motor impairment after stroke, it requires a combination of strength and motor control. This makes it difficult to distinguish between these two different aspects of movement, which may dissociate with respect to recovery time course and respond differently to training (Noskin et al. 2007). Here we distinguish motor control from strength in that, to be skillful, contractions of various muscle groups must be well coordinated. Thus we define motor control, or motor skill, as the ability to make accurate and precise, goal-directed movements without using compensatory movements (Kitago et al. 2013) or reducing movement speed (Reis et al. 2009; Shmuelof et al. 2012), and we define reduced motor control as the loss of this ability.
In the present study, we sought to identify improvements in movements that occur with robotic therapy by performing kinematic analysis on visually guided gravity-supported planar reaching movements, which allowed us to isolate changes in motor control from recovery of strength (Kitago et al. 2013). Kinematic analyses also offer more objective measures of motor performance, compared with clinical assessments such as the FM, which is subject to considerable variance (See et al. 2013). To date, very few robotics rehabilitation studies have used kinematic analysis to look at the effects of robotic training. Krebs and colleagues (1998) showed that patients with subacute stroke had improved ability to draw circles after robotic therapy. Kahn and colleagues (2006) reported that, after 24 sessions of robotic therapy in chronic stroke, patients had straighter reaching trajectories and made fewer submovements. Another study (Lum et al. 2002) showed that, after 2 mo of robotic training, patients had longer reaching extent, along with significant improvements in FM scores.
Another advantage of using kinematic analysis is that it is sensitive to potential changes in the "unaffected arm," which would go undetected by measures like the FM. It is well documented that the ipsilesional arm of patients with stroke also has deficits in motor control but without the confounding effect of weakness (Noskin et al. 2007; Schaefer et al. 2007; Yarosh et al. 2004). Recent studies in animals have shown that skill training is not limb specific and has effects on both the trained and untrained sides. Repetitive use of the impaired limb in rats following unilateral ischemic stroke triggered reorganization of the cortex in the intact hemisphere (Barbay et al. 2013). Studies of motor learning in humans also show significant degrees of improvement in the untrained arm and hand (Grafton et al. 2002; Parlow and Kinsbourne 1989; Wiestler et al. 2014). Thus the unaffected arm can be viewed as a unique opportunity to assay for a motor-learning effect on the affected side.
To assay motor control, we use a gravity-supported, planar reaching task that minimizes both the requirement for antigravity strength and the use of compensatory strategies (Kitago et al. 2013). Unlike the robotic training protocol for which 3D training was employed, the 2D planar assay does not have joint angle redundancy amenable to compensation. This makes it an ideal choice for assessing motor control and can be considered the proximal analog of the finger individuation task (Kitago et al. 2013; Lang and Schieber 2004). By using this planar assay, we also sought to test motor control on a task separate from those performed during the training sessions. We applied a novel kinematic analysis to the visually guided reaching trajectories and compared this approach with standard functional and impairment assessments, the Action Research Arm Test (ARAT; Lyle 1981) and the FM, respectively.
The first objective of the present study was to investigate whether motor control in the affected arm changes in response to robotic training in patients with chronic stroke. The second objective was to investigate whether training the paretic limb caused changes in motor control of the ipsilesional (nonparetic) limb, which has not been previously examined in studies of robotic arm training for patients with chronic stroke.
Study participants.
Nine patients with chronic stroke were recruited from the outpatient rehabilitation clinics at Columbia University Medical Center between June 2009 and May 2011. Patients were included with the following criteria: 1) ischemic stroke at least 6 mo before the start of the first assessment session, 2) motor deficit of one arm with at least 20° wrist extension and 10° finger extension, 3) ability to sit and be active for an hour on a chair without cardiac, respiratory, and/or pain disturbances. We chose to test patients with moderate impairment of the upper extremity because we were specifically interested in motor control changes rather than weakness, and we reasoned that severely impaired patients may have greater masking of motor control capacity by concomitant weakness. Patients were excluded if they 1) were unable to understand and/or follow instructions, 2) had pain in shoulder or arm (visual analog scale ≥4), 3) had other neurological or musculoskeletal issues affecting the upper limb, 4) were unable to give informed consent, or 5) were under 18 yr of age. Kinematic data from 14 neurologically healthy control subjects (9 women, 5 men, mean age 60.8 ± 9.4 yr) recruited from the local community were used as the reference group for the kinematic analysis.
Ethics statement.
The study was conducted in accordance with the principles expressed in the Declaration of Helsinki. All participants signed a written consent form that was approved by the Columbia University Medical Center Institutional Review Board. The study is registered with ClinicalTrials.gov (NCT02331407).
Patients trained with their affected arm using a robotic device (ReoGo) (Fig. 1) that assisted them in various goal-directed reaching exercises. They received training 3 days a week for 3 consecutive weeks. On each day of training, there were two training sessions, each averaging 1.5 h in duration, separated by a break. Each session consisted of the patient sitting next to the ReoGo system, a robotic guide that extended near the subject's arm. The patient's arm was then attached to the robotic guide through a brace with Velcro straps. On the first day of testing, patients were fitted specifically to the device. During the therapy, the patients controlled a cursor on a computer monitor by moving the robotic guide and were instructed to move the cursor to targets that were highlighted.
The therapy was conducted according to predetermined protocols for low- and medium-functioning patients. Patients who were only able to abduct their arm <30° were considered low functioning, and those who had between 30 and 60° of arm abduction were considered medium functioning. The exercises included goal-directed tasks that required reaching to targets in 2D (controlling anterior/posterior and medio/lateral directions) or 3D (which had the addition of a vertical movement component) space. Nine different tasks were performed during the training sessions: forward thrust, horizontal reaching, forward reaching in 2D and 3D, horizontal abduction, making a circle, reaching in a star pattern, reaching in a zigzag pattern, and mimicking bringing a cup to the mouth.
The ReoGo has the capacity to operate in five modes of interaction: 1) Guided: the patient is 100% assisted by the robot but must be attentive to the passive movement; 2) Initiated: the patient correctly initiates the movement and then is 100% assisted to complete the task; 3) Step Initiated: the patient correctly initiates the movement, then is assisted for a short distance along a predefined trajectory, then is required to initiate the next segment of the trajectory; 4) Follow Assist: the patient is allowed to move along the correct predetermined trajectory while the robot assists to prevent deviation from this trajectory; and 5) Free: the patient completely controls the movement.
Separate protocols were followed for low- and medium-functioning patients, with prespecified tasks, number of repetitions, and degree of assistance for each session. Each week, the therapy protocol emphasized progressively more challenging movements, with an increase in the number of arm movement repetitions and a decrease in the amount of assistance from the robotic device.
Study design.
Clinical and kinematic assessments were performed at four time points: 1) 3 wk before therapy, 2) 1 wk before therapy, 3) after completion of therapy, and 4) 3 wk after therapy. The two assessments performed before the robotic intervention were to confirm that the patients had a stable baseline and to examine the contribution of practice effects, particularly for the planar reaching task.
Clinical outcome measures.
All clinical assessments were performed by a single occupational therapist blinded to the patients' performance during therapy. The primary clinical outcome measures were the FM (Fugl-Meyer et al. 1975) and the ARAT (Lyle 1981). Both of these tests are frequently used and have been shown to have good reliability, validity, and responsiveness to motor change in patients with chronic stroke (Gladstone et al. 2002; Hsieh et al. 2009; Lang et al. 2006; Yozbatiran et al. 2008).
The FM is a measure of impairment that considers movement arm, wrist, hand, and coordination. Each of the 22 items is scored on a three-point ordinal scale for a maximum score of 66. The ARAT tests hand and arm function and consists of 19 items in 4 domains: grasp, grip, pinch, and gross movement. Each domain contains items arranged into hierarchical order of difficulty such that success at the most difficult item of a specific subclass assumes success for all items lower in the hierarchy of the same class. Each item is scored on a four-point ordinal scale with a maximum score of 57.
Kinematics and motor control.
To assess the effect of robotic training on motor control of the upper extremity, patients were tested on an untrained planar reaching task, which has been previously described (Kitago et al. 2013). Subjects sat at a glass-surfaced table with their trunk securely belted to a high-backed chair. Table height was adjusted so that the shoulder and elbow were planar. The wrist, hand, and fingers were immobilized with a splint, which only allowed for movements of the shoulder and elbow. The forearm was supported using an air-sled system, which created a frictionless surface for movements. A mirror reflecting a computer display was placed just above the upper extremity so that the subject was unable to see his or her arm. Hand position was tracked in real time using Flock of Birds (Ascension Technology, Burlington, VT) magnetic movement recording system at a frequency of 120 Hz used to provide visual feedback.
Kinematic data from the hand, elbow, and shoulder were calculated and recorded using custom-written routines in RealBasic (Real Software, Austin, TX). The target set consisted of eight radially arrayed circles with a 1-cm radius, 45° apart, 8 cm from a center start circle. Each trial began after the subject held the cursor inside the start circle for 750 ms. Patients were instructed to make straight, out-and-back movements with a sharp reversal within the target. To ensure that movements were made quickly and to minimize online corrections, cursor feedback stopped after 200 ms, and the reversal point was indicated by a white square. Patients were given 1 or 2 practice runs of 88 movements for each arm to become familiar with the task. Patients then completed 2 experimental runs, each comprising 11 cycles of 8 targets, for each arm.
Data analysis.
Hand position data were analyzed using custom routines in MATLAB (Mathworks, Natick, MA). Position time series were low pass filtered (Butterworth filter) at 8 Hz. The first velocity peak above a threshold of 10 cm/s was identified for each trial. This threshold was chosen to exclude small movements made by some patients who had difficulty stabilizing their hands within the start circle. The start of the movement was defined as either the point at which the velocity crossed 1 cm/s or the first velocity minimum before the first velocity peak above 10 cm/s, whichever was later. The end point of the outward movement was defined as the reversal point, that is, the point where distance from the origin stopped increasing.
The following types of movements were excluded from analysis: movements that did not reach 30% of the distance to the target, movements without reversals, and spatial outliers (in which the movement direction was >90° from the target direction).
Functional principal component analysis.
Traditional kinematic analysis of limb trajectories relies on examining specific kinematic variables, such as directional error, smoothness, and end-point accuracy. The choice of variables is dictated by the hypotheses of the study. In the case of recovery from stroke, the range of potential changes in limb trajectory during recovery is not known a priori. Although some specific variables have been shown to change (e.g., number of submovements) (Rohrer et al. 2002), these were preselected based on specific questions about recovery. It would be desirable to examine trajectories at a global level with a method that is sensitive to any changes in overall movement quality, without preselecting a long list of variables and incurring the risk of unnecessary multiple comparisons. We therefore devised a novel method of trajectory analysis, based on functional principal component analysis (FPCA) (Goldsmith et al. 2013; Yao et al. 2005), to characterize reaching kinematics. This approach extends principal component analysis to time series data. Its main benefit is that it examines the entire trajectory and has sensitivity for changes undetected by conventional analyses that focus only on preselected measures such as end-point accuracy or peak velocity. It should be emphasized that FPCA will detect and incorporate all these kinematic features anyway.
We represent kinematic data as [Xi(t), Yi(t)], where Xi(t) and Yi(t) are the X and Y position of the hand at time t. FPCA expresses each motion as the combination of population-level components, selected to capture the major features of the kinematic data, and motion-specific weights or scores: (1) Here μX(t) and μY(t) are population mean functions, ϕkX(t) and ϕkY(t) are shared components, and the cikX and cikY are the motion-specific scores. The mean and shared components are estimated using all curves, and, given these, scores are estimated from individual trajectories. Interpretatively, ϕkX(t) and ϕkY(t) give a data-driven summary of the directions that reaching motions differ in the population, and the scores cikX and cikY quantify how these directions appear in a particular motion. Focusing on the scores cikX and cikY effectively reduces the dimension of the kinematic data; three scores for X and Y suffice to explain >99% of the observed variance in the kinematic data.
The distribution of reaching trajectories can be understood through the distribution of FPCA scores; differences comparing groups are apparent in shifts in the mean or changes in the variance of the scores. We compute the squared Mahalanobis distances [MDi2 = (ci − c̄)T ∑−1(ci − c̄)] for each score to measure the distance of each motion from the population average. MD2 is computed with respect to a reference population, which in this case is a collection of reaching trajectories from the dominant arm of a group of age-matched healthy older adults using the same kinematic task. Intuitively, MD2 is a generalization of the squared Z-score and quantifies the difference between motions made by healthy controls and subjects in this study. Subject-specific average squared Mahalanobis distances (AMD2) were computed for each subject at each target for each time point. FPCA analyses were carried out using R version 3.1.1 (R Development Core Team 2014).
Statistical analysis.
For each of the outcome variables (FM, ARAT, AMD2), we used repeated-measure ANOVA to detect differences between adjacent time points assuming constant variance; separate analyses were conducted for the affected and unaffected arm. Our primary focus was comparing the difference between the first two pretests to the difference between the second pretest and the posttest.
For the kinematic variable (AMD2), observations were made at each of eight targets at all time points. There were several analysis options: 1) to treat all targets as independent within subjects, 2) to treat all targets as uniformly correlated within subjects, and 3) to treat targets as uniformly correlated within subgroups of targets. The first analysis is the least restrictive but may neglect any within-subject correlation. The second analysis is the most restrictive in the sense of the assumed correlation structure. The final analysis balances these by assuming a reasonable correlation structure within target subgroups, according to whether they required movements at single or multiple joints. Previous studies have shown that multijoint reaching movements are particularly difficult for patients with stroke because of the need to account for interaction torques at the shoulder and elbow (Beer et al. 2000; Cirstea et al. 2003). Targets where either shoulder or elbow joint excursion accounted for >70% of the combined joint excursion were considered single-joint targets, whereas the remainder were considered multijoint targets. Each analysis is conducted using a generalized estimating equation framework for the assumed correlation structure and target subgroup.
An a priori power analysis based on effect size of 3.8 and SD of 4.3 in previously reported FM changes in chronic stroke (Kitago et al. 2013) was conducted, and we determined that 9 subjects would be sufficient to yield an observed power of 76%. We also conducted a power analysis on the trajectory variables to assess the probability of detecting a true alternative hypothesis. Effect sizes, variances, and correlation across targets for the trajectory analysis were determined from the comparison of healthy subjects to affected patients with stroke (Kitago et al. 2012). Using these values and still assuming 9 subjects, our expected power to detect a training effect on AMD2 of size 13.5 in the affected arm was 98.8%, assuming that targets are independent.
Table 1 shows a summary of the demographic and lesion characteristics of the nine patients who were enrolled in the study. All patients were able to complete the robotic therapy with no adverse events, and no patients were lost to follow-up. Over the 3 wk of therapy, both low- and medium-functioning patients performed an increasing number of repetitions with progressively less assistance from the robotic device and progressively more complex tasks, as seen in Fig. 2.
Robotic therapy had no demonstrable effect on clinical measures of impairment and function.
There were no significant differences between the two baseline FM values (pretest 1 = 30.3, pretest 2 = 32.8; P = 0.07), nor were there any significant differences before and after training (pretest 2 = 32.8, posttest 1 = 36.0; P = 0.07) (Table 2). Similarly, there were no significant differences in the baseline ARAT measures (pretest 1 = 19.6, pretest 2 = 21.3; P = 0.38), nor were there significant effects of training (pretest 2 = 21.3, posttest = 23.7; P = 0.29) (Table 2).
Movement times.
Movement times in the affected arm decreased from pretest 2 to posttest 1 (mean difference −33 ms, P = 0.02), but there was no significant change in movement times between pretest 1 to pretest 2 (mean difference −31 ms, P = 0.11) or between posttest 1 and posttest 2 (mean difference 8 ms, P = 0.55). In the unaffected arm, there was a significant decrease in movement times from pretest 1 to pretest 2 (mean difference −26 ms, P = 0.01) and between posttest 1 and posttest 2 (mean difference −15 ms, P = 0.00001), but there was no significant change in movement time with training between pretest 2 and posttest 1 (mean difference −2.9 ms, P = 0.70).
Reaching trajectories.
Figure 3 shows the reaching trajectories from a representative patient for both the affected (trained) and unaffected (untrained) arms. Mean AMD2 values for each testing session are shown in Fig. 4. Data for healthy control subjects are included in this figure for reference, but no statistical tests involving these values were conducted; the apparent heteroscedasticity comparing patients to controls does not affect the validity of our tests, which consider only within-group changes over time.
We analyzed the AMD2 outcome using the three methods described above: 1) independence across targets, 2) uniform correlation across all targets, and 3) uniform correlation in target subgroups (Fig. 5). The target subgroups we considered were single-joint and multijoint targets, defined by the degree of interjoint coordination used by healthy control subjects in reaching to these target directions. Decreases in AMD2 indicate that trajectories are more similar to those of healthy controls and represent improvements in control.
A total of 251 movements [2% of total movements, 3.5% (range 0–10.7%) of affected arm movements and 0.5% (range 0–1%) of unaffected arm movements] were rejected by our prespecified criteria. We also performed an analysis including all movements, without rejections, and obtained similar results (not shown).
Reaching skill improved in the robotically trained arm.
In the contralesional arm, there was a significant decrease in AMD2 with training (from pretest 2 to posttest 1) assuming independence across targets (mean difference −16.31, P = 0.0073). There was a decrease assuming uniform correlation although this failed to reach significance (mean difference −16.31, P = 0.077). Within the single-joint target subgroup, the decrease in AMD2 was significant (mean difference −24.28, P = 0.030) although, in the multijoint target subgroup, the decrease was not significant (mean difference −8.34, P = 0.348). Comparisons of the first and second pretest time points and of the first and second posttest time points were not significant under any analysis strategy. The former indicates that testing itself was not the cause of the improvements, and the latter indicates that the small robotic treatment effect on the control of reaching trajectories was sustained for 3 wk. In summary, there was a robust but small effect of robotic training on the control of visually guided reaches in the affected arm, which was more apparent with single-joint than multijoint reaches.
Reaching skill improved in the untrained arm with initial practice but not with robotic training.
In the ipsilesional untrained arm, there was a significant decrease in AMD2 between the first and second pretest assessments, assuming independence across targets (mean difference −3.05, P = 0.0001) and uniform correlation (mean difference −3.05, P = 0.042). Within the single-joint target subgroup, the decrease in AMD2 was significant (mean difference −3.17, P = 0.015) although, in the multi-joint target subgroup, the decrease was not significant (mean difference −2.93, P = 0.11). This pattern of improvement in the control of single-joint movements but not multijoint movements is similar to what we observed in the contralesional arm after robotic training. However, for the untrained arm, there was no significant change in AMD2 with robotic training (from pretest 2 to posttest 1) or between the first and second posttest time points under any analysis strategy. In summary, the untrained "unaffected" arm showed improvement with initial practice during testing on the kinematic task but did not further benefit from robotic training despite not being at ceiling (the skill level of healthy control subjects) (Fig. 4).
We sought to detect an effect of robotic therapy on motor control in patients with chronic hemiparesis after stroke. We found that there were improvements in the control of visually guided reaching trajectories in a planar task with the effects of gravity eliminated. There were no concomitant improvements in measures of impairment (FM) or function (ARAT) in the contralesional arm. These results illustrate that robotic training can lead to improvements in a motor skill in the absence of changes in standard clinical assessments.
The effects of robotic therapy on motor control in the current study were small but robust, with sustained improvements 3 wk later. Significant improvements were seen only for single-joint rather than multijoint movements. The same pattern of improvement was seen in the ipsilesional arm after practice of the task, suggesting that similar skill learning is occurring in both arms. This is interesting, as previous work, in healthy subjects and in patients with stroke, has shown that maintaining accuracy and path straightness is more challenging for multijoint compared with single-joint movements because of the need to compensate for interaction torques (Beer et al. 2000; Cirstea et al. 2003). Thus it appears that, after stroke, anisotropies attributable to limb dynamics are accentuated.
These improvements in motor control occurred without any significant increase in movement time. Improved trajectory accuracy for movements of the same or higher speed represents an improvement in the speed-accuracy tradeoff. The observed improvements thus imply that a form of motor skill learning has taken place (Reis et al. 2009; Shmuelof et al. 2012). There was no ceiling effect for the planar task, as healthy controls performed markedly better than the patients did even with their ipsilesional arm.
Previous studies of robotic therapy in patients with chronic hemiparesis have shown small effect sizes at the impairment level and none at the functional level (Kwakkel et al. 2008; Lo et al. 2010; Prange et al. 2006). Here we report significant but small effects only at the level of motor control. The magnitude in improvement in the FM in our study was comparable to what was found in two larger studies of robotic arm training in patients with chronic stroke, the VA ROBOTICS study (Lo et al. 2010) (3.9 points) and the recently published 3D robotics study (Klamroth-Marganska et al. 2014) (3.3 points). Although the lack of significant improvements in our clinical measures may be related to our small sample size, the absolute changes with training were small (3.2 points on the FM and 2.4 points on the ARAT) and unlikely to be clinically meaningful (Gladstone et al. 2002; Van der Lee et al. 2001). Reaching kinematics were not assessed in either of these aforementioned studies, therefore it is not possible to say whether the small improvements seen at the impairment level were accompanied by improvements in motor control.
The absence of significant effects with the ARAT and the FM could be interpreted to mean that the improvements in motor control were not large enough to generalize to either of these measures. That is to say, the motor control assay may be more sensitive to small effects of robotic training. Furthermore, the movements that are tested in ARAT and FM involve a combination of motor control, strength, and the use of compensatory strategies. Thus an improvement in motor control alone may not be sufficient to lead to improvements in these clinical measures.
Our study population encompassed a wide range of severity, with baseline scores ranging from 9 to 50 for the FM and from 0–38 for the ARAT. We explored the relationship between baseline clinical scores and the amount of improvement with training for the affected arm. Subjects with lower FM scores tended to have larger improvements with training, but, for the ARAT, subjects with higher scores tended to improve more with training although these correlations were nonsignificant. This study was not powered for subgroup analyses based on the severity of the motor deficits, but we found little evidence that the heterogeneity in our population was masking an improvement in the lower or higher functioning groups.
For the ipsilesional, untrained arm, no further improvement was seen after the 3 wk of training with the affected arm despite a persistent impairment compared with healthy control subjects. This lack of generalization to the untrained arm does not necessarily signify that motor learning has not occurred for the trained arm. Previous studies that have demonstrated improvements in both trained and untrained limbs have not examined the quality of the movements as we did in this study, with the exception of one primate study in which the animals were trained and tested with a planar reaching task (Georgopoulos et al. 1981). It may be that the magnitude of motor skill improvement in our study was not large enough to generalize to the untrained side or that, in patients with chronic stroke, the type of motor skill learning we tested is limb and task specific (Bavelier et al. 2012). Indeed, it is the assumption that rehabilitation is based on motor learning coupled with task specificity that has led to the emphasis placed on task-oriented training after stroke (Bayona et al. 2005; French et al. 2010; Hubbard et al. 2009; Schaefer et al. 2013).
The critical question is whether task-oriented training after stroke is merely exploiting normal learning mechanisms to increase skill within the performance envelope available to the patient. This would be comparable to a healthy person getting better at handwriting with their nondominant arm; it has a baseline level of performance that can be improved with practice. The core point is that healthy subjects and patients alike can augment performance to some degree on any task with practice. There is no need to invoke repair or reorganization. Thus the fundamental question raised by our results is whether the robotic training led to an increase in task-specific skill or to a general improvement in motor control. One possibility is that there are 2D task elements in the robotic training that are similar to the movements in the planar assay, which would mean that improvements that we observed can be attributed to task-specific skill. Alternatively, as mentioned already, the training could have had a more general effect on motor control, but it was too small to either generalize or be detected by the ARAT and FM. In the VA ROBOTICS study, there was a small effect of planar training on the FM, which might be taken as evidence for generalization from 2D reaches with gravity eliminated to 3D multijoint movements.
The ambiguity in ascertaining precisely what robotic therapy accomplishes arises because of the inherent difficulties of using task A (planar assay) to assess the effect of training with task B (robot). Task A can be viewed both as an assay for general motor control or a specific task that one can become more skilled at through training. As a hypothetical example, imagine two patients with stroke with hemiparesis. The first patient has a hemiparesis of moderate severity and is assessed on the planar reaching task before any rehabilitation is given. The second patient has more severe arm impairment and receives 2 wk of robotic training. This second patient is then assessed posttraining with the planar reaching task and is found to have exactly the same level of performance on it as the first patient. Thus the two patients now look phenotypically identical on the planar reaching task, but one patient required robotic training and the other did not. Are they phenotypically identical because the robotic training has partially reversed the second patient's more severe impairment, or has the robotic training only made the second patient a little more skilled at the planar task but is otherwise unchanged? This emphasizes the often unappreciated fact that pretraining correlation does not imply training covariation (Moreau and Conway 2014).
Ideally, one would have a battery of preestablished compensation-proof tasks with some a priori framework for how they differ from each other and from the training task. The question, however, of generalization of task-specific training is a vexed one because it presupposes that we have an a priori definition of task. If the degree of similarity between task A and task B is established via a transfer assay, then that same assay cannot be taken as evidence for generalization in the extrapolative sense because transfer occurred only to the degree that there was already overlap between tasks A and B within the part of parameter space trained. Thus transfer of learning across tasks can only be considered generalization if there is a separate assay for task similarity. In a recent study that looked at training on three tasks for the arm and hand, kinematics of the proximal limb was used as the measure of similarity across tasks. Interestingly, kinematic similarity did not predict the degree of transfer. The authors postulated that goal similarity might be the feature that matters instead. Goal, however, is a fuzzy concept; at one level, the goal is always to complete the task successfully, but successful task completion necessarily depends on the specifics of the task and its context. For example, in recent studies of split-treadmill adaptation after stroke, the poor generalization to overground walking has been taken as evidence for a context effect preventing transfer of what is a very similar locomotor pattern on and off the treadmill (Reisman et al. 2009; Torres-Oviedo and Bastian 2012). Finally, it needs to be recognized that rehabilitative training can lead to increased cardiovascular fitness and muscular conditioning, in addition to neural changes. The very small amount of generalization to the FM scale seen in the VA ROBOTICS study (Lo et al. 2010) could be attributable to strength increase in the proximal limb rather than motor-learning effects.
On balance we would tentatively conclude that the improvement in motor control in the planar reaching task after 3 wk of robotic therapy is because of some skill improvement at the task attributable to overlap with some of the planar components of robotic training. The lack of significant improvement in the FM and ARAT further supports our interpretation of a small increment in task-specific skill.
We have recently shown that constraint-induced movement therapy (CIMT) seems to promote functional recovery in chronic stroke mainly, if not exclusively, through compensation. Specifically, we showed that there was no discernible improvement in motor control, using the same planar reaching task as used in the current study, despite a clinically meaningful change in the ARAT (Kitago et al. 2013). Thus for CIMT the results were the opposite of those obtained here for robotic therapy, which suggests a dissociation for these two rehabilitation approaches with respect to gains in motor control vs. function, the latter presumably driven by compensation. This conclusion is not inconsistent with previously reported results, which overall suggest that robotic therapy exerts its small effects at the impairment level (Huang and Krakauer 2009; Kwakkel et al. 2008; Lo et al. 2010; Prange et al. 2006), whereas CIMT exerts its effects at the functional level (Kitago et al. 2013; Wolf et al. 2006).
In this study, patients with chronic hemiparesis who underwent 3 wk of 2D and 3D robotic training showed small but robust improvements in the control of reaching trajectories, which were assayed with an untrained planar task. The same pattern of skill improvement with practice was seen on the untrained ipsilesional side. That patients can show small increases in skill on any given task is hardly surprising, as to date there is no evidence that skill-learning mechanisms are impaired after stroke; hemiparesis is a motor control deficit (Krakauer 2006; Winstein et al. 1999). We conclude that training can eke out small task-specific performance improvements in motor control in patients after stroke through normal motor-learning mechanisms, which cannot reverse damage to the corticospinal tract or trigger reorganization. Generalization will only occur to the degree that the tasks share parts of command space. The much larger and much more general gains seen early after stroke are due to unique plasticity conditions in a limited time window that interact with training to enable reorganization and repair processes that are qualitatively and quantitatively distinct from normal learning (Zeiler and Krakauer 2013). Robotic therapy initiated within this time window might be able to augment such spontaneous biological recovery.
This work was supported by National Institutes of Health K02 NS048099 (J. W. Krakauer) and the Orentreich Family Foundation (J. W. Krakauer).
No conflicts of interest, financial or otherwise, are declared by the authors.
Author contributions: T.K., L.K., S.H., S.L.R., J.W.K., and V.S.H. conception and design of research; T.K., J.G., M.H., J.B., and V.S.H. analyzed data; T.K., J.G., M.H., J.B., P.M., and V.S.H. interpreted results of experiments; T.K., J.G., M.H., and J.B. prepared figures; T.K. and J.W.K. drafted manuscript; T.K., J.G., J.B., P.M., J.W.K., and V.S.H. edited and revised manuscript; T.K., J.G., M.H., P.M., J.W.K., and V.S.H. approved final version of manuscript; L.K., S.H., S.L.R., and V.S.H. performed experiments.
We thank Motorika Medical for supplying the ReoGo robotic device used in this study.
- Copyright © 2015 the American Physiological Society


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MORICHES - Officials say two men are recovering this morning after waves capsized their boats in Moriches Inlet.
Rescuers pulled Antonio Scrivanich, 75, from Centereach, from the water yesterday afternoon.
In a separate incident a few hours later, the Coast Guard pulled an unidentified 49-year-old man from the water.
News 12 Long Island has learned the rough water put the boats under and neither man was wearing a life jacket.
Both men are expected to be OK.

subset: commoncrawl


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Britney spears played a pank on simon cowell during filiming of the us xfactor. He was made to wear a girlie pink tiara lol
does it suit him?
Britneys manager Larry (em for fiance?) recieved a text from assistant wade (of the show)asking if britney needed anything. They text back asking for a straw hat,so wade went off to find a strawhat she then asked him fora tiara lol
He gave it to her while she was with all the other judges and turned the prank on to simon, and said i got this for you lol
what do you think of britney and her pranks?
Source link: http://www.dailymail.co.uk/tvshowbiz/article-2209296/Simon-Cowell-comes-girly-Britney-Spears-makes-wear-tiara-X-Factor-USA-joke.


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Trip Planner : Mexico / Central Mexico and Gulf Coast / Guanajuato / Guanajuato / Shopping / Hidalgo Market (Mercado Hidalgo)
Hidalgo Market (Mercado Hidalgo), Guanajuato
Categories: Flea Markets, Architectural Buildings, Shopping, Tourist Spots
The vibrant array of produce at Hidalgo Market (Mercado Hidalgo) will have you filling your bag with authentic Mexican food and gifts. Located within a vast iron structure originally intended to operate as a rail station, the market opened in 1910, coinciding with Mexico's centennial celebration of independence. This milestone helped coin the market's name after Miguel Hidalgo, a leader in the independence movement. Shopping with the locals across the three levels of the market, you will find many food vendors offering meals at very reasonable prices, or you can buy some produce to take with you. You'll find handcrafted gifts at many stalls, and as is the norm in Mexican markets, haggling is expected. Using our world travel planner, Guanajuato attractions like Hidalgo Market (Mercado Hidalgo) can form part of a personalized travel itinerary.
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Claudio K
Para quien se hospeda en una casa o por tiempos algo más prolongados, no hay nada mejor que comprar ingredientes de primera calidad en un mercado mexicano. Este es simplemente impecable como todos, bu... read more »For who is staying in a house or somewhat longer time, there is nothing better than buying ingredients of top quality in a Mexican market. This is simply impeccable as all good products, friendly people, local to admire culture and proper craftsmanship. You can buy papaya, mango and avocados for 4 people for less than $2. Oaxaca cheese! Exquisite and very cheap. Some tacos of carnitas (the foreigners not you added sauces by security) and a juice are a panorama missed.show original
La portada del mercado es una belleza, la parte interior es como cualquier mercado pero tiene magia: encontrarás fruta fresca, hermosa artesanía de todos los rincones de Guanajuato; trabajos en piel, ... read more »The cover of the market is a beauty, the inside is like any market but has magic: you will find fresh fruit, beautiful crafts from all corners of Guanajuato; works on skin, in ceramic, cardboard, wood, brass and more antique toys.show original
Patricio B
Local markets are where all the produce arrives from around the state as well as a huge selection of arts and crafts that gets to be mind boggling. Local sweets, hand woven clothing, and just about an... read more »
Omar Fierros
Awesome market full fruits and veggies, also a great place to buy local arts and crafts.
Alfredo Sánchez Mejorada Herrera
buen mercado
Robert Eriksson
Excellent and very varied market. In one corner, there are guys chopping huge chunks of meat, while in the middle you can get some good and cheap milkshakes. Clothing and other items are on the balcony that surrounds the ground floor.
Robert Cooke
This ticks all the boxes for Mexican markets leaning slightly towards the touristy side. It has food, stalls and everything you could like. Worth checking out.
Raoul Grasman
Interesting vibrant market with all kinds of stuff. Seems to target both locals and tourists.
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Employers offering the most DY Manager Engineer-related jobs are Mahindra Logistics Ltd, Technosoft Global Services., Bangalore Secretary Service, Indian Job career services private limited, Matrix Clothing Pvt. Ltd. or Nine Digital..
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Neuvoo India is the largest job site in the country with over 1465546 job vacancies available, 578 of which are DY Manager Engineer-related.Show more...
Vodafone |
Bangalore, Karnataka
- 12d ago
CCNP CCIP ALU Juniper Certification. Desired. Bachelors of Engineering in Electronics & Communication... CCNP. CCIE Qual is desirable but not mandatory if engineer can demonstrated in experience and in...
Krishna |
Gurgaon, Haryana
- 13d ago
Production, Manufacturing, Maintenance. Role Category. Service Maintenance Engineer. Role. Service... Ability to generate maintenance information and respond to questions from vendors, managers and...
Krishna |
Gurgaon, Haryana
- 18h ago
Candidate must have strong analytical, documentation and mathematical skills in an engineering auto... Role Category. Quality Assurance Quality Control Manager. Role. Quality Assurance Quality Control...
Jamnagar, Gujarat
- 13d ago
Salary. 1,200,000. 1,700,000 INR (PA). Experience. 13 to 22 Years. Industry. Engineering... Production. Service Engineering. Manufacturing. Maintenance. Key Skills. PROJECT MANAGER COMMISSIONING...
Career Usher |
Dahej, Gujarat
- 4d ago
Role Environment Engineer Officer. Keyskills. Environment Manager Environment Dy. Manager Environment... Manager Environment. Desired Candidate Profile. Education. UG. B.Tech B.E. Any Specialization, Chemical...
Aarvi Encon Private Limited |
Varanasi, Uttar Pradesh
- 15d ago
Opening For Dy Manager Sr Engineer Civil with a PSU Company Job Profile Dy Manager Sr Engineer Civil Job Location Garhmukteshwar Kanpur Allahabad Mathura Varanasi No Location Preference Job...
Right Choice Placement Consultant |
(Unspecified city), Delhi
- 8d ago
Looking for Any Graduate. Post Graduate graduates profile. Qualities Needed for This Jobs DY Manager. process...
Jet Propulsion Laboratory |
Ahmedabad, Gujarat
- 4d ago
Job Description. Job Description. Planning. Senior Manager. Manager. Dy. Manager. Senior Engineer... Engineer. Qualification. Graduate in Mechanical Civil Electrical engineering. Experience. 3. 15 years in...
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What is the speed limit on Hwy 81 in York Ne?
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LeBron James Denies 'Space Jam 2' Rumor
Rumor suggesting that LeBron James would star in "Space Jam 2" was denied by the NBA player's camp. Despite the swirling report, ESPN's Brian Windhorst tweeted, "Well it was fun while it lasted. LeBron sources refute Deadline report, there's no Space Jam 2 or Warner Bros. project in works."
Deadline previously reported that the long-awaited sequel to 1996's animated/live-action mash-up movie "Space Jam" was developed by Charlie and Willie Ebersol, the sons of sports broadcasting veteran Dick Ebersol, as a starring vehicle for the Miami Heat player.
Charlie who previously worked with the NFL was rumored to serve as a producer, while his brother Willie who won an Emmy for the London Olympics would reportedly handle the scriptwriting. The news emerged months after a fake poster for a rumored "Space Jam 2" film starring James hit the web.
Directed by Joe Pytka, the original "Space Jam" movie starred Michael Jordan and Looney Tunes characters. Legendary players like Larry Bird, Patrick Ewing and Charles Barkley supported the flick along with Hollywood stars such as Danny DeVito and Bill Murray. It raked in more than $230 million internationally.
The film's soundtrack was also a winner. While the album was certified at least 6x Platinum, one of the tracks in the CD, R. Kelly's "I Believe I Can Fly", hit the top of the charts and earned him two Grammys.
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Changing mindsDiscrete Mathematics Level 4
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Talent Leads Hr Solutions Pvt Ltd |
Mumbai, Maharashtra
- 10d ago
Key Skills. Visualiser, Illustrator, Product Launch. Qualification. Other Bachelor Degree. Salary (Per Annum). 7 Lac 50 Thousand To 10 Lac. Work Experience. 3. 7 Years. Job Requirement...
Quotient Four Technologies Pvt. Ltd. |
Gurgaon, Haryana
- 6d ago
This could range from a small micro site to a complete social media app. A Sr Visualizer will also work on everything from ideation to execution of various campaigns based on requirement for...
Quotient Four Technologies Pvt. Ltd. |
New Delhi, Delhi
- 4d ago
This could range from a small micro site to a complete social media app. A Sr Visualizer will also work on everything from ideation to execution of various campaigns based on requirement for...
Quotient Four Technologies Pvt. Ltd. |
Gurgaon, Haryana
- 4d ago
Job Description. Primary responsibilities of a Sr. Visualizer will include working on online collaterals... also work on everything from ideation to execution of various campaigns based on requirement for...
Talent Corner Hr Services Private Limited |
Mumbai, Maharashtra
- 9d ago
Designation. Sr. visualizer. Industry. Media and Advertising. Experience. 4. yrs. Salary. Best as per... would be an added advantage. Very Urgent Requirement. If Your Profile Matches The Above Requirement And...
Rci India Pvt Ltd |
Bangalore, Karnataka
- 10d ago
Job Description. Visualizer is a specialist role and would be part of the studio, conceptualsing and... The visualizer would be responsible conceptualisng requirements in the marketing calendar and...
Le Human Resources Solutions Pvt Ltd |
Mumbai, Maharashtra
- 12d ago
Job Description. Dear. Greeting from Le HR Solutions Pvt Ltd. We have urgent requirement for 3D... Position. 3D Visualizer. Location. Mumbai. Projects. Construction. Real Estate. Candidate need to...
Talent Corner Hr Services Private Limited |
Thane, Maharashtra
- 12d ago
JOB DESIGNATION. œ. Visualizer. INDUSTRY. Marketing and Advertising. JOB LOCATION. Mumbai (Andheri... Effectively coordinating with the client servicing team to understand the client. s requirement and...
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Fluttering feeling in genital area. On birth control pills. Cause?
I'm having a weird fluttering feeling in my genital area. No pain, just fluttering. I'm menstruating currently but this has never happened before during menstruation or otherwise. I do take birth control pills but have taken them for yers with no such trouble. Should I be worried or is it just like a pinched nerve or something?
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As there are no other symptoms like burning sensation, itching, foul smelling dischare no need to worry for now as this has just started. But kindly get examined by your gynaecologist as you are taking pills for years. Routing check up for the same is required..Have a good health.
Thanks and regards
Dr. Lohit
Answered: Sun, 23 Jun 2013
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Hi Thanks for using HCM,
As there are no other symptoms like burning sensation, itching, foul smelling dischare no need to worry for now as this has just started. But kindly get examined by your gynaecologist as you are taking pills for years. Routing check up for the same is required..Have a good health.
Thanks and regards
Dr. Lohit
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In a surprising ruling, the Italian Supreme Court ruled that masturbating in public is not a crime, even if it is done with the clear aim of being seen by other members of the public.
The case involved a 69-year-old man who had been caught masturbating in Catania. He had earlier been convicted after he was seen 'taking out his penis' and 'practising autoeroticism' in front of students at the University of Catania campus.
The local Prefect of Catania and the Court of Appeal had agreed that the man should be sentenced to three months in prison and fined €3,420. However, the Supreme Court judges decided that a recent government reform meant "the act is not included in the law as a crime".
The ruling by the highest court has in effect eliminated the criminal aspects of sentencing for obscene acts in public places. However, the man identified only as Pietro L, will now go back to the Prefect of Catania to be sentenced again. The court held that the man must be given a fine between €5,000 and €30,000, with the exact figure to be determined by the local court.
Famous porn site's account holders exposed by hackers
In deciding the case, the Supreme Court judges noted the fact that the Italian parliament had passed a law last year decriminalising the offence of lurking in places frequented by girls in order to be seen masturbating.
There have been other such cases around the world, for example, that of a Swedish man caught masturbating on a beach on Stockholm. The man was acquitted of sexual assault on the basis his actions were not directed towards a specific person.
Courtesy : Express Tribune


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text:
Becker Heating & Air
5210 Country Aire Loop, Greenwood, AR 72936
(479) 996-8400
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Street address:
5210 Country Aire Loop
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ZIP code:
(479) 996-8400
GPS Longitude:
GPS Latitude:
Places nearby
1.31 miles away
Wood Products, Nec
1.78 miles away
Excavation Work
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Business data
|Standard industrial classification code:
|Estimated number of employees:
|Annual sales estimate:
|City / suburb:
|Greenwood, AR
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According to our records, this business is located at 5210 Country Aire Loop in Greenwood (in Sebastian County), Arkansas 72936, the location GPS coordinates are: 35.208983 (latitude), -94.345364 (longitude). Becker Heating & Air is categorized under Plumbing, Heating, Air-Conditioning (SIC code 1711). Current estimates show that the unit has a sales volume of $564,000 and staff of approximately 3 people. You can contact the company by phone at (479) 996-8400.
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text:
Redmond's Own AFH
Redmond, WA 98052
Schedule an appointment
Contact a senior living advisor
Contact a senior living advisor
About Redmond's Own AFH
Redmond's Own AFH offers the best of both worlds: the same comfort as if you were living on your own, and the comfort of knowing a helping hand is there when you need it. It offers great ammenities such as and . Conveniently located in Redmond, Washington, residents at Redmond's Own AFH love knowing that sightseeing and other fun activities are always within reach. Redmond's Own AFH is a one-of-a-kind assisted living facility, offering the best level of care that money can buy - at a surprisingly affordable price. There are many factors to consider when choosing an assisted living center for yourself or an elder loved one - and you may find that Redmond's Own AFH has everything you need.
Affordable Rates based on the needs of the resident.
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Call (877) 311-3048
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"I can't thank you enough for all your help during this process. You were the first call I made, and the last one I needed to make."
"I was at the end of my rope the day I heard from you and you helped me more in that one phone call than I was able to find alone for 6 months. You gave me hope..."
Call Now (877) 311-3048


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text:
how to play them...
how to play them...
***look hot stay cool***
Are you asking just for the scales?
And surely youll buy your pint cup !
and surely Ill buy mine !
And we'll take a cup o kindness yet,
for auld lang syne.
yeah i saw some guitar beginner lessons website but couldnt find the blues and pentatonic scales...and i dont know exactly when to use them...coz most of the times heptatonic scales are used...
are there different set of chords for those scales?
***look hot stay cool***
What is blues?
Its a typical chord progression (comprises of Major or Dom7th) - I IV V I style.
What do you play over it? The blues scale = pentatonic minor scale with an added "blues note" (which is usually bent up a semitone while playing).
So what is unique about Blues music?
You play minor scale melodies over major scale chords.
(if I = A maj, then you play A minor pentatonic)
and listen to 1-2 tracks of:
1. BB King
2. John Lee Hooker
3. Stevie Ray Vaughn
4. Kenny Wayne Shepherd
You will understand it.
You dont get what you deserve, you get what you negotiate.
how to play minor pentatonic scale.i dont know to play pentatonic scales...and whats will be the blues note...i only know the mixolydian mode is some way related to blues
btw how to distinguish blues and rock music
***look hot stay cool***
do we use heptatonic scales while playing blues or only pentatonic scales...
***look hot stay cool***
on the left Eminor pentatonic
right E blues scale starting from the 6th string
you can move it to any position and then it will become the minor pentatonic or blues scale of that note
For example if u play the same thing on 10th fret it will be a D minor pentatonic or D blues scale
i hope i am right
Green Skreamer Video Demo:-https://www.youtube.com/watch?v=F_nVh4C-Y-4
New Sound:-
Basic Instrumental:-https://soundcloud.com/prateek-koul/basic-instrumental
Youtube Channel:-http://www.youtube.com/user/guitarplayer729?feature=CAQQwRs%3D
Guitars:- Cort KX5 Fr, Java EG-11, Givson G-215
Amplifier:- Laney LX12
Effects:- Boss Metal Zone, Digitech RP355, Zoom G1XN(for sale), Green Skreamer
I am asking a few questions out of curiosity......
What scales do you know to play, Major Scales?
What Minor scales have you played or know how to play?
Why do i feel that you have your feet on multiple grounds at the same time? Just my opinion....
I'd recommend a good book to learn scales and modes, but i would like to let you know to ensure that you are learning ONE thing at a time, and not tooo many things at once....
PM me your email ID, i shall email you the book
Guitars - Epiphone Les Paul Standard Plain Top, GB&A Strat, Yamaha C70
Amp - Laney Cub 10 (FOR SALE), Blackheart Little Giant Head, 1X12 Cab (DIY) w/ Eminence Governor Speaker
Pedals - Vox Satchurator, Boss ME-25, EHX LPB-1 - DIY, Marshall Plexi Pedal (DIY), TS-808 (DIY)
**Arya Pedals makes custom pedals just the way you need it, and for a price that does not break your bank**
**Reach out at http://www.facebook.com/AryaPedals or email - aryasridhar(at)gmail.com, or PM me on IGT.**
i need the formula for blues and pentatonic scales
like major is WWHWWWH
and minor is b3 b6 b7th of the major scale
W-whole note
H-half note
***look hot stay cool***
Minor Pentatonic - Consists of the same 5 notes of a major pentatonic scale but its tonic (first note of the scale} is 3 semitones below the tonic of the major pentatonic scale. For example, the C major pentatonic (C - D - E - G - A} has the same notes as the A minor pentatonic (A - C - D - E - G} but arranged differently. The first note or tonic of the A minor pentatonic scale (=A) is 3 semitones (half steps) lower than the first note of the C major pentatonic scale (=C). It uses the 1st - minor 3rd - 4th - 5th - minor 7th notes of a scale.
well i know major, minor, harmonic minor ,melodic minor as well as modes ionian,dorian,phrygian,lydian,mixolydian,aeolian,l ocrian...
***look hot stay cool***
Do you understand what you had asked for and what i have replied?
ow i got it and what about blues scale ...
***look hot stay cool***
@aryasridhar -are you jealous of me that without composing songs i've become a composer haha
***look hot stay cool***


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Headache and Migraines
MRI done to know the source of migraine headache. What does report says?
My results from a recent MRI without contrast indicate: minimal ischemic/gliotic changes vs findings related to migraine headaches . In an earlier part of the report, it is stated: there are a few dot-like foci of increased T2 signal in the deep periventricular white matter regions... ischemic changes also noted involving the central pontine region as well. The MRI was done to find the source of migraine headaches. Mary Ellen Drury
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Sat, 26 Jan 2013
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General & Family Physician
Dr. Alekhya
Thank you for the query. I have gone through your query and understood your concerns. Ischemic changes indicates decreased blood supply to that area and by which you are having
. I advice to take prophylactic treatment for this after consulting your doctor and for ischemic changes also you need to be treated.
Consult a neurologist
first to examine you.Thank you.
Answered: Fri, 11 Oct 2013
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Are you sure you want to delete this answer?
Edit Answer here...
Thank you for the query. I have gone through your query and understood your concerns. Ischemic changes indicates decreased blood supply to that area and by which you are having migraine headaches. I advice to take prophylactic treatment for this after consulting your doctor and for ischemic changes also you need to be treated. Consult a neurologist first to examine you.Thank you.
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|Job Ref:
|Job Type:
|United Kingdom
|Post Code:
|£45000 - £50000/annum £45,000 to £50,000 + car & more
|Post Date:
|09/10/2016 03:27
Job Title: Service Delivery Area Manager
Location: Sandhurst, Camberley
Salary: £45,000 to £50,000 + car
Our client is a leading supplier of facility services to the Ministry of Defence and they now have an immediate requirement for a Service Delivery Area Manager to be based at their military site in Sandhurst, Camberley.
You will manage the Property Maintenance of all sites within your area of responsibility and operate as the immediate escalation point for site level operational and delivery issues. This will involve ensuring the Supply Chain performance meets with all statutory, mandatory and reactive performance indicators are consistently achieved within area of responsibility.
Although not essential candidates who have previously served in the Armed Forces i.e. British Army, Royal Navy or Royal Air Force (RAF) or worked within the Ministry of Defence (MoD) could be of particular interest. Candidates will have a demonstrable management background in Construction, Civil or Building Engineering.
- Manage service delivery of all maintenance and response works in accordance with statutory
legislation and MoD Mandatory requirements, complying with all Health and Safety and
Environmental standards and policies.
- Ensure appropriate work plans and budgets are in place to achieve programmes and financial
commitments, whilst meeting the changing operational need.
- Ensure all documentation relating to maintenance is distributed in a timely manner and recorded
against the appropriate assets on our client's system.
- Identify risks and provide appropriate measures to mitigate the impact.
- Control an Authorised Persons diary to ensure maximum output and continued compliance
throughout the Service Delivery Area.
- Identify opportunities on establishments that will support the MoD's carbon reduction targets. Lead
service delivery and Additional Works to incorporate sustainable solutions and support the
sustainability agenda.
- Ensure that all AWS up to the value of £25k and those that are delivered by Site teams are
delivered within agreed timelines and to ensure the efficient operation of a system of reporting of
the physical progress of these Additional Works.
Applicant requirements:
- HND level qualification in a Building/Civil Engineering or Electrical/ Mechanical Engineering or a related discipline or equivalent experience.
- Management level qualification in H&S and Environment (e.g. SMSTS)
- Continuing Professional Development
- Significant practical management in Construction, Property Maintenance or related field.
- Demonstrable experience leading an operational team to achieve KPIs.
- Ability to maintain strong relations with the customer.
- Planning, directing and controlling activities.
- Proactive performance management of Supply Chain.
- Experience of leading multi-site operations, including agreeing scope and priorities of work.
- Proactive performance management and continuous improvement.
- Significant experience in Construction, Property Maintenance or related field.
- Experience of operating in an MOD environment.
- Working knowledge of CDM regulations.
- Experience of the Asbestos at Work Act, DDA, energy performance, Sustainability etc.
- NEC3 contract requirements
- £45,000 to £50,000 annual salary.
- 25 days holiday plus Bank Holidays.
- Company Vehicle.
- Pension Scheme.
- Challenging and varied working environment