Robot-based hand motor therapy after stroke.

Robots can improve motor status after stroke with certain advantages, but there has been less emphasis to date on robotic developments for the hand. The goal of this study was to determine whether a hand-wrist robot would improve motor function, and to evaluate the specificity of therapy effects on brain reorganization. Subjects with chronic stroke producing moderate right arm/hand weakness received 3 weeks therapy that emphasized intense active movement repetition as well as attention, speed, force, precision and timing, and included virtual reality games. Subjects initiated hand movements. If necessary, the robot completed movements, a feature available at all visits for seven of the subjects and at the latter half of visits for six of the subjects. Significant behavioural gains were found at end of treatment, for example, in Action Research Arm Test (34 +/- 20 to 38 +/- 19, P< 0.0005) and arm motor Fugl-Meyer score (45 +/- 10 to 52 +/- 10, P < 0.0001). Results suggest greater gains for subjects receiving robotic assistance in all sessions as compared to those receiving robotic assistance in half of sessions. The grasp task practiced during robotic therapy, when performed during functional MRI, showed increased sensorimotor cortex activation across the period of therapy, while a non-practiced task, supination/pronation, did not. A robot-based therapy showed improvements in hand motor function after chronic stroke. Reorganization of motor maps during the current therapy was task-specific, a finding useful when considering generalization of rehabilitation therapy.

Space cycle: a human-powered centrifuge that can be used for hypergravity resistance training.

INTRODUCTION: This study represents the first step toward testing the hypothesis that hypergravity can be used as a unique resistance training modality for maintaining the health and function of skeletal muscle in microgravity. The primary objectives of this study were to use a human-powered short-arm centrifuge for the following: 1) to determine whether subjects could perform squats under hypergravity conditions without developing motion sickness or illusory motion; 2) to measure foot forces while performing squats under hypergravity conditions; and 3) to determine the mechanical power required to produce 1.5, 2.0, 2.5, and 3.0 Gz (head to foot) at the feet. METHODS: Subjects (22 males and 19 females) performed 10 squats each at 1.5, 2.0, 2.5, and 3.0 Gz on a human-powered short-arm centrifuge, the space cycle. Foot forces during each squat were monitored using insole force sensors, and normalized to foot forces measured at 1 Gz (relative foot forces). RESULTS: Illusory motion was minimized using a visual focal point, and did not affect the ability of subjects to perform squats. The mean standing relative foot forces at 3.0 Gz were 2.3 and 2.4 for the male and female subjects, respectively. The work rate required to power the space cycle was a linear function of Gz, and is well within the aerobic scope of untrained individuals. DISCUSSION: The findings of this study demonstrate that hypergravity can be used as an effective modality for loading skeletal muscle and that subjects can perform squat resistance exercise without developing motion sickness or illusory motion.

Impaired motor control in patients with benign focal epilepsy of childhood.

Upper extremity motor function was quantitatively assessed in 6 children (age 7-11 years) treated with antiepileptic drugs for benign focal epilepsies of childhood and compared with that of 30 age-matched normal children. Both motor performance and adaptation to perturbing mechanical constraints imposed by a robotic device were significantly impaired in children with benign focal epilepsies of childhood. Our findings thus question whether certain "benign" epilepsies are truly benign and whether pharmacologic treatment might contribute to motor impairment.

Effect of muscle fatigue on internal model formation and retention during reaching with the arm.

The motor system adapts to novel dynamic environments by forming internal models that predict the muscle forces needed to move skillfully. The goal of this study was to determine how muscle fatigue affects internal model formation during arm movement and whether an internal model acquired while fatigued could be recalled accurately after rest. Twelve subjects adapted to a viscous force field applied by a lightweight robot as they reached to a target. They then reached while being resisted by elastic bands until they could no longer touch the target. This protocol reduced the strength of the muscles used to resist the force field by approximately 20%. The bands were removed, and subjects adapted again to the viscous force field. Their adaptive ability, quantified by the amount and time constant of adaptation, was not significantly impaired following fatigue. The subjects then rested, recovering approximately 70% of their lost force-generation ability. When they reached in the force field again, their prediction of the force field strength was different than in a nonfatigued state. This alteration was consistent with the use of a higher level of effort than normally used to counteract the force field. These results suggest that recovery from fatigue can affect recall of an internal model, even when the fatigue did not substantially affect the motor system's ability to form the model. Recovery from fatigue apparently affects recall because the motor system represents internal models as a mapping between effort and movement and relies on practice to recalibrate this mapping.

Stroke recovery and its imaging.

Functional imaging of stroke recovery is a unique source of information that might be useful in the development of restorative treatments. Several features of brain function change spontaneously after stroke. Current studies define many of the most common events. Key challenges for the future are to develop standardized approaches to help address certain questions, determine the psychometric qualities of these measures, and define the clinical usefulness of these methods.

Modeling reaching impairment after stroke using a population vector model of movement control that incorporates neural firing-rate variability.

The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target. Both between- and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between- and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between- and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke.

Neuromotor noise limits motor performance, but not motor adaptation, in children.

Children do not typically appear to move with the same skill and dexterity as adults, although they can still improve their motor performance in specific tasks with practice. One possible explanation is that their motor performance is limited by an inherently higher level of movement variability, but that their motor adaptive ability is robust to this variability. To test this hypothesis, we examined motor adaptation of 43 children (ages 6-17) and 12 adults as they reached while holding the tip of a lightweight robot. The robot applied either a predictable, velocity-dependent field (the "mean field") or a similar field that incorporated stochastic variation (the "noise field"), thereby further enhancing the variability of the subjects' movements. We found that children exhibited greater initial trial-to-trial variability in their unperturbed movements but were still able to adapt comparably to adults in both the mean and noise fields. Furthermore, the youngest children (ages 6-8) were able to reduce their variability with practice to levels comparable to the remaining children groups although not as low as adults. These results indicate that children as young as age 6 possess adult-like neural systems for motor adaptation and internal model formation that allow them to adapt to novel dynamic environments as well as adults on average despite increased neuromotor or environmental noise. Performance after adaptation is still more variable than adults, however, indicating that movement inconsistency, not motor adaptation inability, ultimately limits motor performance by children and may thus account for their appearance of incoordination and more frequent motor accidents (e.g., spilling, tripping). The results of this study also suggest that movement variability in young children may arise from two sources--a relatively constant, intrinsic source related to fundamental physiological constraints of the developing motor system and a more rapidly modifiable source that is modulated depending on the current motor context.

Hemiparetic stroke impairs anticipatory control of arm movement.

Internal models are sensory motor mappings used by the nervous system to anticipate the force requirements of movement tasks. The ability to use internal models likely underlies the development of skillful control of the arm throughout life. It is currently unknown to what extent individuals with hemiparetic stroke can form and implement such internal models. To examine this issue, we measured whether such individuals could learn to anticipate forces applied to their arms by a lightweight robotic device as they practiced reaching to a target. Thirteen subjects with post-stroke hemiparesis were tested. Forces were applied to the arm, which curved the hand path in either the medial or lateral direction, as the subjects reached repeatedly towards a target located in front of them at their workspace boundary. The subjects exhibited a decreased ability to adapt to the perturbing forces with their hemiparetic arms. That is, they did not straighten their reaching path as well, compared to their ipsilesional arms, and they exhibited smaller aftereffects when the perturbing force was unexpectedly removed. The ability to adapt to the force improved significantly with decreasing impairment severity, as quantified using both clinical scales and quantitative strength measurements. Some subjects with strength reductions as severe as 60% were able to adapt to the fields, generating significant aftereffects. We conclude that hemiparetic stroke impairs the ability to implement internal models used for anticipatory control of arm movement, although even some severely weakened subjects retain at least a partial ability to form and use internal models. Finding ways to fully restore this adaptive ability, or to make use of what adaptive ability remains during rehabilitation, is an important goal for improving functional motor recovery.