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Set up in 10 minutes
Install the dependencies (
Phidget22
MRPT
), the project and get up and running in minutes -
Sensor compatibility
The Phidget Load Cell and Encoder interfaces are compatible with a wide range of sensors
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Highly configurable
Sensors are defined into group types, working in a modular and flexible way
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Data recording and CSV export
It supports sampling rates up to 100 Hz and CSV data export, with or without sensor calibration parameters
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Calibration feature
It includes an interactive calibration panel to adjust sensor calibration parameters
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Open Source, GPL-3.0
The software is licensed under the GNU GPL-3.0 and available on GitHub
About the Software
A python software for synchronized data management of specific force platforms sensors compatible with Phidget API and other sensor types such as IMUs.
This project is part of the author's master's thesis in industrial engineering at the University of Almería and funded by the "Programa Operativo FEDER 2014-2020" and the Andalusian "Consejería de Transformación Económica, Industria, Conocimiento y Universidades", under the project UAL2020-CTS-A2100.

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SOFTWARE DEVELOPMENT AND CALIBRATION OF A FORCE PLATFORM FOR SPORTS SCIENCE
Check the master's thesis in spanish by clicking the button below.
A flexible configuration
The configuration file uses YAML
format for better readability, and all sensors are stored in a single configuration section for a more structured setup.
Sensors are then organized into sensor groups. If a sensor does not belong to a group, it will be ignored.
Sensor groups are fully flexible
You can define a group with sensors of the same type or different types.
Within the program, you can enable or disable specific sensors within a group or an entire group.
For more details, check out the following documentation page:
Just simple and straightforward settings.
You can even import customized configuration files with different sensors and group setups.
settings:
custom_config_path: null
test:
name: Name
folder_path: /tests/
results:
save_raw: true
save_calib: true
recording:
data_interval_ms: 10
tare_data_amount: 300
calibration:
data_interval_ms: 10
data_amount: 300
Group your sensors to get specific graphs based on the group type and enhance data organization in CSV exports.
sensor_groups:
imus:
name: Body IMUs
type: GROUP_DEFAULT
read: true
sensor_list:
- imu_1
- imu_2
- imu_3
barbell_encoders:
name: Barbell encoders
type: GROUP_DEFAULT
read: true
sensor_list:
- encoder_1
- encoder_2
Define all your sensors in this section.
sensors:
encoder_1:
name: Encoder_Z_1
type: SENSOR_ENCODER
read: true
connection:
channel: 0
serial: 641800
initial_position: 0
properties:
serial_number: AAAA
max_length: 2500mm
calibration:
slope: 0.01875
intercept: 0.0
Data graphs and CSV export
You can visualize the recorded data directly from the graphs tabs.
There are graphs for each recorded sensor, as well as specific ones depending on the sensor group type, such as force platforms.
It is also possible to trim the data and adjust the Butterworth filter used for signal processing.
For data export, the CSV format is used, allowing both raw data export and processed data export using the sensors' calibration parameters.
Quick setup
Install the required dependencies and clone the project into your workspace.
You can follow this steps to set it up in a few minutes.
Only Linux distributions are supported, preferably Ubuntu 22.04 LTS
The project has been developed and tested in Ubuntu 22.04 LTS. Phidget does support Windows and Mac OS, but Taobotics IMUs do not.
Tip
Do it in a virtual environment to avoid module installation issues (using virtualenv
, for example).
This project is developed with Python v3.10.6
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Step 1: Install the external dependencies
curl -fsSL https://www.phidgets.com/downloads/setup_linux | sudo -E bash - &&\ sudo apt-get install -y libphidget22
sudo add-apt-repository ppa:joseluisblancoc/mrpt sudo apt install libmrpt-dev mrpt-apps sudo apt install python3-pymrpt
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Step 2: Clone the
force_platform
repository
git clone https://github.com/AaronPB/force_platform.git
git clone git@github.com:AaronPB/force_platform.git
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Step 3: Install the project requirements
pip install -r requirements.txt