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  • Language
    Python
  • License
    GNU General Publi...
  • Created over 8 years ago
  • Updated 5 months ago

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Repository Details

Open Source Analytics & Visualisation Software for Inertial Measurement Units

OpenIMU - Data Analyser for Inertial Measurement Units and Actimetry Data

Authors

  • Dominic Létourneau (@doumdi)
  • Simon Brière (@sbriere)

Description

OpenIMU aims to provide an open source and free generic data importer, viewer, manager, processor and exporter for Inertial Measurement Units (IMU) and actimetry data. By using a common sensor data format and structure, data from different sources can be imported and managed in the software. This software was developped with support from INTER.

Features

Current features

  • Common file format (SQLite) managed by OpenIMU, but that can also be opened from other software

  • Import recorded data from sensors:

  • Transfer data directly from sensors:

    • AppleWatch SensorLogger (Custom research app for data collection)
  • Data organization

    • By participants groups
    • By participants
    • By recordsets
    • By results
  • Data viewing

    • Temporal display of recordsets to quickly see when data was recorded
    • Sensor graph view plotting with zoom functions
    • GPS viewer for GPS data
  • Data processing

    • Processing module, currently supporting:
      • Freedson Activity Algorithm (Freedson PS1, Melanson E, Sirard J., Calibration of the Computer Science and Applications, Inc. accelerometer., Med Sci Sports Exerc. 1998 May;30(5):777-81)
    • Evenson Activity Alogirhtm (Kelly R. Evenson, Diane J. Catellier, Karminder Gill, Kristin S. Ondrak & Robert G. McMurray (2008) Calibration of two objective measures of physical activity for children, Journal of Sports Sciences, 26:14, 1557-1565, DOI: 10.1080/02640410802334196 )
    • Processed results viewer
  • Data exporter

    • CSV format
    • Matlab format
    • Data export selector
  • Available in French and English, and as Windows and Mac OS apps.

Planned features

  • Data splitting into sub-recordsets (by time, by day, manually)

  • More data processing modules

Screenshots

Screenshot_1 Screenshot_2 Screenshot_3 Screenshot_4 Screenshot_5 Screenshot_6

Getting Started for Developers

Please follow those steps to setup your development environment.

Requirements

  1. Make sure you have a valid compiler installed:

    1. Linux : gcc/g++
    2. Mac : LLVM through XCode
    3. Windows: Visual Studio C++ 2017
  2. Install CMake

  3. Install Qt + QtCreator

    1. Install the latest Desktop distribution fitting your compiling environment (will not be needed in the future)
  4. Install MiniConda3

  5. Install PyCharm Community Edition

Step 1 : Open the root CMakeLists.txt in QtCreator

  1. Opening the root CMakeLists.txt will allow to create and build the project
    1. Build the project using the "python-all" target, it will automatically generate the Python environment in env/python-3.10, PySide6 UI and RCC files.
    2. All python dependencies will be automatically downloaded
    3. Once the project is built, you will not need QtCreator until you change or add a resource file or a QtDesigner ui file.
    4. If you change or add ui or resources files, you need to rebuild the project from QtCreator.

Step 2 : Create a PyCharm project

  1. Using PyCharm, opening the directory "{PROJECT_ROOT}/python"
    1. Select the existing Python 3.10 environment in "{PROJECT_ROOT}/python/env/python-3.10" in the app menu: PyCharm->Preferences->Project:python->Project Interpreter

Step 3 : Run the application

  1. Run the OpenIMUApp.py application from PyCharm

  2. Edit the code as you would normally do in a python program.

  3. Run tests in the tests directory

Notes

  1. In a near future, we hope to have everything in the QtCreator IDE. Stay tuned!

Enjoy!

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