Data Analysis Software

External Software Integrations

We have a range of integration options with various external software platforms for data analysis and enhanced research capabilities. Our integrations include popular tools such as MNE, EEGLAB, OpenHDemg, I-Spin, MU Edit, BESA, Clinical Science Systems, AcqKnowledge, and more. These integrations are designed to provide seamless connectivity, ensuring that you can utilize the full potential of these advanced software systems while maintaining efficient workflows and comprehensive data analysis.

Whether you are working with EEG or HD-EMG, we have solutions to suit your needs.

MNE (Python)

BESA Software

I-Spin SAGA Live (MATLAB)

MUedit (MATLAB)

For a detailed overview of its key features and capabilities, be sure to read more about the highlights below.

List of External Software Integrations

On this page, we will start with an introduction on our File Formats and then discuss the following External Software Integrations for EEG and HD-EMG:

EEG

  • MNE

  • EEGLAB

  • BESA

  • Neurocenter

  • AcqKnowlege

HD-EMG

  • openhdemg

  • I-Spin SAGA Live

  • MUedit

File Formats (.Poly5, .XDF, .EDF)

TMSi has various file formats available to ease the analysis phase of your study. Currently, TMSi supports .Poly5 format (TMSi-native), .XDF format (LSL-native) and the widely-used .EDF format. Both the .Poly5 and .XDF formats store all data coming from your device (as they are 32-bit file formats), whereas the .EDF format removes offsets from the signal to simplify signal complexity.

The current file formats allow for integration with MNE, EEGLAB, BESA and MUedit. Refer to the table on the right for more information.

In the SAGA User Application, the APEX User Application and the TMSi Python interface, you can select whether to save data to either .XDF or .Poly5 file formats. Furthermore, the TMSi Python interface has an example that shows how to convert your .Poly5 files into .EDF files, so that you can use this data in other applications.

Available File Formats

MNE

- Compatible and SAGA and APEX - 

MNE is an open-source Python library that can be used for exploring, visualizing, and analyzing EEG data, as well as other types of physiological data. MNE offers a range of visualization options, including topographic plots, power spectral densities, and visualizations of Event-Related Potentials (ERPs). An example of the latter option can be seen in the figure below.

MNE is a library that provides many different analysis options that are well-documented. The library provides you with many off-the-shelf tools, speeding up your research process. Additionally, there’s a Graphical User Interface library available, MNELAB, which uses the core functionalities of the MNE library.

All file formats supported by TMSi can be seamlessly loaded into MNE directly as an MNE object, conveniently providing data to the different algorithms. The online documentation of MNE  includes various tutorials and comprehensive documentation of the functions available for data analysis.

As MNE is a Python library, you need to have Python installed on your PC. Next, the TMSi Python interface needs to downloaded, which includes an installer that ensuring correct installation of the MNE library. The TMSi Python interface provides different examples that use MNE, which can be found in the ‘reading_data’ folder. For instance, example scripts show how to configure .XDF and .Poly5 datasets into MNE objects. Moreover, the ‘example_ica’ uses the Independent Component Analysis (ICA) processing software offered by MNE.

Example of ERP Visualization from MNE

EEGLAB

- Compatible and SAGA and APEX - 

EEGLAB is an open-source, interactive MATLAB toolbox designed for processing and visualizing EEG data. It can be accessed either through an interactive GUI or by utilizing the structured programming environment directly.

EEGLAB is a rich toolbox, that comes with a wide range of features for visualizing and processing EEG data. Examples include: time-frequency plots, topographic maps, ERP analysis, basic filtering, independent component analysis, and multiple artifact removal algorithms.  Additionally, EEGLAB’s functionality is continuously expanded through its plugin feature, allowing research groups to contribute their own extensions.

To start using EEGLAB with TMSi’s EEG recordings, MATLAB must be installed on your PC. Loading TMSi files is most conveniently done using the .XDF format. After installing EEGLAB, various plugins can be downloaded to extend the functionalities. For instance, the load_xdf plugin facilitates the import of XDF recordings into EEGLAB.

Another option is provided by the SAGA Interface for MATLAB, which converts .Poly5 files to .set files for importation into EEGLAB. EEGLAB can be downloaded from here. Please note that some functionalities require different MATLAB toolboxes, such as the signal processing toolbox.

To start EEGLAB, add the folder to the MATLAB path and then type ‘eeglab’ in the MATLAB terminal. This will open up the GUI, allowing files to be loaded and used for analysis.

BESA

- Compatible and SAGA and APEX - 

BESA is a widely-used EEG/MEG analysis software tool, which comes with a variety of data review tools, source analysis pipelines, and other types of EEG processing algorithms. BESA is considered an easy-to-use software, making data analysis more straightforward.

The integration with BESA is based on the .EDF file format that can be saved from the TMSi Python Interface. More information on the TMSi Python Interface can be read here. After installing the TMSi Python interface, recorded .Poly5 files can be converted to .EDF files in post-processing, either file-by-file or in batches. This is an essential step to start using BESA.

Example of BESA Software

Neurocenter

- Compatible and SAGA - 

Neurocenter is a clinically-used software with many options for EEG data acquisition, review and analysis. It is known for being an all-in-one solution for handling EEGs, and is easy to use.

Montages can be configured to make viewing live signals convenient and allows you to annotate the EEGs freely. This is useful in checking for epileptiform discharges, for example.

The Neurocenter team and TMSi have collaborated to make a plugin for the SAGA system to record 32 or 64 EEG channels.

Additionally, Neurocenter has the option to store recordings on the cloud for easy collaboration and the various options for analysis pipelines. Examples include brain symmetry index scoring, alpha/delta ratio determination, spectral analysis, and more!

Example of Neurocenter Software

AcqKnowledge

- Compatible with APEX - 

AcqKnowledge is a software tool from BIOPAC that can be used for acquiring and analyzing many different (electro-)physiological data streams, as well as video feeds, stimulus presentation and more. APEX is one of the integrated hardware types that can be used with this software, bringing high-quality data into the AcqKnowledge ecosystem.

Utilizing a Graphical User Interface, AcqKnowledge caters to users without programming experience, providing access to advanced software tools. There are a variety of analysis tools available, such as spectral analysis, real-time filtering, evoked responses, and EOG artefact removal. Furthermore, data streams from other modalities, such as video feeds can also be integrated into the dataset..

APEX is integrated in a seamless fashion by means of a small controller application. The controller application is responsible for all communication between the PC and APEX, ensuring that data is provided at the requested time to AcqKnowledge. From AcqKnowledge, measurements can be started and stopped as long as the controller application is running in the background. Different files of data acquisition are available in the integration, including EEG data, impedance data, and the data that has been recorded to file. Therefore, all the types of data streams from APEX can be used with AcqKnowledge.

openhdemg

- Compatible with SAGA - 

Openhdemg is an open-source Python toolbox for the analysis of decomposed High-Density EMG data, developed by Valli et al. The library is well-documented and can be used either directly using scripting or using a Graphical User Interface (GUI). Openhdemg has a variety of analysis options, including a visualization of the Motor Unit filter, Motor Unit tracking and more.

Upon completion of an experiment, running the decomposition algorithm (e.g. using MUedit) and doing the subsequent cleaning of the obtained Motor Unit activity, the decomposed data can be loaded into openhdemg.

Please note, TMSi is working on a dedicated export function to store decomposed data into a format that’s compatible with openhdemg, allowing for a seamless transition from the TMSi Python interface to openhdemg.

I-Spin SAGA Live

- Compatible with SAGA - 

I-Spin SAGA Live is a MATLAB application for the acquisition and analysis of High-Density EMG (HD-EMG) signals. It can detect the discharge activity of individual motor units in real time. Additionally, it can apply the learned motor unit filter in real-time. This makes it possible to provide subjects with visual feedback on the Motor Unit activity during experiments.

This tool can help guide researchers who aim to study movement control at the motor neuron level. The application has been designed and constructed by a dedicated research team (Rossato et al.), who utilized TMSi’s Interface for MATLAB as a foundational tool in its development process.

Highlights of I-Spin SAGA Live

  • Acquisition of HD-EMG signals, followed by Motor Unit Decomposition, so that discharge activities are obtained for multiple single motor units.

  • Post-processing of discharge activities to intuitively clean unwanted artifacts from the decomposed signal.

  • Live application of motor unit filters enables real-time biofeedback, allowing users to understand muscle control strategies at the motor unit level.

  • Force feedback functionality allows users to control their muscle contraction level, providing a personalized and interactive experience.

  • Signal quality checks for noise levels and EMG amplitude for data reliability and high-quality results.

  • Integration with the Open Source MU Edit Library for easy access, compatibility, and seamless data management.

  • Comes with a helpful quick-start guide that offers clear, step-by-step instructions on how I-SpinSAGA works, facilitating a smooth learning process.

  • Data structure interface shared with MU Edit.

More detailed information on the implementation and available procedures can be found on the GitHub page of I-SpinSAGA. There, you will also find a step-by-step protocol that describes the application in detail, as well as how to start using it in your experimental setup. Alternatively, you can look at this blog for more information and download instructions.

Credit: I-SpinSAGA is an adaptation from I-Spin live which has been developed by J. Rossato et al. (Please cite https://doi.org/10.7554/eLife.88670.1 when you use the library for your experiments).

Example of I-Spin SAGA Live

MUedit (MATLAB)

- Compatible with SAGA - 

MUedit is an open-source MATLAB toolbox that enables you to decompose High-Density EMG (HD-EMG) signals into Motor Unit spike trains. The accompanying paper can be found here and is the first open-source implementation of Negro et al.’s frequently-used algorithm.


MUedit also contains a specific page that allows manual editing of the results of the automated process, allowing for a reduction in poorly detected motor units. Cleaning the spike trains make it possible to improve the reliability of the subsequent analysis steps.
The results coming from MUedit can be further used in other types of software to analyze and use the learned motor unit filters. Examples of these libraries include I-Spin and openhdemg.

MUedit is a MATLAB toolbox that can be downloaded here. TMSi has written file readers that are able to convert .Poly5 files and .XDF files into the toolbox, so that there is a seamless transition from TMSi’s data acquisition software into the decomposition phase using MUedit. MUedit has been tested on many different versions of MATLAB, ranging from 2018a to 2023b.

Please note, TMSi is currently working on providing the files directly in the toolbox. Until that time, the loading functions are available upon request.

Example of MUedit Software

Software

  • SAGA User Application

    SAGA User Application

    Our free software for HD-EMG and EEG measurements. Configure SAGA, measure impedances, view real-time data, and more! It is straightforward and accessible for users of all experience levels. It also provides possibilities for post-processing and analysis in MATLAB, Python, or other External Software Integrations.

    Read more
  • APEX User Application

    APEX User Application

    Our free software for EEG measurements lets you configure APEX, measure impedances, view real-time data, and more! It is straightforward and accessible for users of all experience levels. It also provides possibilities for post-processing and analysis in MATLAB, Python, or other External Software Integrations.

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  • SPIRE User Application

    SPIRE User Application

    Our free software for HD-EMG measurements lets you configure SPIRE, measure impedances, view real-time data, and more! It is straightforward and accessible for users of all experience levels. It also provides possibilities for post-processing and analysis in MATLAB, Python, or other External Software Integrations. COMING SOON!

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  • TMSi Python

    TMSi Python

    We offer our TMSi Python library that interfaces with our amplifiers. Example EEG and EMG workflows show data acquisition, impedance plots, and signal visualization (i.e heat maps). It is Open Source, allows you to build your applications, and integrates with many processing, visualization, and workflow libraries available for acquisition and synchronization.

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  • TMSi MATLAB

    TMSi MATLAB

    The TMSi SAGA Interface for MATLAB is a library enabling integration of the SAGA Device Driver with MATLAB, allowing data measurement, analysis, and customization. It includes examples for basic functionalities, visualization options for sample and impedance data, and a heatmap for EEG and HD-EMG signals.

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  • External Software

    External Software

    We have a range of integration options with various external software platforms to enhance your data analysis and research capabilities. Our integrations include popular tools such as MNE, EEGLAB, OpenHDemg, I-Spin, MU Edit, BESA, Clinical Science Systems, AcqKnowledge, and more. Whether you are working with EEG or HD-EMG, we have solutions to suit your needs.

    Read more