Joel W. Burdick

Effect of Epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: a case study

BACKGROUND Repeated periods of stimulation of the spinal cord and training increased the ability to control movement in animal models of spinal cord injury. We hypothesised that tonic epidural spinal cord stimulation can modulate spinal circuitry in human beings into a physiological state that enables sensory input from standing and stepping movements to serve as a source of neural control to undertake these tasks. METHODS A 23-year-old man who had paraplegia from a C7-T1 subluxation as a result of a motor vehicle accident in July 2006, presented with complete loss of clinically detectable voluntary motor function and partial preservation of sensation below the T1 cord segment. After 170 locomotor training sessions over 26 months, a 16-electrode array was surgically placed on the dura (L1-S1 cord segments) in December 2009, to allow for chronic electrical stimulation. Spinal cord stimulation was done during sessions that lasted up to 250 min. We did 29 experiments and tested several stimulation combinations and parameters with the aim of the patient achieving standing and stepping. FINDINGS Epidural stimulation enabled the man to achieve full weight-bearing standing with assistance provided only for balance for 4·25 min. The patient achieved this standing during stimulation using parameters identified as specific for standing while providing bilateral load-bearing proprioceptive input. We also noted locomotor-like patterns when stimulation parameters were optimised for stepping. Additionally, 7 months after implantation, the patient recovered supraspinal control of some leg movements, but only during epidural stimulation. INTERPRETATION Task-specific training with epidural stimulation might reactivate previously silent spared neural circuits or promote plasticity. These interventions could be a viable clinical approach for functional recovery after severe paralysis. FUNDING National Institutes of Health and Christopher and Dana Reeve Foundation.

The explicit dynamic model and inertial parameters of the PUMA 560 arm

To provide COSMOS, a dynamic model based manipulator control system, with an improved dynamic model, a PUMA 560 arm was disassembled; the inertial properties of the individual links were measured; and an explicit model incorporating all of the non-zero measured parameters was derived. The explicit model of the PUMA arm has been obtained with a derivation procedure comprised of several heuristic rules for simplification. A simplified model, abbreviated from the full explicit model with a 1% significance criterion, can be evaluated with 805 calculations, one fifth the number required by the recursive Newton-Euler method. The procedure used to derive the model is laid out; the measured inertial parameters are presented, and the model is included in an appendix.

Spike detection using the continuous wavelet transform

This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the method allows for nearly real-time execution.

Implications of Assist-As-Needed Robotic Step Training after a Complete Spinal Cord Injury on Intrinsic Strategies of Motor Learning

Robotic training paradigms that enforce a fixed kinematic control might be suboptimal for rehabilitative training because they abolish variability, an intrinsic property of neuromuscular control (Jezernik et al., 2003). In the present study we introduce “assist-as-needed” (AAN) robotic training paradigms for rehabilitation of spinal cord injury subjects. To test the efficacy of these robotic control strategies to teach spinal mice to step, we divided 27 adult female Swiss–Webster mice randomly into three groups. Each group was trained robotically by using one of three control strategies: a fixed training trajectory (Fixed group), an AAN training paradigm without interlimb coordination (Band group), and an AAN training paradigm with bilateral hindlimb coordination (Window group). Beginning at 14 d after a complete midthoracic spinal cord transection, the mice were trained daily (10 min/d, 5 d/week) to step on a treadmill 10 min after the administration of quipazine (0.5 mg/kg), a serotonin agonist, for a period of 6 weeks. During weekly performance evaluations, the mice trained with the AAN window paradigm generally showed the highest level of recovery as measured by the number, consistency, and periodicity of steps during the testing sessions. In all three measurements there were no significant differences between the Band and the Fixed training groups. These results indicate that the window training approach, which includes loose alternating interlimb coordination, is more effective than a fixed trajectory paradigm with rigid alternating interlimb coordination or an AAN paradigm without any interlimb constraints in promoting robust postinjury stepping behavior.

Sensor-Based Exploration: The Hierarchical Generalized Voronoi Graph

The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensor-based exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, then along the HGVG, and finally from the HGVG to the goal. Since the bulk of the path planning occurs on the one-dimensional HGVG, motion planning in arbitrary dimensioned spaces is virtually reduced to a one-dimensional search problem. A bulk of this paper is dedicated to ensuring the HGVG is sufficient for motion planning by demonstrating the HGVG (with its links) is an arc-wise connected structure. All of the proofs in this paper that lead toward the connectivity result focus on a large subset of spaces in R3, but wherever possible, results are derived in Rm. In fact, under a strict set of conditions, the HGVG (the GVG by itself) is indeed connected, and hence sufficient for motion planning. The chief advantage of the HGVG is that it possesses an incremental construction procedure, described in a companion paper, that constructs the HGVG using only line-of-sight sensor data. Once the robot constructs the HGVG, it has effectively explored the environment, because it can then use the HGVG to plan a path between two arbitrary configurations.

On the inverse kinematics of redundant manipulators: characterization of the self-motion manifolds

The author takes a global rather than instantaneous look at the inverse kinematics of redundant manipulators. This approach is based on a manifold mapping reformulation of manipulator kinematics. While the kinematic problem has an infinite number of solutions for redundant manipulators, the infinity of solutions can be grouped into a finite and bounded set of disjoint continuous manifolds. Each of these manifolds, termed self-motion manifolds, physically corresponds to a distinct self-motion of the manipulator, and the number, geometry, and characterizations of the self-motion manifolds are investigated.<<ETX>>

Neural prosthetic control signals from plan activity

The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals. To demonstrate how control signals can be derived from such plan activity we performed a computational study with neural activity previously recorded from the posterior parietal cortex of rhesus monkeys planning arm movements. We employed maximum likelihood decoders to estimate movement direction and to drive finite state machines governing when to move. Performance exceeded 90% with as few as 40 neurons.

Cognitive Neural Prosthetics

Research on neural prosthetics has focused largely on using activity related to hand trajectories recorded from motor cortical areas. An interesting question revolves around what other signals might be read out from the brain and used for neural prosthetic applications. Recent studies indicate that goals and expected value are among the high-level cognitive signals that can be used and will potentially enhance the ability of paralyzed patients to communicate with the outside world. Other new findings show that local field potentials provide an excellent source of information about the cognitive state of the subject and are much easier to record and maintain than spike activity. Finally, new movable probe technologies will enable recording electrodes to seek out automatically the best signals for decoding cognitive variables.

The development of a robotic endoscope

This paper describes the development of a prototype robotic endoscope for gastrointestinal diagnosis and therapy. The goal of this device is to access, in a minimally invasive fashion, the portions of the small intestine that cannot be accessed by conventional endoscopes. This paper describes the macroscopic design and function of the device, and the results of preliminary experiments that validate the concept.

Mobility of bodies in contact. I. A new 2/sup nd/ order mobility index for multiple-finger grasps

Using a configuration-space approach, the paper develops a 2nd-order mobility theory for rigid bodies in contact. A major component of this theory is a coordinate invariant 2nd-order mobility index for a body, B, in frictionless contact with finger bodies A/sub 1/,...A/sub k/. The index is an integer that captures the inherent mobility of B in an equilibrium grasp due to second order, or surface curvature, effects. It differentiates between grasps which are deemed equivalent by classical 1st-order theories, but are physically different. We further show that 2nd-order effects can be used to lower the effective mobility of a grasped object, and discuss implications of this result for achieving new lower bounds on the number of contacting finger bodies needed to immobilize an object. Physical interpretation and stability analysis of 2nd-order effects are taken up in the companion paper.