Course syllabus

EEN185 Neural Engineering

Neural engineering lp3 VT23 (7.5 hp), Electrical Engineering

 

Faculty Teaching assistants  Student representatives

Dr Kirstin Ahmed, Lecturer

Dr Morten Bak Kristoffersen, Lecturer

Dr Fabian Just, Lecturer

Prof Max Ortiz Catalan, Examiner

Shahrzad Damercheli

Malin Ramne

Liv Alenäs, liv.alenas01@gmail.com

Jakob Göransson, jakobmalmergoransson@hotmail.com

Viktor Olafsson, jakoki1212@gmail.com

Alice Thornander, thalice@student.chalmers.se

Annie Abrahamsson, annie.abrahamsson@telia.com

 

1. Course purpose

The purpose of the course is to provide an introduction to Neural Engineering. Subjects such as human/machine interfacing, bioelectric signals and restoration of sensorimotor impairments will be covered. Emphasis will be placed on the clinical application and functional restoration.

 

2. Schedule

This link will take you to the Chalmers calendar where all EEN185 lectures and labs are timetabled: TimeEdit

 

3. Course literature

There are two core textbooks for this course to supplement lectures: 

  1. Horch, K.W. and Kipke, D.R. eds., 2017. Neuroprosthetics: theory and practice (Vol. 8). World Scientific
  2. He, B. ed., 2020. Neural engineering. Kluwer Academic/Plenum.

Both are available as PDFs in the Modules section on Canvas.

Since Neural Engineering is a rapidly developing field a lot of EEN185 lecture content will be based on currently evolving research that may not yet be published in text books. As the course unfolds, relevant references to the newest peer reviewed research papers will be provided instead, this will be continually updated over time and referred to in relevant lectures.

 

4. Course design

The teaching is given in the form of lectures / laboratory work / projects in small groups.

This course is heavily weighted in favor of a project that is directly relevant to cutting edge research in the treatment of patients with sensorimotor impairment. Students will develop software and use hardware capable of treating patients for whom some conditions do not currently have a solution. This exciting and translational work will provide an insight into how these medical devices are conceived and implemented.

Project assessment will entail a group presentation as well as an individual report. Projects will be worked on in the laboratory sessions

 

4.1 Lectures and exam (3.5/7.5hp)

All lecture notes will be posted, there may be examination questions where content was delivered orally and is not explicitly written on the slides – therefore be aware of missing lectures. No lectures will be recorded. 

 

4.2 Project report (2/7.5hp)

Each student must write a project report in English and submit it on time. A late submission will result in failing this part of the course *(see 5.2 exemptions for late submissions). Maximum 2000 words plus figure + table captions, code, and references. 

The report will be graded U (Fail), 3 (Pass), 4 (Pass with credit) or 5 (Pass with special distinction). Grading will consider the application of the concepts learned in this course (weighted at 50%), and not the potential impact of the project device in the clinical vision part of your report. Similarly, when writing about the proof-of-concept part of your project we do not intend to weight the grading too much in favour of the technical success or breadth of your project. Both parts (clinical vision and proof-of-concept part) will carry a combined weight of 30% of the grade. If you have successfully achieved the described project outline or the agreed suggested an outline, then you will be able to achieve the best score even if you did not go beyond what was outlined. In addition, the following will be assessed (weighted at 20%):

  • The quality of the writing: this means spelling, grammar, structure (eg the use of paragraphs, headings, etc..), but also how you take the reader through your report (the reader's journey). You should ensure that the order in which you report information is logical and that everything you want the reader to understand and see is in your report and that you dont reference them away from your document in order to understand something.
  • Be clear in your communication: avoid verbosity and repetition. You have limited space and one skill in good scientific communication is to convey your message with brevity. Figures can help a lot 
  • Use of correct permissions for figures: All figures used that are not yours require permission for use (the copyright owner is the person you need permission from, they will generally be marked on the published paper. If the publisher holds the copyright, then it is still polite to ask permission from the authors as well, although this is not legally required).
  • Written format: All reports must be written in Word or Overleaf using Calibri, Arial or Times New Roman font with a minimum of 11pt font (including figure labels) and a minimum 1.15 line spacing.
  • Referencing: Only use the IEEE or Vancouver referencing system (tip. Use Mendeley or Endnote as a source management system)
  • Additional information: Include a table of contents, Illustrations are encouraged, save your file in the format: firstname_surname_EEN185report_23

 

DATE

For report submission: 3rd April 2023 at 11:59

 

4.3 Project presentation (2/7.5hp)

Each group must present their project. Presentations must be 10 minutes or less followed by up to 10 minutes of questions. A score of U (Fail), 3 (Pass), 4 (Pass with credit) or 5 (Pass with special distinction) for each of the following criteria during the presentations will be given. What has been technically achieved by your group in your project will be weighted heavily here (50%). If you have successfully achieved the described project outline or the agreed suggested an outline, then you will achieve the baseline required to pass. If you go beyond this, then you will obtain a better grade for this part of the presentation

  • The flow of the presentation made sense from start to finish
  • The presenters demonstrated a comprehensive understanding of their project 
  • All members should deliver a significant part of the presentation
  • Ensure the presentation is visually engaging including use of all multi media
  • Project outcome

If a group member cannot present that person only will fail this part of the course *(see 5.2 exemptions)

 

DATE

For group presentations will be 13th March.

 

4.4 Labs for the projects

Self selected groups of 4 or 5. Projects will be technical (Matlab will be an important part - it is advisable to have a good spread of skills in each group). You will have options provided to pick your project from. Labs should be attended by all group members. each member is required to have Matlab  installed on their machine; this can be found here. 

 

DATES (at the latest)
Mon 6th February: Upload your group (student names) and select your project and update Canvas accordingly.

Tues 7th February: Anyone without a group will be allocated a group and project.

 

4.5 Quizzes

Students will have the opportunity to earn optional bonus points that impact their grade in the form of short quizzes throughout the course. These will be published on the Quiz page on Canvas

 

4.6 Grading

Grade

5

4

3

fail

%

100 - 85

84 - 70

69 - 50

< 50

 

 

 

 

 

5. Course management

5.1 Email/Canvas emails will not be handled throughout the course.

All information required to successfully complete the course and project work will be posted on Canvas
When you have questions please approach us directly in the lab sessions. Ensure to approach Kirstin, Morten or Fabian only (not the TAs) with questions relating to the course exam, lectures and project report. However all teaching staff can handle any lab questions

 

* 5.2 Exemptions for course deadlines/exams

Exemptions from examinations/grade penalties/project presentation absence/missing report deadline or more than 2 labs will not be granted without:

either

Medical/mental health: A signed letter or email from medical doctor or a clinical psychologist stating that you are not well enough to meet the deadline(s) you have requested the letter for.

or

Compassionate grounds: A signed letter or email from a guardian/ legal representative stating that you are not well enough to meet the deadline(s) you have requested the letter for.

Communications must include a return email/postal address and telephone number.

 

6. Learning objectives and syllabus

Learning objectives:

1.    Explain why we interface humans with machines Relate how we sense input and control output in a healthy body and contrast this in an impaired body.
2.    Define what neural human/machine interfaces are and describe their differing requirements and limitations.
3.    Describe how to interface humans with machines by implanting sensors and using them to stimulate the body.
4.    Show how to record, measure and process bioelectric signals.
5.    Apply machine learning techniques on bioelectric signals.
6.    Demonstrate control of a system, such as a prosthetic limb or a virtual avatar, using bioelectric signals.
7.    Discuss how to restore sensorimotor impairments, for example how to interface a prosthetic hand with an individual who has lost a hand.
8.    Evaluate how to design a neural human machine interface (implantable electrodes predominantly).
9.    Work in a structured way together in groups and document planning and progress.

Link to the syllabus on Studieportalen.

 

7. Examination (3.5/7.5hp)

A 4 hour written exam at the end of the course will form a significant part of the course. 

Include:

  • All taught components of the course will be examinable in order to test student comprehension of the material and to ensure the learning objectives have been met.
  • The exam is compulsory
  • Grades of U (Fail), 3 (Pass), 4 (Pass with credit) or 5 (Pass with special distinction) will be applied
  • The exam will not be digital
  • The exam will be held on the 16th March
  • The exam will be after the project presentations and before the project report submission deadline