can GUI visualize and analyze ANT+ and BLE sensor data on the Linux Pinephone
The GUI v5 graphical user interface of the OpenBCI software is based on Brainflow and can run on ARM64 based devices like the Linux PinePhone:
This is good news. Matlab now has support for Bluetooth low energy sensors like the Polar OH1:
https://ch.mathworks.com/help/matlab/import_export/collect-data-from-fitness-monitoring-devices.html
I suppose this is because my endless effort to promote these sensors for desktop applications like Matlab, and because of my many questions about this subject in the Matlab community, which could not be answered by the Matlab support team.
Newer Garmin watches can also broadcast Bluetooth low energy sensor data and can be used for the Matlab example. For sporting activities, the ANT+ standard is widespread, and should in theory also be used with Matlab:
Matlab home version for 100 USD is sufficient to use it for Bluetooth low energy sensors and ANT+ with MQTT. No additional toolboxes are necessary. As far as I know, Matlab is know the first often used desktop application which can process ANT+ and Bluetooth low energy sensor data. The Matla examples only need to be put together by a software engineer and spread widely. These ANT+ and BLE sports sensors are low cost high quality physiological sensors which can be used for all kinds of purposes.
But who wants to carry around a laptop with Matlab for sporting activities? There are several software projects available for ANT+ and BLE which where developed for the Rasperri PI, which can also run on ARM based devices like the Linux PinePhone:
https://forum.pine64.org/showthread.php?tid=10172&highlight=ble+bike+computer
also these projects should be put together by a software engineer, and integrated for instance in a special Linux PinePhone distro.
Since the GUI v5 OpenBCI software should run on the Linux PinePhone, it can be used as a software platform to vizualize and analyze ANT+ and BLE sensor data.
Comments
The Polar OH1 optical heart rate sensor is a low-cost high quality sensor which has ECG accuracy:
https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0217288
The Stryd power meter foot pod is the most accurate foot pod available:
https://fellrnr.com/wiki/Stryd
With the software discussed here in this thread, these research grade sensors can be used with OpenBCI GUI v5 (needs to be tested).
Peter, hi.
You can add this capability yourself, by forking the GUI. But note that this would be quite a lot of work. As a prefix you would also need to add these devices to those supported by Brainflow. Since the GUI uses Brainflow to access the device layer.
Regards, William
OpenBCI already does support optical pulse measurement with the Pulse Sensor,
https://docs.openbci.com/docs/05ThirdParty/02-Pulse_Sensor/Pulse_Sensor_Landing
https://shop.openbci.com/collections/frontpage/products/pulse-sensor?variant=22543672899
Thanks William. I did a little research on accuracy of optical sensors. Pulse sensors with only few sensor are not very accurate. The Polar OH1 on the other side is very comfortable to wear, has six optical sensors and ECG accuracy:
https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0217288
Pulse Sensor (designed by Joel Murphy, cofounder of OpenBCI), is quite accurate and has worked for numerous other users. In addition to the GUI widget, one can also interface directly to any Arduino. As both code and hardware are open-source.
https://pulsesensor.com/