Last Updated on September 20, 2024 by pg@petergamma.org
In recent years, Peter Gamma from www.petergamma.org has reviewed a lot about product based on the ADS1299 EEG chip from Texas Instruments:
https://petergamma.org/tag/ads1299
As you can see, we made many negative experiences with this chip. On the other hand we found that it has become easier to connect physiological sensors to the Internet of things (IoT):
And we found also great instructions how to build our own ECG device with the AD8232 ECG sensor from Scott Harden, PhD. DMD.:
Scott worked around 10 years on the development of the sound card ECG device. You can easily stream physiological sensor data to a cloud, as shown for instance in this example with the AD8232 ECG chip:
We found an instruction how to increase the A/D conversion rate to 16 bit which is required for research applications:
The instruction in the above two videos use ESP32. ESP32 is also used to stream for instance sensor data from a temperature sensor to Home Assistant:
Home Assistant was not developed for physiological sensors, but smartwatch sensor data from the Apple watch can be streamed into Home Assistant, InfluxDB and visualized in Grafana. Smartwatches deliver physiological data, but they are only of limited use for research applications. In the following example we can see this in an example with the Apple watch:
Home Assistant which is based on InfluxDB and is for house sensors. But there is also software for physiological sensors which is similar to Home Assistant. And if sensors can be attached to ESP32 to stream it into Home Assistant, we suppose that this also works with physiological software platforms which are based on InfluxDB. And instead of an ECG sensor, we can add EEG sensors. The following paper discusses how to use EEG sensors with InfluxDB:
Integrated Development Environment for EEG-Driven Cognitive-Neuropsychological Research
https://ieeexplore.ieee.org/abstract/document/9087877
OpenBCI can already be connected over ESP32 to real-time databases such as Home Assistant, Firebase, etc.:
This allows streaming of EEG sensor data up to 16 channels into an InfluxDB data base where they can be joined with other sensor data from the physiological sensors mentioned above.
This is a discussion of a physiologist who is not a soft- and hardware developer. Bu we invite you to go to a university library to check if you find instructions in the scientific literature which can be used to build your own physiological multi-sensor based on InfluxDB:
https://infozentrum.ethz.ch/en
When we go through the above instructions step by step, we are asking the question, has using InfluxDB with physiological sensor data not become easier in recent years than many years ago when we had our first look at it?
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