Brownian processes in human motor control support descending neural velocity commands.

The motor neuroscience literature suggests that the central nervous system may encode some motor commands in terms of velocity. In this work, we tackle the question: what consequences would velocity commands produce at the behavioral level? Considering the ubiquitous presence of noise in the neuromusculoskeletal system, we predict that velocity commands affected by stationary noise would produce "random walks", also known as Brownian processes, in position. Brownian motions are distinctively characterized by a linearly growing variance and a power spectral density that declines in inverse proportion to frequency. This work first shows that these Brownian processes are indeed observed in unbounded motion tasks e.g., rotating a crank. We further predict that such growing variance would still be present, but bounded, in tasks requiring a constant posture e.g., maintaining a static hand position or quietly standing. This hypothesis was also confirmed by experimental observations. A series of descriptive models are investigated to justify the observed behavior. Interestingly, one of the models capable of accounting for all the experimental results must feature forward-path velocity commands corrupted by stationary noise. The results of this work provide behavioral support for the hypothesis that humans plan the motion components of their actions in terms of velocity.

Dynamic primitives in constrained action: systematic changes in the zero-force trajectory.

Humans substantially outperform robotic systems in tasks that require physical interaction, despite seemingly inferior muscle bandwidth and slow neural information transmission. The control strategies that enable this performance remain poorly understood. To bridge that gap, this study examined kinematically constrained motion as an intermediate step between the widely studied unconstrained motions and sparsely studied physical interactions. Subjects turned a horizontal planar crank in two directions (clockwise and counterclockwise) at three constant target speeds (fast, medium, and very slow) as instructed via visual display. With the hand constrained to move in a circle, nonzero forces against the constraint were measured. This experiment exposed two observations that could not result from mechanics alone but may be attributed to neural control composed of dynamic primitives. A plausible mathematical model of interactive dynamics (mechanical impedance) was assumed and used to "subtract" peripheral neuromechanics. This method revealed a summary of the underlying neural control in terms of motion, a zero-force trajectory. The estimated zero-force trajectories were approximately elliptical and their orientation differed significantly with turning direction; that is consistent with control using oscillations to generate an elliptical zero-force trajectory. However, for periods longer than 2-5 s, motion can no longer be perceived or executed as periodic. Instead, it decomposes into a sequence of submovements, manifesting as increased variability. These quantifiable performance limitations support the hypothesis that humans simplify this constrained-motion task by exploiting at least three primitive dynamic actions: oscillations, submovements, and mechanical impedance.NEW & NOTEWORTHY Control using primitive dynamic actions may explain why human performance is superior to robots despite seemingly inferior "wetware"; however, this also implies limitations. For a crank-turning task, this work quantified two such informative limitations. Force was exerted even though it produced no mechanical work, the underlying zero-force trajectory was roughly elliptical, and its orientation differed with turning direction, evidence of oscillatory control. At slow speeds, speed variability increased substantially, indicating intermittent control via submovements.

Dynamic Primitives Limit Human Force Regulation during Motion.

Humans excel at physical interaction despite long feedback delays and low-bandwidth actuators. Yet little is known about how humans manage physical interaction. A quantitative understanding of how they do is critical for designing machines that can safely and effectively interact with humans, e.g. amputation prostheses, assistive exoskeletons, therapeutic rehabilitation robots, and physical human-robot collaboration. To facilitate applications, this understanding should be in the form of a simple mathematical model that not only describes humans' capabilities but also their limitations. In robotics, hybrid control allows simultaneous, independent control of both motion and force and it is often assumed that humans can modulate force independent of motion as well. This paper experimentally tested that assumption. Participants were asked to apply a constant 5N force on a robot manipulandum that moved along an elliptical path. After initial improvement, force errors quickly plateaued, despite practice and visual feedback. Within-trial analyses revealed that force errors varied with position on the ellipse, rejecting the hypothesis that humans have independent control of force and motion. The findings are consistent with a feed-forward motion command composed of two primitive oscillations acting through mechanical impedance to evoke force.

Separating neural influences from peripheral mechanics: the speed-curvature relation in mechanically constrained actions.

While the study of unconstrained movements has revealed important features of neural control, generalizing those insights to more sophisticated object manipulation is challenging. Humans excel at physical interaction with objects, even when those objects introduce complex dynamics and kinematic constraints. This study examined humans turning a horizontal planar crank (radius 10.29 cm) at their preferred and three instructed speeds (with visual feedback), both in clockwise and counterclockwise directions. To explore the role of neuromechanical dynamics, the instructed speeds covered a wide range: fast (near the limits of performance), medium (near preferred speed), and very slow (rendering dynamic effects negligible). Because kinematically constrained movements involve significant physical interaction, disentangling neural control from the influences of biomechanics presents a challenge. To address it, we modeled the interactive dynamics to "subtract off" peripheral biomechanics from observed force and kinematic data, thereby estimating aspects of underlying neural action that may be expressed in terms of motion. We demonstrate the value of this method: remarkably, an approximately elliptical path emerged, and speed minima coincided with curvature maxima, similar to what is seen in unconstrained movements, even though the hand moved at nearly constant speed along a constant-curvature path. These findings suggest that the neural controller takes advantage of peripheral biomechanics to simplify physical interaction. As a result, patterns seen in unconstrained movements persist even when physical interaction prevents their expression in hand kinematics. The reemergence of a speed-curvature relation indicates that it is due, at least in part, to neural processes that emphasize smoothness and predictability.NEW & NOTEWORTHY Physically interacting with kinematic constraints is commonplace in everyday actions. We report a study of humans turning a crank, a circular constraint that imposes constant hand path curvature and hence should suppress variations of hand speed due to the power-law speed-curvature relation widely reported for unconstrained motions. Remarkably, we found that, when peripheral biomechanical factors are removed, a speed-curvature relation reemerges, indicating that it is, at least in part, of neural origin.

Gauging force by tapping tendons.

Muscles are the actuators that drive human movement. However, despite many decades of work, we still cannot readily assess the forces that muscles transmit during human movement. Direct measurements of muscle-tendon loads are invasive and modeling approaches require many assumptions. Here, we introduce a non-invasive approach to assess tendon loads by tracking vibrational behavior. We first show that the speed of shear wave propagation in tendon increases with the square root of axial stress. We then introduce a remarkably simple shear wave tensiometer that uses micron-scale taps and skin-mounted accelerometers to track tendon wave speeds in vivo. Tendon wave speeds are shown to modulate in phase with active joint torques during isometric exertions, walking, and running. The capacity to non-invasively assess muscle-tendon loading can provide new insights into the motor control and biomechanics underlying movement, and could lead to enhanced clinical treatment of musculoskeletal injuries and diseases.

Two-dimensional dynamic fluid bowtie attenuators.

Fluence field modulated (FFM) CT allows for improvements in image quality and dose reduction. To date, only one-dimensional modulators have been proposed, as the extension to two-dimensional (2-D) modulation is difficult with solid-metal attenuation-based fluence field modulated designs. This work proposes to use liquid and gas to attenuate the x-ray beam, as unlike solids, these materials can be arranged allowing for 2-D fluence modulation. The thickness of liquid and the pressure for a given path length of gas were determined that provided the same attenuation as 30 cm of soft tissue at 80, 100, 120, and 140 kV. Liquid iodine, zinc chloride, cerium chloride, erbium oxide, iron oxide, and gadolinium chloride were studied. Gaseous xenon, uranium hexafluoride, tungsten hexafluoride, and nickel tetracarbonyl were also studied. Additionally, we performed a proof-of-concept experiment using a 96 cell array in which the liquid thickness in each cell was adjusted manually. Liquid thickness varied as a function of kV and chemical composition, with erbium oxide allowing for the smallest thickness. For the gases, tungsten hexaflouride required the smallest pressure to compensate for 30 cm of soft tissue. The 96 cell iodine attenuator allowed for a reduction in both dynamic range to the detector and scatter-to-primary ratio. For both liquids and gases, when k-edges were located within the diagnostic energy range used for imaging, the mean beam energy exhibited the smallest change with compensation amount. The thickness of liquids and the gas pressure seem logistically implementable within the space constraints of C-arm-based cone beam CT (CBCT) and diagnostic CT systems. The gas pressures also seem logistically implementable within the space and tube loading constraints of CBCT and diagnostic CT systems.

Realization of fluence field modulated CT on a clinical TomoTherapy megavoltage CT system.

The multi-leaf collimator (MLC) assembly present on TomoTherapy (Accuray, Madison WI) radiation therapy (RT) and mega voltage CT machines is well suited to perform fluence field modulated CT (FFMCT). In addition, there is a demand in the RT environment for FFMCT imaging techniques, specifically volume of interest (VOI) imaging. A clinical TomoTherapy machine was programmed to perform VOI. Four different size ROIs were placed at varying distances from isocenter. Projections intersecting the VOI received 'full dose' while those not intersecting the VOI received 30% of the dose (i.e. the incident fluence for non VOI projections was 30% of the incident fluence for projections intersecting the VOI). Additional scans without fluence field modulation were acquired at 'full' and 30% dose. The noise (pixel standard deviation) and mean CT number were measured inside the VOI region and compared between the three scans. Dose maps were generated using a dedicated TomoTherapy treatment planning dose calculator. The VOI-FFMCT technique produced an image noise 1.05, 1.00, 1.03, and 1.05 times higher than the 'full dose' scan for ROI sizes of 10 cm, 13 cm, 10 cm, and 6 cm respectively within the VOI region. The VOI-FFMCT technique required a total imaging dose equal to 0.61, 0.69, 0.60, and 0.50 times the 'full dose' acquisition dose for ROI sizes of 10 cm, 13 cm, 10 cm, and 6 cm respectively within the VOI region. Noise levels can be almost unchanged within clinically relevant VOIs sizes for RT applications while the integral imaging dose to the patient can be decreased, and/or the image quality in RT can be dramatically increased with no change in dose relative to non-FFMCT RT imaging. The ability to shift dose away from regions unimportant for clinical evaluation in order to improve image quality or reduce imaging dose has been demonstrated. This paper demonstrates that FFMCT can be performed using the MLC on a clinical TomoTherapy machine for the first time.

Creation of an atlas of filter positions for fluence field modulated CT.

PURPOSE: Fluence field modulated CT (FFMCT) and volume of interest (VOI) CT imaging applications require adjustment of the profile of the x-ray fluence incident on a patient as a function of view angle. Since current FFMCT prototypes can theoretically take on an infinite number of configurations, measuring a calibration data set for all possible positions would not be feasible. The present work details a methodology for calculating an atlas of configurations that will span all likely body regions, patient sizes, patient positioning, and imaging modes. The hypothesis is that there exists a finite number of unique modulator configurations that effectively span the infinite number of possible fluence profiles with minimal loss in performance. METHODS: CT images of a head, shoulder, thorax, abdominal, wrist, and leg anatomical slices were dilated and contracted to model small, medium, and large sized patients. Additionally, the images were positioned from iso-center by three different amounts. The modulator configurations required to compensate for each image were computed assuming a FFMCT prototype, digital beam attenuator, (DBA), was set to equalize the detector exposure. Each atlas configuration should be different from the other atlas configurations. The degree of difference was quantified using the sum of the absolute differences in filter thickness between configurations. Using this metric, a set of unique wedge configurations for which no two configurations have a metric value smaller than some threshold can be constructed. Differences in the total number of incident photons between the unconstrained filters and the atlas were studied as a function of the number of atlas positions for each anatomical site and size/off-centering combination. RESULTS: By varying the threshold used in creating the atlas, it was found that roughly 322 atlas positions provided an incident number of photons within 20% of using 19,440 unique filters (the number of atlas entries ranged from 7213 to 1). Additionally, for VOI applications implemented with a single VOI region, the number of required filter configurations was expressed in a simple closed form solution. CONCLUSIONS: The methodology proposed in this work will enable DBA-FFMCT and DBA-VOI imaging in the clinic without the need for patient specific air-scans to be performed. In addition, the methodology proposed here is directly applicable to other modulator designs such as piecewise linear, TomoTherapy multi leaf collimators, 2D fluid arrays, and inverse geometry CT.