Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course BMEN30F valid from Spring 2023

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  • English
  • Every spring semester
  • The aim of this course is to give a broad overview of neural engineering concepts and principles for recording outgoing (efferent) and generating ingoing (afferent) neural signals. These concepts form the basis for neural interfaces or human-machine interfaces. This area is interdisciplinary and encompasses the fields of neuroscience, physiology, signalprocessing, machine learning and robotics. The course will give insights into existing and future neural interfaces, neural prostheses and neurorobotics.
  • The course will introduce principles and technologies of neuroengineering applications including basic human neurophysiology and -anatomy, brain stimulator, spinal cord stimulation, functional electrical stimulation (FES), neural-machine interface for motor prosthesis control, artificial visual and auditory devices for augmented sensory perception
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • be familiar with the basic anatomy and physiology of the human central and peripheral nervous system
    understand how motor commands translates into muscle actions
    understand how sensation translates into perceptions
    understand and be able to describe basic principles behind human-machine interfac
Competences and Skills
  • For a passing grade the doctoral student must
  • be able to use techniques for electroencephalography recordnings
    be able to use techniques for electromyography recordings
    be able to use techniques for nerve stimulation
    be able to apply neural engineering in different contexts
    be able to describe human-machine interfaces for the spinal cord, peripheral nerves and muscles
Judgement and Approach
  • For a passing grade the doctoral student must
  • be able to analyse, evaluate and implement human-machine interfaces
    be able to interpret and discuss informaiton from scientific literature regarding neruoengineering advances
    be able to reflect over the ethical consequences of neuroengineering
Types of Instruction
  • Lectures
  • Laboratory exercises
  • Exercises
  • Project
Examination Formats
  • Written exam
  • ing (eng) Completed laboratory work with approved laboratory report and approved assignments, approved project report and presentation.
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • Mathematics, Physics and Physiology (eg. EXTG50).
Selection Criteria
  • Lecturepresentations och labmanuals. Journal articles and book chapters (online resources)
Further Information
  • Expert guest lecturers from other faculties or other universities may appear. With less than 12 participants, the course may be given with reduced teaching and more self studies.
Course code
  • BMEN30F
Administrative Information
  • 2022-03-24
  • Professor Thomas Johansson

All Published Course Occasions for the Course Syllabus

1 course occasion.

Start Date End Date Published
2023‑01‑16 2023‑03‑19

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