Build the next generation of wearbles during this project! In 2016 we built a self-powering ring oximeter that measures the heart rate and the oxygen saturation in the blood using a NIRS sensor, integrated in a wearable ring. It worked pretty well: detected holding the breath, output the current pulse rate and the oxygenation via Bluetooth onto an Android app and managed to recharge the battery. Basic features:
- Bluetooth communications with a smartphone for data extraction
- A solar panel connected to a COTS energy harvester chip to run the device without charging the battery
- A low power microcontroller to compute the (pulse/oxygenation) algorithm on-board the device
- An accelerometer for motion tracking
Now we would like to upgrade the system by adding advanced machine learning capabilities for sensor fusion and replace the harvester with a more efficient chip. Wearable devices, such as smartwatches and activity trackers, are strongly limited by the available energy in their batteries. Charging devices is cumbersome and can be avoided by adding energy-harvesting capabilities to autonomously supply the device with power. CSEM developed a state-of-the-art energy-harvesting chip that efficiently extracts power from the connected solar cells. This includes intelligent adaption to changing lighting conditions, variable light distributions over the set of cells and adaptive dynamic voltage and frequency scaling (ADVFS) within the chip.
- Some experience in programming microcontrollers and developing PCBs
- Motivation to build a real systems
TBD. A detailed task description will be worked out right before the project, taking the student's interests and capabilities into account.
- Looking for master/semester project students.
- Supervision: Petar Jokic, Michele Magno
- Place of work: The project will be carried out at CSEM Zurich (in Technopark, next to Hardbrücke)
- Professor: Luca Benini