https://github.com/introlab/openimu

Open Source Analytics & Visualisation Software for Inertial Measurement Units
https://github.com/introlab/openimu

accelerometers analysis applewatch database energy expenditure imu imu-data inertial measurement scripting sqlalchemy sqlite3 units

Last synced: 5 days ago
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Open Source Analytics & Visualisation Software for Inertial Measurement Units

• Host: GitHub
• URL: https://github.com/introlab/openimu
• Owner: introlab
• License: gpl-3.0
• Created: 2016-01-28T17:39:43.000Z (over 9 years ago)
• Default Branch: main
• Last Pushed: 2025-01-31T18:23:56.000Z (4 months ago)
• Last Synced: 2025-05-16T06:07:44.449Z (5 days ago)
• Topics: accelerometers, analysis, applewatch, database, energy, expenditure, imu, imu-data, inertial, measurement, scripting, sqlalchemy, sqlite3, units
• Language: Python
• Size: 60.6 MB
• Stars: 285
• Watchers: 34
• Forks: 69
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.TXT

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README

        
# 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](http://regroupementinter.com).

## Features

### Current features

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

*   Import recorded data from sensors:

    *   [Actigraph GTX3 series](https://www.actigraphcorp.com/actigraph-wgt3x-bt)

    *   [OpenIMU-MiniLogger](https://github.com/introlab/OpenIMU-MiniLogger)

    *   AppleWatch SensorLogger (Custom research app for data collection)

*   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](./docs/images/Start_Screen.png)

![Screenshot_2](./docs/images/SensorView_Screen.png)

![Screenshot_3](./docs/images/GPSView_Screen.png)

![Screenshot_4](./docs/images/Analyze_Screen.png)

![Screenshot_5](./docs/images/Results_Screen.png)

![Screenshot_6](./docs/images/Export_Screen.png)

## 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](https://cmake.org/download/)

3.  Install [Qt + QtCreator](https://www.qt.io/)

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

  

4.  Install [MiniConda3](https://conda.io/miniconda.html)

    

5.  Install [PyCharm Community Edition](https://www.jetbrains.com/pycharm/)

### 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!