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B Hannaford

Publications and source records attributed to B Hannaford.

10 recordsLinked to original sources
PubMed1992

Dual stable point model of muscle activation and deactivation.

Two dynamic models of muscle activation and deactivation based on the concepts of ion transport, reaction rates, and muscle mechanics are proposed. Storage release and uptake of calcium by the sarcoplasmic reticulum, and a two-step chemical reaction of calcium and troponin are included in the first model. This is a concise version of the complex chemical reactions of muscle activation and deactivation in sarcoplasm. The second model is similar to the first, but calcium-troponin reactions are simplified into two nonlinear rates functions. Due to these nonlinear dynamics, the second model can explain the catch-like enhancement of isometric force response. Simulation results which match experimental data are shown. Also, two new phenomena which need further experiment to verify are predicted by the second model.

Animals↗
PubMed1990

A nonlinear model of the phasic dynamics of muscle activation.

This paper presents a phasic excitation-activation (PEXA) model of the process of motoneuron excitation and the resultant activation and force development of a motor unit. The model input is an amount of depolarizing current (as when injected with an intracellular electrode) and the model output is muscle force. The model includes dynamics and nonlinearities similar to phenomena discovered experimentally by others: the firing rate response of motoneurons to steps of depolarizing current and the "catch-like enhancement" of force produced by overlapping motor neuron action potentials. The parameter values used in this model are derived from experimentally measured data and expressed in physical units, and model predictions extend to published data beyond those used in generating the model parameter values.

Action Potentials↗
PubMed1987

Late agonist activation burst (PC) required for optimal head movement: a simulation study.

Fast as possible (time optimal) single joint movements throughout the body are characterized by the triphasic (3 pulse) pattern of activation in the agonist and antagonist muscles. Simulation studies using a sixth order, non-linear model were undertaken to determine the relationship between time optimal movement and three pulse control. Exhaustive exploration of the multidimensional space formed by descriptive parameters of the control signal yielded control signals which drove the model to produce optimal movements. The result of these one to two week computer simulation runs was that if the limb is required to stay close to the target immediately after the end of the control signal, the fastest movements are produced by a three pulse control signal.

Biomechanical Phenomena↗
PubMed1986

An intrinsic mechanism for the oscillatory contraction of muscle.

A new model based on the theory of dynamical systems is proposed for the intrinsic random or systems is proposed for the intrinsic random or pseudo-random mechanism underlying certain types of muscular tremor. The active length-tension curve of the individual sarcomere, in conjunction with the passive length-tension relation is a map from length to tension with an observed time delay between length change and resulting tension change. The passive length tension relation is assumed to instantaneously relate this tension change back to a change in length. The stability properties of this iterated interval map are investigated by means of computer simulation and computation of the Lyapunov exponent and the bifurcation tree. The resulting analysis is related to experimental tremor data in the literature in terms of period doubling, bifurcation points, and "chaotic" behavior. The model appears to have its most fruitful application in understanding the insect type and isometric mammalian types of tremor.

Animals↗
PubMed1985

Roles of the elements of the triphasic control signal.

In fast (time-optimal) movements about many joint systems, the triphasic EMG pattern has been observed. Although the first agonist burst obviously initiates the movement, the roles of the second and third bursts, appearing in the antagonist and agonist respectively, have been less clear. In this study, the timing of experimentally measured EMG signals led to construction of a three-pulse control signal that produced an accurate simulation of experimentally measured time-optimal head rotations using a sixth-order nonlinear model in conjunction with an optimization algorithm. By ablating pulses from the model control signal and observing the resulting dynamics, the roles of the three pulses can be assessed. As a result, the pulses can be designated PA, the action pulse (for the first agonist burst), PB, the braking pulse (for the antagonist burst), and PC, the clamping pulse (for the second agonist burst). Comparison of dynamic parameters from the simulated movements revealed strategies used to generate control signals for movements of various speeds.

Electromyography↗
PubMed1985

Effects of applied vibration on triphasic electromyographic patterns in neurologically ballistic head movements.

Vibration of agonist or antagonist muscle tendon produced changes in the triphasic electromyographic pattern of neck muscles; EMG signals were rectified, averaged, and also integrated by planimetry. The triphasic EMG envelopes obtained during fast horizontal head rotation showed unmodified early agonist pulse, the action pulse (PA), under all conditions; increased antagonist pulse, the braking pulse (PB), only with antagonist muscle vibration; and increase of late agonist pulse, the clamping pulse (PC), only with agonist muscle vibration. Vibration experiments can be considered as a model for studying interactions between central and peripheral effects on control of normal movements.

Electromyography↗