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Predict eye movement through brain activity
Nowadays, many people use fitness wearables to monitor health conditions. They can track calorie intake, step number, sleep quality, and heart rate. What hasn't been fully explored yet are wearables with sensors to track brain activity. Recorded brain activity could provide relevant information for attention, decision-making, health purposes, or even eye movements. One of the possible approaches to this problem is a measurement of brain activity with sensors in glasses or a headband. The advertised project aims to provide a proof of concept for this solution. We plan to measure EEG/EOG activity with dry electrodes and relate them to eye movement.
**Your task**
- Design and conduct an experiment where you measure EEG/EOG and eye movement. We will provide you with the material including the EEG/EOG wearable and an eye tracker setup.
- Analyze the robustness/limitations of your experimental setup.
- Use Machine Learning methods to predict eye movement through EEG/EOG data. This will build on former work ( http://eegeye.net ).
**Your profile**
- Background in Engineering (Biomedical, Mechanical, Chemical…)
- Familiar with Deep Learning, experience with TensorFlow or PyTorch
- Motivation to work on a project at the intersection of Neuroscience and Engineering
- Willingness to work in an interdisciplinary team (Hardware, Machine Learning, Psychology, Neuroscience)
**You would work with**
- Simone Benatti, Assistant Professor, University of Modena e Reggio Emilia
- Andrea Cossettini, Reserach Cooperation Manager, ETH Future Computing Laboratory
- Thorir Ingolfsson, PhD Candidate, Integrated Systems Laboratory, ETH Zurich
- Martyna Plomecka, PhD Candidate at Neuroscience Center Zurich, UZH
- Ard Kastrati, PhD Candidate in Distributed Computing Group, ETH Zurich
**Your task**
- Design and conduct an experiment where you measure EEG/EOG and eye movement. We will provide you with the material including the EEG/EOG wearable and an eye tracker setup.
- Analyze the robustness/limitations of your experimental setup.
- Use Machine Learning methods to predict eye movement through EEG/EOG data. This will build on former work ( http://eegeye.net ).
**Your profile**
- Background in Engineering (Biomedical, Mechanical, Chemical…)
- Familiar with Deep Learning, experience with TensorFlow or PyTorch
- Motivation to work on a project at the intersection of Neuroscience and Engineering
- Willingness to work in an interdisciplinary team (Hardware, Machine Learning, Psychology, Neuroscience)
**You would work with**
- Simone Benatti, Assistant Professor, University of Modena e Reggio Emilia
- Andrea Cossettini, Reserach Cooperation Manager, ETH Future Computing Laboratory
- Thorir Ingolfsson, PhD Candidate, Integrated Systems Laboratory, ETH Zurich
- Martyna Plomecka, PhD Candidate at Neuroscience Center Zurich, UZH
- Ard Kastrati, PhD Candidate in Distributed Computing Group, ETH Zurich
The goal will be defined together with you :)
The goal will be defined together with you :)
If you are interested, we would love to get to know you! Please write an Email to all of us including your **motivation, CV, and transcript of records**:
- Martyna Plomecka, **martyna.plomecka@uzh.ch**
- Ard Kastrati, **kard@ethz.ch**
If you are interested, we would love to get to know you! Please write an Email to all of us including your **motivation, CV, and transcript of records**:
