Motoneuron is the control unit of skeletal muscles,and the dynamic frequency-regulating feedback from the afferent nerve of receptors like muscle spindles forms the physical basis of its closed-loop regulation.Focused on the synapses of muscle spindle afferents,this paper established a dynamical system-Markov model starting from presynaptic stimulations to postsynaptic responses,and further verified the model via comparisons between theoretical results and relevant experimental data.With the purpose of describing the active features of dendritic membrane,we employed the methods of dynamical systems rather than the traditional passive cable theory,and identified the physical meaning of parameters involved.For the dynamic behavior of postsynaptic currents,we adopted simplified Markov models so that the analytical solutions for the open dynamics of postsynaptic receptors can be obtained.The model in this paper is capable of simulating the actual non-uniformity of channel density,and is suitable for complex finite element analysis of neurons;thus it facilitates the exploration of the frequency-regulating feedback and control mechanisms of motoneurons.
Skeletal muscle is the source of human body motion.Many scholars have been studying in this field to reveal its contraction mechanism,and relevant achievements have been awarded the Nobel Prize.This paper reviewed the current researches on biomechanics of skeletal muscle,and concluded two strategies(top-down and bottom-up methods) for the biomechanical research of skeletal muscle.Moreover,this paper generalized two major aspects of muscle research:(1) the multi-force coupling mechanism and the collective operation mechanism of molecular motors;(2) the bioelectrochemical driving and control principium of muscle contraction.We discussed the solution for experimental verification and induced a novel idea to study the biomechanics of skeletal muscle based on the microscopic working mechanism of molecular motor,which is the origin of muscle contraction.Finally we analyzed the disadvantages in existent researches and explored future directions that need further studies.
This paper presents a new method for estimating the isometric contraction force and the characterization of muscle’s intrinsic property.The method,called the energy kernel method,starts with converting the electromyography(EMG)signal into planar phase portraits,on which the elliptic distribution of the state points is named as the energy kernel,while that formed by the noise signal is called the noise kernel.Based on such stochastic features of the phase portraits,we approximate the EMG signal within a rectangular window as a harmonic oscillator(EMG oscillator).The study establishes the relationship between the energy of control signal(EMG)and that of output signal(force/power),and a characteristic energy is proposed to estimate the muscle force.On the other hand,the natural frequencies of the noise and the EMG signal can be attained with the energy kernel and noise kernel.In this way,the direct signal–noise recognition and separation can be accomplished.The results show that the representativeness of the characteristic energy toward the force is satisfactory,and the method is very robust since it combines the advantages of both RMS and MPF.Moreover,the natural frequency of the EMG oscillator is not governed by the MU firing rate of a specific muscle,indicating that this frequency correlates with the intrinsic property of muscle.The physical meanings of the model provide new insights into the understanding of EMG.
