Simulation of motor unit action potential recordings from intramuscular multichannel scanning electrodes

International audienceMultichannel intramuscular EMG (iEMG) recordings provide information on motor neuron behaviour, muscle fiber (MF) innervation geometry and, recently, have been proposed as means for establishing human-machine interfaces. Objective: in order to provide a reliable benchmark for computational methods applied to such recordings, we propose a simulation model for iEMG signals acquired by intramuscular multi-channel electrodes. Methods: we propose a number of modifications to the existing iEMG simulation methods, such as farthest point sampling for more uniform motor unit in-nervation centers distribution in the muscle cross-section, fiber-neuron assignment algorithm, motor neuron action potential propagation delay modelling and a linear model for multichannel recordings simulation. The proposed approach is also extended to gradually shifting (scanning) electrodes. Results: we provide representative applications of this model to the validation of methods for the estimation of motor unit territories, and for iEMG decomposition. Moreover, we extend this model to a full multichannel iEMG simulator using classical linear EMG modelling and existing approaches to the generation of motor neuron discharge sequences. Conclusions: the obtained simulation model provides physiologically accurate MUAPs across entire motor unit territories and for various electrode configurations. Significance: it can be used for the development and evaluation of mathematical methods for multichannel iEMG processing and analysis

Structure and properties of the layered perovskites in Sm-Ba-Co-Fe-O System

Perovskite oxide materials with the general formula of ABO3, where A is an alkali earth or rare earth metals and B is transition metals, have attracted much attention as cathodes for solid oxide fuel cells because of their high electronic conductivity and fast mobility of oxygen ions. The introduction of Ba2+ and Ln3+ ions with significantly different radii into the A-sites leads to a formation of layered perovskite-type structures which have formed due to the cations’ ordering in the alternating layers. Depending on the nature of rare earth and 3d metal, it was possible to obtain double LnBaM2O6-δ, triple LnBa2M3O9-δ, or quintuple Ln2Ba3M5O15-δ perovskites. The aim of the present work was studying the effect of Ln/Ba and Fe/Co ratio for the crystal and defect structure and properties of oxides in the Sm-Ba-Co-Fe-O system. Polycrystalline samples of SmBaCo2−xFexO6-δ and Sm2-εBa3+εFe5-yCoyO15-δ were prepared by the glycine–nitrate synthesis. Final annealing was performed at 1100°С in air during 120h with intermediate grindings, followed by slow cooling down to room temperature at a rate of about 100°/h. The structural parameters were refined by the Rietveld method using the Fullprof-2008 software. Transmission electron microscopy studies were performed using FEI Tecnai G2 30 UT microscope operated at 300kV. The changes of oxygen content in complex oxides were measured by coulometric titration method as a function of temperature and oxygen partial pressure. The absolute value of oxygen content in the samples was determined using a direct reduction in the TG cell by hydrogen flow and red-ox titration. Thermal expansion of samples was studied using Netzsch DIL 402C dilatometer within the temperature range 25 – 1100°С in air. Total conductivity and Seebeck coefficient were measured simultaneously using a 4-probe technique. The crystal structure of SmBaCo2−xFexO6-δ (0≤x≤0.5) was described by the orthorhombic ap×2ap×2ap cell (Pmmm sp. gr.), while SmBaCo2−xFexO6-δ (0.6≤x≤1.1) crystallized in the tetragonal structure, ap×ap×2ap cell (P4/mmm sp. gr.). The crystal structure of single-phase Sm2-εBa3+εFe5-yCoyO15-δ (ε = 0, y = 0.5–1.5; ε = 0.125, y = 0) determined by XRD was described as cubic (sp. gr. Pm3m). However, transmission electronic microscopy revealed that oxides possess tetragonal structure with 5-fold c parameter. The defect structure of oxides with double perovskite structure was described using the model based on the simple cubic perovskite SmMeO3 (Me = Co, Fe) as a reference state. Equilibrium constants and enthalpies of the point defects formation were refined. The concentrations of all defect species were calculated as functions of temperature and oxygen nonstoichiometry. The temperature dependencies of total conductivity for SmBaCo2−xFexO6-δ and Sm2-εBa3+εFe5-yCoyO15-δ possess maxima at approximately 300–350ºC in air. The partial substitution of iron for cobalt leads to a decrease in the conductivity value. Seebeck coefficient for all compounds reveals positive values within the entire temperature and oxygen partial pressure ranges that indicate predominant p-type conductivity. The dependencies of electrical conductivity and Seebeck coefficient versus oxygen nonstoichiometry were discussed on the basis of the defect structure models. The values of activation energy for fixed oxygen content values were calculated. This work was supported by the Russian Science Foundation (Grant № 18-73-00159

Recursive decomposition of electromyographic signals with a varying number of active sources: Bayesian modelling and filtering

International audienceThis paper describes a sequential decomposition algorithm for single channel intramuscular electromyography (iEMG) generated by a varying number of active motor neurons. As in previous work, we establish a Hidden Markov Model of iEMG, in which each motor neuron spike train is modeled as a renewal process with inter-spike intervals following a discrete Weibull law and motor unit action potentials are modeled as impulse responses of linear time-invariant systems with known prior. We then expand this model by introducing an activation vector associated to the state vector of the Hidden Markov Model. This activation vector represents recruitment/derecruitment of motor units and is estimated together with the state vector using Bayesian filtering. Non-stationarity of the model parameters is addressed by means of a sliding window approach, thus making the algorithm adaptive to variations in contraction force and motor unit action potential waveforms. The algorithm was validated using simulated and experimental iEMG signals with varying number of active motor units. The experimental signals were acquired from the tibialis anterior and abductor digiti minimi muscles by fine wire and needle electrodes. The decomposition accuracy in both simulated and experimental signals exceeded 90% and the recruitment/derecruitment was successfully tracked by the algorithm. Because of its parallel structure, this algorithm can be efficiently accelerated, which lays the basis for its future real-time applications in human-machine interfaces, e.g. for prosthetic control

Structure and properties of commercially pure titanium nitrided in the plasma of a low-pressure gas discharge produced by a PINK plasma generator

The paper analyzes the surface structure and properties of commercially pure VT1-0 titanium nitrided in the plasma of a low-pressure gas discharge produced by a PINK plasma generator. The analysis demonstrates that the friction coefficient of the nitrided material decreases more than four times and its wear resistance and microhardness increases more than eight and three times, respectively. The physical mechanisms responsible for the enhancement of strength and tribological properties of the material are discussed

Combined surface modification of commercial aluminum

The paper analyzes research data on the structure and properties of surface layers of commercially pure A7-grade aluminum subjected to treatment that combines deposition of a thin metal film, intense pulsed electron beam irradiation, and nitriding in low-pressure arc plasma. The analysis shows that the combined method of surface modification provides the formation of a multilayer structure with submicro- and nano-sized phases in the material through a depth of up to 40 ?m, allowing a manifold increase in its surface microhardness and wear resistance (up to 4 and 9 times, respectively) compared to the material core. The main factors responsible for the high surface strength are the saturation of the aluminum lattice with nitrogen atoms and the formation of nano-sized particles of aluminum nitride and iron aluminides

Numerical simulation of discharge plasma generation and nitriding the metals and alloys

This research provides the numerical simulation of the plasma generation in a hollow cathode as well as the diffusion of nitrogen atoms into the metal in the low-pressure glow discharge plasma. The characteristics of the gas discharge were obtained and the relation of the basic technological parameters and the structural and phase state of the nitrided material were defined. Authors provided the comparison of calculations with the experimental results of titanium nitriding by low-pressure glow discharge plasma in a hollow cathode

On-line recursive decomposition of intramuscular EMG signals using GPU-implemented bayesian filtering

Objective: Real-time intramuscular electromyography (iEMG) decomposition, which is needed in biofeedback studies and interfacing applications, is a complex procedure that involves identifying the motor neuron spike trains from a streaming iEMG recording. Methods: We have previously proposed a sequential decomposition algorithm based on a Hidden Markov Model of EMG, which used Bayesian filter to estimate unknown parameters of motor unit (MU) spike trains, as well as their action potentials (MUAPs). Here, we present a modification of this original model in order to achieve a real-time performance of the algorithm as well as a parallel computation implementation of the algorithm on Graphics Processing Unit (GPU). Specifically, the Kalman filter previously used to estimate the MUAPs, is replaced by a least-mean-square filter. Additionally, we introduce a number of heuristics that help to omit the most improbable decomposition scenarios while searching for the best solution. Then, a GPU-implementation of the proposed algorithm is presented. Results: Simulated iEMG signals containing up to 10 active MUs, as well as five experimental fine-wire iEMG signals acquired from the tibialis anterior muscle, were decomposed in real time. The accuracy of decompositions depended on the level of muscle activation, but in all cases exceeded 85%. Conclusion: The proposed method and implementation provide an accurate, real-time interface with spinal motor neurons. Significance: The presented real time implementation of the decomposition algorithm substantially broadens the domain of its application

Federal Budget and State Fiscal Policy: Macroeconomic Adaptation until 2025

The article examines the modern concept of the state fiscal policy in Russia and the possibilities of its implementation through the federal budget in the face of new global challenges. To this end, the authors assessed the resource base of the federal budget of the Russian Federation, as well as the adequacy of measures of fiscal regulation of the current economic situation. In this regard, the authors evaluated the feasibility of the initial macroeconomic indicators underlying the parameters of the federal budget for 2023–2025, primarily its revenues, and the risks of their possible change. The authors associate the key risks of failure to achieve the stated goals of the budget and tax policy for the period 2023–2025 with a sharp reduction in the resource base of the federal budget, especially its oil and gas revenues in the context of worsening geopolitical tensions and increasing sanctions pressure on the Russian Federation. The study focuses on the justification of approaches to minimize the negative consequences of external shocks both for the subjects of the Russian economy and for public finances. In the course of the study, the authors used the methods of statistical data processing, factor modeling, regression analysis and expert evaluation. The scientific novelty of the study lies in the assessment of the impact of new global challenges on the balance of the Russian federal budget and substantiation of approaches to transform fiscal regulation measures in response to these challenges. The practical significance of the study lies in the possibility of using its results in the development of state fiscal policy in the medium term under the conditions of dramatic changes in the scenario conditions of formation of the federal budget

Optimization criteria for entry into the consolidated group of taxpayers in order to create an effective tax mechanism and improve the social, economic development of regions in the Russian Federation

This article discusses the existing socio-economic development of regions. The social and economic development of the regions is directly affected by the tax ratio and mechanisms of their functioning, which are the subject of study for both foreign and Russian economists, as the state regulation of any economy is possible through tax relations between parties. In 2012, there was established the taxation of consolidated groups of taxpayers, which exists in many countries and provides payment of income taxes based on the total financial and business performance of the group. However, in our opinion, the requirements for entry into the group are much too high. The article presents a method that allows analyzing the changes in the number of potential participants of a consolidated group of taxpayers depending on the changes in the threshold of entry using indicators. These indicators can be based on the aggregate value of assets, or represented in terms of total revenue or the amount of taxes paid. The reduction in the existing criteria will optimize tax administration of the major taxpayers and more evenly redistribute financial flows between regions of Russia