Publications by authors named "Rositsa Raikova"

Some evidence indicates that lower back muscles located at the non‑dominant side of the body are more fatigue resistant than their opposite counterparts presumably due to preferential use of the dominant hand. The aim of the study was to determine if any distinction exists in the surface electromyographic activity of corresponding contralateral non‑fatigued lumbar multifidus (LM) muscles as a function of hand dominance. The relative to maximum root mean square, the median frequency (MdF) and spike shape parameters were computed from the surface myoelectric signals of ipsilateral and contralateral lumbar multifidus muscle of 46 adult healthy subjects (27 right‑handed, 19 left‑handed) during voluntary contractions evoked by the single arm lifts in prone position.

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The mathematical muscle models should include several aspects of muscle structure and physiology. First, muscle force is the sum of forces of multiple motor units (MUs), which have different contractile properties and play different roles in generating muscle force. Second, whole muscle activity is an effect of net excitatory inputs to a pool of motoneurons innervating the muscle, which have different excitability, influencing MU recruitment.

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During a voluntary contraction, motor units (MUs) fire a train of action potentials, causing summation of the twitch forces, resulting in fused or unfused tetanus. Twitches have been important in studying whole-muscle contractile properties and differentiation between MU types. However, there are still knowledge gaps concerning the voluntary force generation mechanisms.

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The synchronized firings of active motor units (MUs) increase the oscillations of muscle force, observed as physiological tremor. This study aimed to investigate the effects of synchronizing the firings within three types of MUs (slow-S, fast resistant to fatigue-FR, and fast fatigable-FF) on the muscle force production using a mathematical model of the rat medial gastrocnemius muscle. The model was designed based on the actual proportion and physiological properties of MUs and motoneurons innervating the muscle.

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Background: The biomechanical background of the transitory force decrease following a sudden reduction in the stimulation frequency under selected experimental conditions was studied on fast resistant motor units (MUs) of rat medial gastrocnemius in order to better understand the mechanisms of changes in force transmission.

Methods: Firstly, MUs were stimulated with three-phase trains of stimuli (low-high-low frequency pattern) to identify patterns when the strongest force decrease (3-36.5%) following the middle high frequency stimulation was observed.

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Trunk muscle electromyographic (EMG) signals are often contaminated by the electrical activity of the heart. During low or moderate muscle force, these electrocardiographic (ECG) signals disturb the estimation of muscle activity. Butterworth high-pass filters with cut-off frequency of up to 60 Hz are often used to suppress the ECG signal.

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After a stroke, motor units stop working properly and large, fast-twitch units are more frequently affected. Their impaired functions can be investigated during dynamic tasks using electromyographic (EMG) signal analysis. The aim of this paper is to investigate changes in the parameters of the power/frequency function during elbow flexion between affected, non-affected, and healthy muscles.

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An unfused tetanus of a motor unit (MU) evoked by a train of pulses at variable interpulse intervals is the sum of non-equal twitch-like responses to these stimuli. A tool for a precise prediction of these successive contractions for MUs of different physiological types with different contractile properties is crucial for modeling the whole muscle behavior during various types of activity. The aim of this paper is to develop such a general mathematical algorithm for the MUs of the medial gastrocnemius muscle of rats.

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Slow motor units (MUs) have no sag in their unfused tetani. This study in anesthetized rats shows that the sag can be observed in slow soleus MUs after prolonged activity. Twitches and unfused tetanic contractions were recorded from male (n=35) and female (n=39) MUs before and after the four minutes of the fatigue test (trains of 13 pulses at 40 Hz repeated every second).

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Mathematical decomposition of tetanic contractions of slow motor units (MUs) of the rat heterogeneous medial gastrocnemius muscle revealed immense variability of twitch-shape responses to successive pulses, contrary to results obtained for fast MUs. The aim of this study in rat soleus muscle, almost exclusively composed of slow MUs, was to reveal whether such variability of twitch-shape decomposed components was a common property of slow MUs in the two studied muscles, and whether ranges of the force amplitude or time parameters of these decomposed twitches showed sex differences. Unfused tetanic contractions evoked by stimulation at variable interpulse intervals were analyzed for 10 MUs of males and 10 MUs of females.

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More accurate muscle models require appropriate modelling of individual twitches of motor units (MUs) and their unfused tetanic contractions. It was shown in our previous papers, using a few MUs, that modelling of unfused tetanic force curves by summation of equal twitches is not accurate, especially for slow MUs. The aim of this study was to evaluate this inaccuracy using a statistical number of MUs of the rat medial gastrocnemius muscle (15 of slow, 15 of fast resistant and 15 of fast fatigable type).

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The double discharges are observed at the onset of contractions of mammalian motor units (MUs), especially during their recruitment to strong or fast movements. Doublets lead to MU force increase and improve ability of muscles to maintain high force during prolonged contractions. In this review we discuss an ability to produce doublets by fast and slow motoneurons (MNs), their influence on the course of action potential afterhyperpolarization (AHP) as well as its role in modulation of the initial stage of the firing pattern of MNs.

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Unfused tetanic contractions evoked by trains of stimuli at variable interpulse intervals (IPIs) were recorded for 10 fast fatigable (FF), 10 fast resistant (FR), and 10 slow (S) motor units (MUs) and subsequently decomposed with a mathematical algorithm into trains of twitch-shape responses to successive stimuli. The mean stimulation frequencies were matched for each MU to evoke tetani of similar fusion degrees, whereas the variability range of IPIs was in each case 50-150% of the mean IPI. Force and time parameters of decomposed twitches were analyzed and related to the first response.

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Muscle force is due to the cumulative effect of repetitively contracting motor units (MUs). To simulate the contribution of each MU to whole muscle force, an approach implemented in a novel computer program is proposed. The individual contraction of an MU (the twitch) is modeled by a 6-parameter analytical function previously proposed; the force of one MU is a sum of its contractions due to an applied stimulation pattern, and the muscle force is the sum of the active MUs.

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In the present study a previously proposed model of a twitch based on an analytical function with four-parameters (lead, contraction and half-relaxation times and maximum force of the twitch) was validated on 115 motor units (MUs), divided into slow (S), fast-fatigue resistant (FR) and fast fatigable (FF) types. The original records were collected from electrophysiological experiments performed on MUs from the medial gastrocnemius muscle of five rats. Besides the easy calculation of the twitch parameters and their variability, the usefulness of the model was confirmed by eliminating artifacts and noise in the original twitch records, as well as by calculations of the velocity of force increase and decrease, the area under force records, and by normalization of all twitches with respect to the maximal force and contraction time.

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Repeated stimulation of motor units (MUs) causes an increase of the force output that cannot be explained by linear summation of equal twitches evoked by the same stimulation pattern. To explain this phenomenon, an algorithm for reconstructing the individual twitches, that summate into an unfused tetanus is described in the paper. The algorithm is based on an analytical function for the twitch course modeling.

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Changes in the kinematic and electromyographic characteristics that occur while learning to move as fast as possible have been studied experimentally. Experimental investigation of what happens to the individual motor units (MUs) is more difficult. Access to each MU is impossible, and the recruitment and force developing properties of all individual MUs cannot be known.

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A critical point in models of the human limbs when the aim is to investigate the motor control is the muscle model. More often the mechanical output of a muscle is considered as one musculotendon force that is a design variable in optimization tasks solved predominantly by static optimization. For dynamic conditions, the relationship between the developed force, the length and the contraction velocity of a muscle becomes important and rheological muscle models can be incorporated in the optimization tasks.

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The applicability of static optimization (and, respectively, frequently used objective functions) for prediction of individual muscle forces for dynamic conditions has often been discussed. Some of the problems are whether time-independent objective functions are suitable, and how to incorporate muscle physiology in models. The present paper deals with a twofold task: (1) implementation of hierarchical genetic algorithm (HGA) based on the properties of the motor units (MUs) twitches, and using multi-objective, time-dependent optimization functions; and (2) comparison of the results of the HGA application with those obtained through static optimization with a criterion "minimum of a weighted sum of the muscle forces raised to the power of n".

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Using the method of Lagrange multipliers an analytical solution of the optimization problem formulated for a two-dimensional, 3DOF model of the human upper limb has been described in Part I of this investigation. The objective criterion used is the following: [formula: see text], where F(i) -s are the muscle forces modelled and c(i) -s are unknown weight factors. This study is devoted to the numerical experiments performed in order to investigate which sets of the weight factors may predict physiologically reasonable muscle forces and joint reactions.

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Analytical solutions of indeterminate problems formulated for biomechanical models with more than one degree of freedom (DOF) are rarely found. This paper is an extension of the investigations of a 1 DOF model (Raikova, 1996, J. Biomechanics, 763-772) for a more complex 3 DOF model.

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