Wearable and low power eye tracking system

A wearable and low power eye tracking system is being developed at IMEC-NL. The eye-tracking is based on combination of multiple technologies including imaging and biopotential timeseries. Basic functional hardware, embedded software and an off-line algorithm have been already developed. The scope of the project is to integrate the available offline algorithms (Matlab) to an embedded solution (C/C++) that would need to show robustness for the duration of the battery (up to 8 hours). The final goal for this project would be to make a robust prototype and prove the system works properly by recording data on a small number of volunteers.

The main responsibility of the student is to develop embedded software and integrate algorithms on an ARM-Cortex M4 based environment, to enable the usage of the solution for data acquisition.

The Wearable Health Solutions (WHS) at IMEC has been working on low power circuits and systems for measurement of biopotentials over the last 10 years. With representation both in Leuven (Belgium) and Eindhoven (Netherlands), the team focuses in measurements of health parameters mostly related to electrical activity (ECG, EEG, EMG, GSR, etc). Several iterations of both ASICs and wearable systems (integrating those ASICs) have been at the forefront of the state of the art in the field of wearable signal acquisition and computing. More information....

Assignment

• Literature review.
• Embedded software development and testing (C/C++).
• Improve existing software.
• Integrate the existing algorithms and enable wireless operation.
• Testing for stabilization.
• Data collection.

Requirements

Bachelor's/Master's student with background in Software/Electrical engineering.

• Experience with firmware development in microcontrollers is a must (low level drivers, use of DMA, I2C, SPI, etc).
• Experience with embedded systems (OS and OS-less). ARM Cortex M series experience is a plus.
• Programming skills: C/C++ (language to be used) and Matlab (need to translate from Matlab to C).
• Able to read HW schematics and navigate through layouts.
• Able to use lab equipment (oscilloscopes, power supplies, logic analyzers, etc).
• Basic knowledge of signal processing.
• Experience with imaging is appreciated.
• Excellent written and verbal English skills.
• Motivated student eager to work independently and expand knowledge in the field.

Contact

prof.dr.ir. Alle-Jan van der Veen

Signal Processing Systems Group

Department of Microelectronics

Last modified: 2019-10-21