Neural Engineering

This module will introduce learners to the interdisciplinary field of Neural Engineering. Neural Engineering is an area of biomedical engineering that involves applying engineering principles and techniques to understand and interact with the human nervous system.

Most modules require a 2.2 degree in a related discipline or equivalent professional experience. Should you have any queries regarding your eligibility, please contact us at

N.B A background in engineering, physics, applied mathematics or a related discipline will be required

On successful completion of this module a learner will be able to:

1. Understand the major divisions of the nervous system and the mechanisms responsible for electrical activity of cardiac, nerve and muscle tissue.

2. Use mathematical models to calculate ionic currents and voltages in cell membranes at rest and during excitation.

3. Derive and implement mathematical models to examine the mechanisms of action potential generation and propagation in excitable cells.

4. Apply electromagnetics principles to solve for electric fields in biological tissues arising from activation of nerve, muscle and cardiac tissues.

5.Predict the effects of electrical stimuli applied to biological tissues.

6. Design appropriate protocols for electrical or magnetic stimulation of biological tissues for clinical and research applications.


Learn from world renowned academic staff in Ireland’s leading, future focused and globally recognised colleges.

Gain an accredited NFQ qualification/micro credential that you may count towards a full award if you so wish in the future.

Previous modules may be used as recognition of prior learning towards Advance Centre degree programmes.

Equip yourself with the latest in demand skillset, tools, know-how and knowledge to succeed in your career.

Gain a competitive edge, influence growth and steer strategic goals in your organisation upon completion of your studies with the Advance Centre.

Yes, if you complete this module it can be credited as part of the ProfDip Biomedical Signals & Systems

Neural Engineering

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