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This paper presents the development of an electromyographic (EMG) signal processing system for controlling upper limb prostheses using data from the MYO Armband, which includes eight EMG sensors. The system processes raw EMG signals through filtering, frequency analysis, and other enhancement techniques to improve signal quality. An interactive MATLAB interface, built on the Myo SDK MATLAB MEX Wrapper, enables real-time visualization and application of various filters. A comprehensive comparison of filtering methods assesses their influence on signal reliability and performance. Quantitative results indicate that the Power Grip gesture produces the highest EMG activation, while the Extended Index Finger shows lower muscle engagement, highlighting distinct activation patterns. Heat map visualizations reveal spatial activation differences across sensors, essential for designing effective gesture classifiers. The developed platform enhances noise robustness and improves accuracy in interpreting motor commands. Despite hardware limitations, the system demonstrates the feasibility of adaptive prosthesis control and suggests integration with hybrid methods, such as voice control, to further enhance functionality and user experience.

This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)–(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB's variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1s (OpenSim) to 2.9s (MATLAB). For the closed-loop case, a proportional–integral–derivative controller was used to successfully balance a pole on model's hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions.

The aim of this study is to develop a research platform for rapid prototyping of the power electronics converters for solar photovoltaic (PV) system applications. This study describes the field-programmable gate array (FPGA)-based hardware-in-the-loop (HIL) simulation of voltage source inverter (VSI) used for PV system power conversion. The PV system and inverter models are realised in simulation as part of the HIL to test the real-time functionality of the FPGA controller. The generation of switching control signals for the VSI and its interface with the PV system is developed through the Xilinx System Generator (XSG) domain. The XSG automatically generates the VHSIC hardware description language (VHDL) code using hardware description language co-simulation for generation of gating signal for modulation of the VSI. To validate the proposed approach, the sinusoidal pulse-width modulation using bipolar and unipolar switching schemes and current control method have been tested for the PV supported VSI. The proposed approach of the rapid prototype model has been designed and implemented in the laboratory through XSG and MATLAB/SIMULINK interface. Performance comparison between the software simulation and real-time HIL simulation has been demonstrated.

This paper addresses the planning problem regarding the location and sizing of PV generators in distribution networks with a radial topology. This problem is mathematically modeled using a mixed integer nonlinear programming (MINLP) model, which seeks to reduce the total annual operating costs of the system for a planning horizon of 20 years. The objective function used in this paper comprises three elements: (i) the energy purchase costs at the substation node (i.e., the main supply node), (ii) the investment costs for the integration of PV generators, and (iii) the costs associated with the operation and maintenance of these devices. To solve this problem, the interconnection of MATLAB and GAMS software is proposed, while using a master–slave methodology, with which a high-quality solution to this problem is achieved. In the master stage, the MATLAB software is used as a tool to program a discrete version of the sine–cosine algorithm (DSCA), which determines the locations where the PV generators are to be installed. In the slave stage, using one of the solvers of the GAMS software (BONMIN) with the known locations of the PV generators, the MINLP model representing the problem to be studied is solved in order to find the value of the objective function and the nominal power of the PV generators. The numerical results achieved in the IEEE 33- and 69-node systems are compared with the mixed-integer conic programming model solution reported in the specialized literature, thus demonstrating the efficiency and robustness of the proposed optimization methodology.

The grounding system in substations generally uses electrode rods, because electrodes can affect the effectiveness of fault current conduction, so the equipment will be safer. Considering the importance of the grounding system, the installed grounding system must be considered and maintained properly. One of them is the grounding found in Glugur. The main objective of this research is to comprehensively evaluate the substation grounding system by modeling the grounding system at the Glugur Substation using MATLAB graphical user interface (GUI). The grounding resistance follows a grid system with an area of 20×15=300 m² with specific resistance being clay using 100 rod electrodes. From the results of ground resistance simulation modeling using MATLAB GUI, it can be concluded as follows: for a certain resistance value, the number of electrodes for 100 Ωm is 3.55 Ω, for ground resistance with a constant depth and a varying number of 100 electrodes, it is 3.45 Ω, and for. The grounding resistance with a constant and varying number of 1,000 rods is obtained at 2.65 Ω. From these results, the modeling carried out is in accordance with the standards of electricity regulations in Indonesia.

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

When optimizing chemical processes, conflicting objectives are often present (Logist et al, 2011). In industry, the trend towards sustainable development highlights this challenge because it encompasses three pillars: economy, society, and environment. A common example is the search for higher profitability while improving the safety of operation and reducing the energy consumption. In this framework, the exergy concept is highly relevant since it is understood as the confluence of energy, environment, and sustainable development (Rosen and Dincer, 2001). This contribution presents a novel approach to exploit the synergies of the exergy analysis and the gradient-based multi-objective optimization (MOO) of processes. An interface with Aspen Plus has been developed to exploit the added value of this approach, aiming to minimize the lost work in the context of conflicting objectives. The interface links the process simulator to Matlab, which is used as platform to run CasADi, a symbolic framework for algorithmic differentiation and numerical optimization (Andersson, 2013). The traditional butyl acetate production process is chosen as case study. It represents a common set-up of the chemical industry, where the conditions in the separation section are critical regarding quality but also yield and process intensity. Tri-objective constrained problems were formulated to address sustainability goals. The traditional approach based on energy consumption is compared to the case considering lost work minimization. The developed approach reveals how the minimum energy and lost work result from the partial increase in the duty for one of the distillation columns. This reflects the enhanced process understanding obtained, for which the exergy based optimization proves to be more informative, with slightly better results, and highly favorable trade-offs between objectives.

This paper introduces a recursive identification methods toolbox (called RIM) running under Matlab environment for dynamic system identification from available data. The RIM includes many methods which are generally used. The RIM helps users to validate the theoretical results and to carry out comparison between identifications methods without the need of algorithms programming. Furthermore, the RIM can be used as an education platform to study the identification parameters effect on model validity and results accuracy. To show its performance and capability, the RIM is evaluated through many application examples.