A technical note on variable inter-frame interval as a cause of non-physiological experimental artefacts in ultrasound.

Ultrasound (US) imaging is a well-recognized technique for the study of static tissues but its suitability for studying tissue dynamics depends upon accurate frame time information, which may not always be available to users. Here we present methods to quantify the inter-frame interval (IFI) variability, and evaluate different procedures for collecting temporal information from two US-imaging devices. The devices tested exhibited variable IFIs that could only be confirmed by direct measures of timing signals, available by means of electrical signals (triggers) and/or temporal information contained in the software used for the US data collection. Interpolating frame-by-frame measures of dynamic changes within image sequences using individual IFI values provided improved synchronization between measures of skeletal muscle movement and activation; validating US as a valuable technique for the study of musculoskeletal tissue dynamics, when correctly implemented.

Intermittent control of unstable multivariate systems with uncertain system parameters.

Multivariable intermittent control (MIC) combines stability with flexibility in the control of unstable systems. Using an underlying continuous-time optimal control design, MIC uses models of the physical system to generate multivariate open-loop control signals between samples of the observed state. Using accurate model values of physical system parameters, stability of the closed loop system is not dependent upon sample interval. Here we consider the sensitivity of MIC to inaccurate model values of system parameters. The high dimensionality of multiple parameters combined with an unstable open loop system ensures the ratio of hyper-volumes containing good to bad parameter combinations resembles a "needle in a haystack". Is this sensitivity a problem or an asset? Prediction error between open loop and observed states provides the basis for triggering a sampling event but is also sensitive to inaccurate model values. Investigation of the mapping between prediction error and model values of physical parameters illustrates the value of prediction error to identify combinations of parameters giving stable closed loop control with low state error, similar to that provided by accurate values. Sensitivity of prediction error to model inaccuracy is potentially an asset facilitating adaptation and supporting the rationale for MIC to combine control with flexibility.

Intermittent control of unstable multivariate systems.

A sensorimotor architecture inspired from biological, vertebrate control should (i) explain the interface between high dimensional sensory analysis, low dimensional goals and high dimensional motor mechanisms and (ii) provide both stability and flexibility. Our interest concerns whether single-input-single-output intermittent control (SISO_IC) generalized to multivariable intermittent control (MIC) can meet these requirements.We base MIC on the continuous-time observer-predictorstate-feedback architecture. MIC uses event detection. A system matched hold (SMH), using the underlying continuoustime optimal control design, generates multivariate open-loop control signals between samples of the predicted state. Combined, this serial process provides a single-channel of control with optimised sensor fusion and motor synergies. Quadratic programming provides constrained, optimised equilibrium control design to handle unphysical configurations, redundancy and provides minimum, necessary reduction of open loop instability through optimised joint impedance. In this multivariate form, dimensionality is linked to goals rather than neuromuscular or sensory degrees of freedom. The biological and engineering rationale for intermittent rather than continuous multivariate control, is that the generalised hold sustains open loop predictive control while the open loop interval provides time within the feedback loop for online centralised, state dependent optimisation and selection.

A novel system of electrodes transparent to ultrasound for simultaneous detection of myoelectric activity and B-mode ultrasound images of skeletal muscles.

Application of two-dimensional surface electrode arrays can provide a means of mapping motor unit action potentials on the skin surface above a muscle. The resulting muscle tissue displacement can be quantified, in a single plane, using ultrasound (US) imaging. Currently, however, it is not possible to simultaneously map spatio-temporal propagation of activation and resulting tissue strain. In this paper, we developed and tested a material that will enable concurrent measurement of two-dimensional surface electromyograms (EMGs) with US images. Specific protocols were designed to test the compatibility of this new electrode material, both with EMG recording and with US analysis. Key results indicate that, for this new electrode material, 1) the electrode-skin impedance is similar to that of arrays of electrodes reported in literature; 2) the reflection of US at the electrode-skin interface is negligible; 3) the likelihood of observing missing contacts, short-circuits, and artifacts in EMGs is not affected by the US probe; 4) movement of tissues sampled by US can be tracked accurately. We, therefore, conclude this approach will facilitate multimodal imaging of muscle to provide new spatio-temporal information regarding electromechanical function of muscle. This is relevant to basic physiology-biomechanics of active and passive force transmission through and between muscles, of motor unit spatio-temporal activity patterns, of their variation with architecture and task-related function, and of their adaptation with aging, training-exercise-disuse, neurological disease, and injury.

Human balancing of an inverted pendulum: is sway size controlled by ankle impedance?

Using the ankle musculature, subjects balanced a large inverted pendulum. The equilibrium of the pendulum is unstable and quasi-regular sway was observed like that in quiet standing. Two main questions were addressed. Can subjects systematically change sway size in response to instruction and availability of visual feedback? If so, do subjects decrease sway size by increasing ankle impedance or by some alternative mechanism? The position of the pendulum, the torque generated at each ankle and the soleus and tibialis anterior EMG were recorded. Results showed that subjects could significantly reduce the mean sway size of the pendulum by giving full attention to that goal. With visual feedback sway size could be minimised significantly more than without visual feedback. In changing sway size, the frequency of the sways was not changed. Results also revealed that ankle impedance and muscle co-contraction were not significantly changed when the sway size was decreased. As the ankle impedance and sway frequency do not change when the sway size is decreased, this implies no change in ankle stiffness or viscosity. Increasing ankle impedance, stiffness or viscosity are not the only methods by which sway size could be reduced. A reduction in torque noise or torque inaccuracy via a predictive process which provides active damping could reduce sway size without changing ankle impedance and is plausible given the data. Such a strategy involving motion recognition and generation of an accurate motor response may require higher levels of control than changing ankle impedance by altering reflex or feedforward gain.