Last Updated on January 24, 2023 by pg@petergamma.org
If our goal is to write new code for instance for respiratory rate estimation from R-R peak data, we suggest to find a solution for an OpenBCI WIFI shield which has no issues. How this can be done is described in this journal. And then connect the OpenBCI WIFI shield over the WIFI shield Rest API to InfluxDB, and do from there our coding in Python.
The Neurosity Crown has a EEG headband with 8 channels and WIFI. The Neurosity Crown developers attached a mini PC to their EEG headband as close as possible to the sensor band. We suppose that the basis of Neurosity Crown is an OpenBCI WIFI shield with a Cyton board. And the connection goes from the WIFI shield to for instance InfluxDB. According to their description and according to other information we found, they did not use LSL or MQTT for their connection. There are some hints that they use MQTT, too. But we repeat, according to our own little experience, the best way if we want to write code to process sensor data from OpenBCI, is to connect the OpenBCI WIFI shield over REST API to for instance InfluxDB. This is the best pathway if we want to build a multi-sensor device.
We are non-coders, and this is only a speculation. We did not test this this pathway, we did only study it. But we came to this conclusion after we compared the available pathways from OpenBCI to other platforms. We found this pathway the most interesting pathway. Everything else is according to our own little experience a waist of time.
Also this instruction is complicated, as many instructions which can be found in our journal. But this is a pathway which is well documented. You can find information about where to find the documentation for it for instance in this journal. We did not test this pathway, and also not the others which are available for OpenBCI, and we are non-coders. But we can imagine to test this sensor pathway, and to see if we get it to work. This pathway described here is the most interesting for us personally.