Postgraduate Diploma in EEG/Eye-Tracking Techniques and Attention Analysis
Online 800-hour Postgraduate Diploma in EEG/Eye-Tracking Techniques and Attention Analysis. 8 modules covering IEC 60601-2-26 (electroencephalographs), IEC 60601-1 (safety of medical electrical equipment) and EEGLAB. Assigned tutor and open enrolment.
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Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Relate attentional processes to their physiological markers.
Carry out high-quality EEG recordings by controlling impedances and artefacts.
Process the EEG signal through filtering, ICA, evoked potentials and spectral analysis.
Configure eye-tracking studies and extract fixation and saccade metrics.
Integrate EEG and eye-tracking in a multimodal analysis of attention.
Apply ethical, electrical safety and data protection requirements.
Design and analyse an attention study in an operational environment.
Who it's for
- Neuroergonomics researcher who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- Biomedical signal engineer who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- Human factors specialist who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- User experience researcher who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- Neurophysiology laboratory technician who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- Physiological data scientist who wishes to specialise in EEG/Eye-Tracking Techniques and Attention Analysis.
- Engineering or science graduates seeking to enter research and universities.
What you'll work with
- IEC 60601-2-26 (electroencephalographs)
- IEC 60601-1 (safety of medical electrical equipment)
- International 10-20 system of electrode placement
- ISO 9241-11 (usability)
- Declaration of Helsinki
- Regulation (EU) 2016/679 (GDPR)
8 modules · 800 h
1.1Models of attention: selective, sustained and divided1.2Posner's attentional networks1.3Mental workload and vigilance1.4Subjective measures: NASA-TLX1.5Behavioural measures and reaction times1.6Complementary physiological measures1.7Experimental design in cognitive ergonomics1.8Ethics and consent in biometric recordings1.9Applications in transport, healthcare and industry1.10Practical case: designing a vigilance study
2.1Neurophysiological origin of the signal2.2International 10-20 system2.3Wet, dry and gel electrodes2.4Amplifiers and sampling rate2.5Portable EEG and wireless systems2.6Impedance and signal quality2.7Ocular, muscular and movement artefacts2.8Event synchronisation with LSL2.9Recording protocols2.10Laboratory: EEG set-up and resting-state recording
3.1Filtering and references3.2Artefact rejection with ICA3.3Pipelines with MNE-Python and EEGLAB3.4Spectral analysis and bands3.5Alpha and theta power as load indices3.6Evoked potentials P300 and N2003.7Time-frequency analysis with wavelets3.8Functional connectivity between regions3.9Permutation statistics3.10Practice: spectral analysis with MNE-Python
4.1Physiology of eye movement4.2Fixations, saccades and smooth pursuit4.3Remote systems and eye-tracking glasses4.4Calibration and accuracy4.5Pupillometry and cognitive load4.6Blinking and drowsiness (PERCLOS)4.7Areas of interest and gaze metrics4.8Heat maps and scanpaths4.9Eye-tracking in virtual reality4.10Laboratory: gaze study on an interface
5.1EEG and gaze synchronisation5.2Fixation-related potentials5.3Fusion with heart rate and EDA5.4Feature extraction5.5State classification with machine learning5.6Cross-validation by subject5.7Individual differences between subjects5.8Model interpretation5.9Limitations of inference5.10Practice: multimodal mental workload classifier
6.1Driver drowsiness detection6.2Attention of pilots and air traffic controllers6.3Surveillance in control rooms6.4Surgery and surgeon workload6.5Evaluation of interfaces and HMI6.6Simulator-based training6.7Adaptive neuroergonomic systems6.8Advertising and neuromarketing: critiques6.9Ecological validity of studies6.10Practical case: evaluation of a vehicle HMI
7.1Privacy of neural and biometric data7.2Neurorights and mental privacy7.3GDPR and health data7.4AI Regulation and emotion recognition7.5Reproducibility and pre-registration7.6BIDS format for EEG data7.7Reporting results7.8Electrical safety of equipment7.9Limitations of consumer devices7.10Workshop: data management plan for a study
8.1Research question8.2Experimental design of the study8.3Recording set-up8.4Pilot data acquisition8.5Signal processing8.6Statistical analysis of results8.7Predictive model of attention8.8Discussion and limitations8.9Dissertation and presentation8.10Final review with the tutor
How you'll learn
Training 100% online on the SEIUM campus, with downloadable material, recorded classes and assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is EEGLAB, MNE-Python, Tobii Pro Lab, PsychoPy, MATLAB, in free, academic or evaluation versions. Case studies draw on real EEG laboratory recording procedures, eye-tracking studies with attention tasks, and synchronised multimodal analysis. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Relate attentional processes to their physiological markers.
Carry out high-quality EEG recordings by controlling impedances and artefacts.
Process the EEG signal through filtering, ICA, evoked potentials and spectral analysis.
Configure eye-tracking studies and extract fixation and saccade metrics.
Integrate EEG and eye-tracking in a multimodal analysis of attention.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical standards documentation.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme consists of 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The programme works with EEGLAB, MNE-Python, Tobii Pro Lab, PsychoPy, MATLAB. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrative project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Check the recognition policy when you enrol.
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