Peter Gamma (Physiologist & Director) Meditation Research Institute Switzerland (MRIS)

How to build a physiological multi-sensor device based on Home Assistant, InfluxDB & Grafana (summary)?

Last Updated on September 20, 2023 by pg@petergamma.org

We already reviewed this topic here:

to summarize the main components:

1. Start with the Apple watch:

2. Add a temperature sensor over ESP32 to Home Assistant

3. Add an AD8232 ECG Sensor over ESP32 to Home Assistant

  • How to Electronics showed how to add an AD8232 ECG Sensor over ESP32 to the Ubdots cloud.

https://how2electronics.com/iot-ecg-monitoring-ad8232-sensor-esp32/

  • Instead of connecting this circuit to Ubudots we can try if we can connect it to Home Assistant following the example with the temperature sensor shown in the video above:

4. Add an ADS1115 chip for 16 bit analog to digital conversion rate

  • ESP32 offers a bit rate of 12 bit analog to digital conversion rate:

https://docs.espressif.com/projects/esp-idf/en/v4.2/esp32/api-reference/peripherals/adc.html

  • for research applications 16 bit analog to digital conversion rate is recommended. We can solve this problem by adding an ADS1115 chip
  • Here are two more instructions which use an ECG or a PPG sensor with the ADS1115 chip:

https://www.hackster.io/pukhrajdhiman/dnn-based-homemade-ecg-a4259a

https://www.theengineeringprojects.com/2023/01/heartbeat-monitoring-system-with-ads1115-raspberry-pi-4.html

5. We can add further ECG, EEG, MEG, etc. sensor following the example of the AD8232 ECG Sensor

  • Home Assistant and InfluxDB are multi-sensor applications, so we can add as many sensors as we want.

6. We can test if we can read and write sensor data with the InfluxDB client for Python in Home Assistant

7. We can run Home Assistant on a Raspberry Pi for mobile applications