Low-Power Capacitive Sensing for Biosignal Analyses was a semester thesis that I worked on from September 2021 to January 2022. The project involved using a novel sensor called the QVAR sensor to measure biosignals such as ECG and EEG.
One of the main advantages of the QVAR sensor is that it can measure charge variations, making it possible to take dry measurements. This is especially useful for EEG measurements, as it eliminates the need for wet electrodes and makes the process more comfortable for the patient.
To implement the QVAR sensor, I designed a PCB using Altium software. The design of the PCB was critical to ensuring that the sensor could be integrated into a low-power system that could operate in a battery-powered environment.
Finally, I used an ANNA-B18 microcontroller to program the PCB and enable the QVAR sensor to measure biosignals. The microcontroller was chosen for its low power consumption and small form factor, making it ideal for use in a portable biosignal monitoring system.
Overall, the Low-Power Capacitive Sensing for Biosignal Analyses project was an exciting opportunity to work with cutting-edge technology and develop new solutions for biosignal monitoring. It required a deep understanding of both hardware and software design, as well as knowledge of signal processing and biosignal analysis techniques.