Review



islocalmax function of matlab 2022a  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    MathWorks Inc islocalmax function of matlab 2022a
    Islocalmax Function Of Matlab 2022a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pm37660167-122-10-14
    Average 90 stars, based on 1 article reviews
    islocalmax function of matlab 2022a - by Bioz Stars, 2026-10
    90/100 stars

    Images

    Related Articles

    other:

    Article Title: NIRS-based fresh grape ripeness prediction with SPA-LASSO spectral feature selection.
    Article Snippet: Methods carried out in Matlab 2022a, and the t-test was performed using SPSS 19.0 soware.

    Article Title: Integration of parallel pathways for flight control in a hawkmoth reflects prevalence and relevance of natural visual cues
    Article Snippet: We extracted contrast edges using the MATLAB 2022a inbuilt function ‘edge’, using a Prewitt filter, and variable contrast threshold (0.01, 0.025, 0.05, 0.1 and 0.5).

    Article Title: Supporting Information for The hidden order of Turing patterns in arid vegetation ecosystems
    Article Snippet: We numerically simulate Eqs. (S1)-(S3) and Eq. (S4) in Python 3.8 (pyopencl) and MATLAB 2022a.

    Article Title: Integration of parallel pathways for flight control in a hawkmoth reflects prevalence and relevance of natural visual cues
    Article Snippet: In Matlab 2022a, we then used a filter to pass only the optic flow vectors that corresponded to translational optic flow along the camera’s trajectory.

    Article Title: Tool wear and surface integrity analysis of austenitic stainless-steel machining with variable-length restricted contact tools at large depth of cut
    Article Snippet: Austenitic stainless steels face multiple challenges during machining, including poor workability, severe tool wear, and unfavorable surface quality.. Considering the machining issues resulting from poor tool-chip contact conditions, novel restricted contact tools with variable tool-chip contact lengths were developed to enhance machining performance.. In this study, a systematic analysis was conducted to investigate the impact of variable tool-chip contact lengths on tool wear and surface integrity during the wet machining of 316L austenitic stainless-steel.

    Article Title: Hippocampal iron patterns in aging and mild cognitive impairment
    Article Snippet: Data analysis was performed using MATLAB (Version 2022a, Statistics and Machine Learning Toolbox Version 12.3, Bioinformatics Toolbox Version 4.16) software.

    Generated:

    Article Title: Design and meshing characteristics of curvilinear cylindrical gears with asymmetric teeth
    Article Snippet: .. Fig. 8 Definition of the gear pair finite element model. ( Note This figure was generated by creating an inp file using Matlab 2022a (URL: https://ww2.mathworks.cn/products/matlab.html ), and then the file was read and displayed on the screen using Abaqus 2019 (URL: https://www.3ds.com/products/simulia ).) ..



    Similar Products

    matlab function 'islocalmax  (MathWorks Inc)
    90
    MathWorks Inc matlab function 'islocalmax
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Matlab Function 'Islocalmax, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc11446545-256-12-10
    Average 90 stars, based on 1 article reviews
    matlab function 'islocalmax - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    islocalmax function of matlab 2022a  (MathWorks Inc)
    90
    MathWorks Inc islocalmax function of matlab 2022a
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Islocalmax Function Of Matlab 2022a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pm37660167-122-10-14
    Average 90 stars, based on 1 article reviews
    islocalmax function of matlab 2022a - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    islocalmax function matlab 2022a  (MathWorks Inc)
    90
    MathWorks Inc islocalmax function matlab 2022a
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Islocalmax Function Matlab 2022a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc10475048-131-10-14
    Average 90 stars, based on 1 article reviews
    islocalmax function matlab 2022a - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    matlab function islocalmax  (MathWorks Inc)
    90
    MathWorks Inc matlab function islocalmax
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Matlab Function Islocalmax, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pm37578314-74-11-13
    Average 90 stars, based on 1 article reviews
    matlab function islocalmax - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    matlab-functions islocalmax  (MathWorks Inc)
    90
    MathWorks Inc matlab-functions islocalmax
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Matlab Functions Islocalmax, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc10292016-134-8-8
    Average 90 stars, based on 1 article reviews
    matlab-functions islocalmax - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    matlab functions islocalmax  (MathWorks Inc)
    90
    MathWorks Inc matlab functions islocalmax
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Matlab Functions Islocalmax, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pm37378045-140-3-1
    Average 90 stars, based on 1 article reviews
    matlab functions islocalmax - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    matlab islocalmax function  (MathWorks Inc)
    90
    MathWorks Inc matlab islocalmax function
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Matlab Islocalmax Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc08806157-108-61-58
    Average 90 stars, based on 1 article reviews
    matlab islocalmax function - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    islocalmax (signal, minimal distance, and minimal peak prominence) matlab function  (MathWorks Inc)
    90
    MathWorks Inc islocalmax (signal, minimal distance, and minimal peak prominence) matlab function
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Islocalmax (Signal, Minimal Distance, And Minimal Peak Prominence) Matlab Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc08359364-111-68-79
    Average 90 stars, based on 1 article reviews
    islocalmax (signal, minimal distance, and minimal peak prominence) matlab function - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    islocalmax (signal, minimal distance) matlab function  (MathWorks Inc)
    90
    MathWorks Inc islocalmax (signal, minimal distance) matlab function
    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function <t>‘islocalmax’.</t> Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.
    Islocalmax (Signal, Minimal Distance) Matlab Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+function+islocalmax/pmc08359364-111-43-47
    Average 90 stars, based on 1 article reviews
    islocalmax (signal, minimal distance) matlab function - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function ‘islocalmax’. Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.

    Journal: eLife

    Article Title: I-Spin live, an open-source software based on blind-source separation for real-time decoding of motor unit activity in humans

    doi: 10.7554/eLife.88670

    Figure Lengend Snippet: ( A ) During isometric contractions, electromyographic (EMG) signals can be considered as the sum of all action potentials that originate from the muscle fibres of all the active motor units that lie within the electrodes recording zone. The shape of the recorded action potentials differs across electrodes when recorded with an array of surface or intramuscular electrodes. The EMG signal and each individual MUAP profile depends on the position of the electrode, as highlighted by the different colours. ( B ) Decomposing EMG signals consists of solving the inverse problem, that is, to estimate the discharge times of the active motor units from the EMG signals. Our software uses a fast independent component analysis (fasICA) to optimise a set of separation vectors for each motor unit. To this end, each separation vector is iteratively optimised to maximise the sparseness of the motor unit pulse train. At the end of this step, the motor unit pulse train is refined, and a k-mean classification is applied to separate the high peaks, which represent the targeted motor unit spikes, from the low peaks (other motor units and noise). ( C ) During the online EMG decomposition, the extended EMG signals recorded over 125 ms segments are projected on the separation vectors, and the peaks are detected using the function ‘islocalmax’. Each peak is classified as spike or noise depending on the distance separating them from the centroids of the classes identified during the calibration. At the end of this process, the motor unit firing activity is translated into visual feedback, in the form of a raster plot, a quadrant, or the smoothed firing rate of an identified motor unit.

    Article Snippet: Local peaks were identified for each motor unit using the MATLAB function ‘islocalmax’ with a minimal separation of 25 ms between peaks to limit the number of false positives ( ).

    Techniques: Software, Plasmid Preparation, Activity Assay