Reengineering Biomedical Engineering Curricula: A New Product Development Approach

Product development engineers in medical industries have created design control procedures to ensure high quality designs that are as error-free as possible. The reason is simple; companies must adhere to certain engineering and manufacturing best practices in order to obtain certification of their devices for sale in the US and abroad. We describe here an ongoing effort to apply these industrial best practices to the design and implementation of a novel sequence of undergraduate biomedical computing courses within the Department of Bio-medical Engineering at Marquette University (Milwaukee, Wisconsin). We have tightly integrated our industrial advisory board into this design and development effort. The board has contributed to significantly to the orderly generation of curricular requirements, the development of course implementation designs and the evaluation of these designs per requirements

Elastic, Viscous, and Mass Load Effects on Poststroke Muscle Recruitment and Co-contraction During Reaching: A Pilot Study

Background: Resistive exercise after stroke can improve strength (force-generating capacity) without increasing spasticity (velocity-dependent hypertonicity). However, the effect of resistive load type on muscle activation and co-contraction after stroke is not clear. Objective: The purpose of this study was to determine the effect of load type (elastic, viscous, or mass) on muscle activation and co-contraction during resisted forward reaching in the paretic and nonparetic arms after stroke. Design: This investigation was a single-session, mixed repeated-measures pilot study. Methods: Twenty participants (10 with hemiplegia and 10 without neurologic involvement) reached forward with each arm against equivalent elastic, viscous, and mass loads. Normalized shoulder and elbow electromyography impulses were analyzed to determine agonist muscle recruitment and agonist-antagonist muscle co-contraction. Results: Muscle activation and co-contraction levels were significantly higher on virtually all outcome measures for the paretic and nonparetic arms of the participants with stroke than for the matched control participants. Only the nonparetic shoulder responded to load type with similar activation levels but variable co-contraction responses relative to those of the control shoulder. Elastic and viscous loads were associated with strong activation; mass and viscous loads were associated with minimal co-contraction. Limitations: A reasonable, but limited, range of loads was available. Conclusions: Motor control deficits were evident in both the paretic and the nonparetic arms after stroke when forward reaching was resisted with viscous, elastic, or mass loads. The paretic arm responded with higher muscle activation and co-contraction levels across all load conditions than the matched control arm. Smaller increases in muscle activation and co-contraction levels that varied with load type were observed in the nonparetic arm. On the basis of the response of the nonparetic arm, this study provides preliminary evidence suggesting that viscous loads elicited strong muscle activation with minimal co-contraction. Further intervention studies are needed to determine whether viscous loads are preferable for poststroke resistive exercise programs

A Pneumatically Actuated Manipulandum for Neuromotor Control Research

Functional magnetic resonance imaging (fMRI) techniques have great potential for identifying which neural structures are involved in the control of goal-directed reaching movements. However, fMRI techniques alone are not capable of probing the neural mechanisms involved in acquisition of novel motor behaviors because such studies require that the moving limb be perturbed in a controlled fashion. We outline a plan to design and develop a non-metallic, pneumatically actuated tool that, along with systems identification techniques and functional magnetic resonance imaging (fMRI), will characterize and quantify how the human central nervous system uses sensory information during practice-based motor learning

The Arm Motion (AMD) Detection Test

Stroke can lead to sensory deficits that impair functional control of arm movements. Here we describe a simple test of arm motion detection (AMD) that provides an objective, quantitative measure of movement perception related proprioceptive capabilities in the arm. Seven stroke survivors and thirteen neurologically intact control subjects performed the AMD test. In a series of ten trials that took less than 15 minutes to complete, participants used a two-button user interface to adjust the magnitude of hand displacements produced by a horizontal planar robot until the motions were just perceptible (i.e. on the threshold of detection). The standard deviation of movement detection threshold was plotted against the mean and a normative range was determined from the data collected with control subjects. Within this normative space, subjects with and without intact proprioception could be discriminated on a ratio scale that is meaningful for ongoing studies of degraded motor function. Thus, the AMD test provides a relatively fast, objective and quantitative measure of upper extremity proprioception of limb movement (i.e. kinesthesia)

Learning Redundant Motor Tasks With and Without Overlapping Dimensions: Facilitation and Interference Effects

Prior learning of a motor skill creates motor memories that can facilitate or interfere with learning of new, but related, motor skills. One hypothesis of motor learning posits that for a sensorimotor task with redundant degrees of freedom, the nervous system learns the geometric structure of the task and improves performance by selectively operating within that task space. We tested this hypothesis by examining if transfer of learning between two tasks depends on shared dimensionality between their respective task spaces. Human participants wore a data glove and learned to manipulate a computer cursor by moving their fingers. Separate groups of participants learned two tasks: a prior task that was unique to each group and a criterion task that was common to all groups. We manipulated the mapping between finger motions and cursor positions in the prior task to define task spaces that either shared or did not share the task space dimensions (x-y axes) of the criterion task. We found that if the prior task shared task dimensions with the criterion task, there was an initial facilitation in criterion task performance. However, if the prior task did not share task dimensions with the criterion task, there was prolonged interference in learning the criterion task due to participants finding inefficient task solutions. These results show that the nervous system learns the task space through practice, and that the degree of shared task space dimensionality influences the extent to which prior experience transfers to subsequent learning of related motor skills

Sensory Motor Remapping of Space in Human-Machine Interfaces

Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices

Characterization of Motor Adaptation and Limb Posture Regulation During Arm Reaching Movements Following Stroke

Whether attempting to pour water into a handheld glass, or simply trying to hold a young child\u27s hand, many activities of daily living require interaction with unpredictable or uncertain mechanical environments. Here we describe a systems identification study that used a planar manipulandum to characterize how hemiparetic stroke survivors adapt reaching movements to novel mechanical environments. By analyzing trial-by-trial variations in hand path kinematics, we found that stroke survivors are less likely than neurologically-intact subjects to adjust motor commands for upcoming movements based on hand trajectory errors experienced on previous trials. This ability is most significantly compromised in subjects with Fugl-Meyer scores ≤ 20. The ability to terminate movement accurately at the desired target was significantly compromised on the impaired side for most stroke survivors. This measure of performance contrasts with the trajectory updating measure in that it did not depend on impairment level. These data suggest that stroke survivors vary in their ability to effectively adapt motor commands based on recent sensorimotor experience. The findings also provide indirect support for the hypothesis that final posture regulation and feedforward trajectory control are complimentary processes that may be differentially compromised following stroke

Remembering Forward: Neural Correlates of Memory and Prediction in Human Motor Adaptation

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions – including prefrontal, parietal and hippocampal cortices – exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancelation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures