OpenSignals Mobile Description
OpenSignals is our user-friendly software for biosignals acquisition from PLUX devices and mobile device internal sensors. It has been designed to work seamlessly using either Bluetooth (BT) or Bluetooth Low Energy (BLE) connectivity.
OpenSignals Mobile is the perfect tool for researchers, educators, trainers, and anyone else who is curious about acquiring biosignals.
NEW FEATURES:
• Find out which internal sensors are available on your phone.
• Acquire data from all internal sensors available on your phone (including GPS, Rotation Vector, Step Counter, etc.).
• Real-time data visualisation of internal sensors.
• Acquire data from PLUX and internal android sensors at the same time using the Multi-device Data Logger.
FEATURES:
• Acquire data from Biosignalsplux and BITalino devices.
• Real-time data visualisation directly on your phone.
• Acquire data for up to 7 devices at the same time using the Multi-device Data Logger.
• All the acquired data may be saved directly on your phone in .txt file format.
This development has been partially funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement N°690494 (http://www.i-prognosis.eu/).
OpenSignals Mobile is the perfect tool for researchers, educators, trainers, and anyone else who is curious about acquiring biosignals.
NEW FEATURES:
• Find out which internal sensors are available on your phone.
• Acquire data from all internal sensors available on your phone (including GPS, Rotation Vector, Step Counter, etc.).
• Real-time data visualisation of internal sensors.
• Acquire data from PLUX and internal android sensors at the same time using the Multi-device Data Logger.
FEATURES:
• Acquire data from Biosignalsplux and BITalino devices.
• Real-time data visualisation directly on your phone.
• Acquire data for up to 7 devices at the same time using the Multi-device Data Logger.
• All the acquired data may be saved directly on your phone in .txt file format.
This development has been partially funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement N°690494 (http://www.i-prognosis.eu/).
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