Master’s in Technology-Based Neurorehabilitation Engineering
Online master's programme of 1,900 hours in technological neurorehabilitation engineering. 12 modules covering neuroplasticity, neurological assessment, rehabilitation robotics, neurostimulation, brain-computer interfaces, therapeutic virtual reality, wearable monitoring, telerehabilitation, clinical data analysis and MDR regulation, with an assigned technical tutor.
Take the controls.
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
Explain the mechanisms of neuroplasticity and functional recovery.
Assess neurological function with validated measures.
Apply robotics and stimulation in neurorehabilitation.
Develop BCI and therapeutic virtual reality systems.
Monitor rehabilitation with sensors and telerehabilitation.
Analyse clinical data to predict recovery.
Implement technologies in line with regulation and ethics.
Who it's for
- Neurorehabilitation engineers working with robots, stimulators or rehabilitation software.
- BCI researchers who want to bring their work closer to clinical rehabilitation.
- Telerehabilitation specialists designing remote therapy services.
- Clinical engineers in hospitals and brain injury units.
- Serious games developers building therapeutic virtual environments.
- Healthcare innovation managers introducing neurotechnology into services.
- Engineering or science graduates seeking to enter neurorehabilitation hospitals.
What you'll work with
- Regulation (EU) 2017/745 (EU Medical Device Regulation, MDR)
- IEC 80601-2-78 (medical robots for rehabilitation)
- ISO 14155 (clinical investigation of medical devices)
- ISO 14971 (risk management)
- IEC 62366-1 (usability engineering)
- Regulation (EU) 2016/679 (GDPR, data protection)
- IEC 60601-2-10 (nerve and muscle stimulators)
- MATLAB
- OpenViBE
- Unity
- EEGLAB
- R
12 modules · 1900 h
1.1Cellular mechanisms of neuroplasticity1.2Spontaneous recovery after stroke1.3Plasticity after spinal cord injury1.4Acquired brain injury and trauma1.5Parkinson's disease, multiple sclerosis and neurodegeneration1.6Principles of motor learning1.7Intensity, repetition and task specificity1.8Critical periods of recovery1.9Predictive biomarkers such as PREP21.10Case study: recovery curve after stroke
2.1Fugl-Meyer, Barthel and Rankin scales2.2Cognitive screening with MoCA2.3Clinical gait assessment2.4Balance with the Berg scale2.5Kinematic assessment of reaching2.6Neuroimaging with functional MRI and DTI2.7Motor evoked potentials2.8Patient-reported outcomes in neurological patients2.9Selection of measures according to the ICF2.10Practical: instrumented assessment of the upper limb
3.1End-effector robots for the arm3.2Treadmill gait exoskeletons3.3Exoskeletons for complete spinal cord injury3.4Hand rehabilitation robots3.5Assist-as-needed algorithms3.6Dosage and parameters of robotic therapy3.7Clinical trials with robots after stroke3.8Robotic devices for the home3.9Cost-effectiveness analysis of robotics3.10Laboratory: session with an upper-limb robot
4.1Functional electrical stimulation for gait4.2Therapeutic neuromuscular electrical stimulation4.3Repetitive transcranial magnetic stimulation4.4Transcranial direct current stimulation4.5Epidural spinal cord stimulation after injury4.6Paired vagus nerve stimulation4.7Neuromodulation for spasticity4.8Safety and contraindications of stimulation4.9Combining stimulation with active therapy4.10Practical: FES pattern for gait
5.1Principles and components of a BCI5.2Non-invasive EEG-based BCIs5.3Motor imagery paradigms5.4BCIs coupled to orthoses for rehabilitation5.5Neurofeedback with EEG and fMRI5.6Invasive BCIs with microelectrodes5.7Feature extraction and classification5.8BCI calibration and usability5.9Ethical issues of BCIs5.10Laboratory: motor imagery BCI with OpenViBE
6.1Immersive and non-immersive virtual reality6.2Commercial and therapeutic exergames6.3Visual, auditory and haptic feedback6.4Motivation and treatment adherence6.5Teletherapy with virtual environments6.6Cybersickness and patient tolerance6.7Cochrane reviews on virtual reality6.8Design of therapeutically meaningful virtual tasks6.9Combining virtual reality and robotics6.10Case study: VR programme for stroke
7.1Wearables for neurological patients7.2Real-world use of the affected limb7.3Inertial units in daily gait7.4Portable electromyography at home7.5Gait analysis outside the laboratory7.6Remote activity monitoring7.7Fall alerts in neurological patients7.8Sensor data for clinical decisions7.9Data protection for monitored patients7.10Practical: measuring arm use with accelerometry
8.1Synchronous and asynchronous models8.2Technology platforms for teletherapy8.3Remote functional assessment8.4Patient safety at home8.5Strategies to improve adherence8.6Role of the caregiver in teletherapy8.7Evidence on telerehabilitation effectiveness8.8Legal framework for remote care8.9Implementation in public health services8.10Workshop: design of a telerehabilitation service
9.1Study design in neurorehabilitation9.2Randomised controlled trials with devices9.3Mixed models for repeated measures9.4Machine learning with clinical data9.5Recovery prediction models9.6Stroke registries and databases9.7Systematic reviews and meta-analysis9.8Reproducibility and CONSORT guidelines9.9Minimal clinically important difference9.10Laboratory: predictive model of motor recovery
10.1Neurorehabilitation devices under the MDR10.2Classification of stimulators and robots10.3Particular requirements of IEC 80601-2-7810.4Neurorights and protection of brain activity10.5Consent in patients with cognitive impairment10.6Clinical investigations according to ISO 1415510.7Usability of devices for neurological patients10.8Risks of stimulation and robotics10.9Equity of access to neurotechnology10.10Case study: regulatory pathway for a stimulator
11.1Integration into brain injury units11.2Training of physiotherapists and occupational therapists11.3Equipment funding models11.4Health technology assessment in neurorehabilitation11.5Change management in the service11.6Quality of care indicators11.7Patient- and family-centred care11.8Continuity with primary care11.9Organisational innovation in services11.10Case study: implementation of a hospital robot
12.1Target population and clinical need12.2Review of the available evidence12.3Justified selection of the technology12.4Design of the therapeutic intervention12.5Outcome assessment protocol12.6Analysis of study data12.7Regulatory and ethical aspects of the project12.8Implementation plan for a service12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable materials, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so the programme is compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB, OpenViBE, Unity, EEGLAB and R, in free, academic or evaluation versions. Practical work is based on real procedures: robot and VR sessions in a simulated clinical environment, EEG recording for BCI and analysis of recovery data. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Regulation (EU) 2017/745 on medical devices, IEC 80601-2-78, ISO 14155, ISO 14971, IEC 62366-1, Regulation (EU) 2016/679 (GDPR), IEC 60601-2-10.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
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 totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with MATLAB, OpenViBE, Unity, EEGLAB and R, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software, and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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