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AnyWave: a cross-platform and modular software for visualizing and processing electrophysiological signals.

B Colombet1, M Woodman1, J M Badier1

  • 1INSERM, UMR1106, Marseille, France; Aix-Marseille Université, Institut de Neurosciences des Systèmes, Marseille, France.

Journal of Neuroscience Methods
|January 24, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces AnyWave, a novel software tool for clinical neurophysiology. It visualizes and processes data, integrating new algorithms and fostering collaboration between researchers and clinicians.

Keywords:
EEGElectrophysiologyMATLABMEGMulti-platform softwarePythonSignal processing

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Clinical Neurophysiology

Background:

  • Digital signal processing is increasingly vital in clinical neurophysiology.
  • A gap exists between algorithm developers and clinical end-users.
  • There is a need for tools that bridge this gap by delivering new algorithms efficiently.

Purpose of the Study:

  • To develop a software tool that visualizes and processes neurophysiological data.
  • To create a platform for integrating and delivering new signal processing algorithms.
  • To enhance collaboration between clinical neurophysiologists and biomedical engineers.

Main Methods:

  • AnyWave is designed as an open, extensible software solution compatible with common operating systems.
  • It supports various data formats and utilizes high-fidelity visualization.
  • External tools can be integrated as plug-ins developed in C++, MATLAB, or Python.

Main Results:

  • The current version includes plug-ins for connectivity graph computation (non-linear correlation h2) and time-frequency representation (Morlet wavelets).
  • AnyWave provides an efficient neurophysiological data visualizer integrating state-of-the-art techniques.
  • The software is freely available under the LGPL3 license.

Conclusions:

  • AnyWave is an efficient neurophysiological data visualizer and processing tool.
  • Its architecture facilitates the integration of new techniques and supports clinical research needs.
  • The software is expected to improve collaboration between clinical neurophysiologists and signal processing researchers.