Course syllabus
EEN185 Neural Engineering
Neural engineering lp3 HT24 (7.5 hp), Electrical Engineering
| Faculty | Teaching assistants | Student representatives |
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Dr Morten B. Kristoffersen, Lecturer (mortenb@chalmers.se) Prof. Peter Falkman, Examiner (petter.falkman@chalmers.se) |
Zhixuan Zhang (zhixuan@chalmers.se) |
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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
The core textbooks for this course to supplement lectures is:
- Horch, K.W. and Kipke, D.R. eds., 2017. Neuroprosthetics: theory and practice (Vol. 8). World Scientific
Which is available as PDF in the Modules section on Canvas.
However, 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 and a group project which you will work on in the lab sessions.
4.1 Lectures and exam (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 [date pending]
All lecture notes will be posted.
4.2 Project (4/7.5hp)
The goal of the project is to develop a proof-of-concept of a medical device OR a consumer product. At the end of the course, a functioning concept is expected and should be shown in the final presentation. For some projects, data measured and treated can make up for the demo (for example, if the application cannot easily be shown).
- For medical devices, the proof of concept should take into account the condition it will treat and the limitations of the patient group.
- For consumer product, the proof of concept should take into account the use case, the competition and be well designed.
The project will be done in self-selected groups of 4-5 people. In the labs, you will be given an EMG acquisition device which can also give tactile (vibration) stimulation. A Matlab "class" to communicate with the device will be provided, which means that coding will be in Matlab unless you wish to re-implement the class. Labs should be attended by all group members. It is recommended that everyone have Matlab installed on their machine; Matlab can be found here.
The grade (pass/fail) will be determined based on the project report and the project presentation.
DATES (at the latest)
Sun 21st January: Upload your group (student names) and select your project and update Canvas accordingly.
Mon 22nd January: Anyone without a group will be allocated a group and project.
4.2.1 Project report
Group report:
Each group must write a project report detailing the project and its implementation. The following chapters are expected:
- Introduction (describe the condition or need, and describe how you will solve it)
- Methods (how did you implement your solution, include code snippets, but only describe the most important parts of the code. Figures and diagrams can be useful to explain the implementation)
- Results (Demonstrate that your implementation works by showing data you have recorded. The data should be relevant to the condition or need (introduction) and not simply some raw EMG data)
- Discussion (What went well? What did not work (e.g. if you changed project direction, you can describe it here)
There is no word count on the group report, but I expect you to be concise.
Individual chapter
To demonstrate that each of you understand the project work, I ask you to write an individual chapter. The chapter should contain
- Summary of the project
- Next step (if you had more time, how would you have improved the project?)
- Reflection (what did you think was the most challenging/interesting aspect of the project? What would you do differently for your next project?)
You can refer to figures and tables etc. in the group report in your individual chapter.
Writing and submission (group report + individual chapter)
The report can be written in Swedish or English. The report must be submitted on time. A late submission of the report will result in failing this part of the course *(see 5.1 exemptions for late submissions).
Grading will consider the application of the concepts learned in this course, and not the potential impact of the project. 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. 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:
- The quality of the writing: this means spelling, grammar, structure (e.g. 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 do not reference them away from your document in order to understand something.
- Be clear in your communication: avoid verbosity and repetition. An important 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 should have a reference.
- Written format: All reports must be written 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)
Submission: Each student submits the group report and the individual chapter as one file. The file should be named firstname_surname_EEN185report_24
DATE
For report submission: 6th March 2024 at 11:59 (before noon)
4.2.2 Project presentation
Each group must present their project. Presentations must be 10 minutes or less followed by up to 10 minutes of questions. The aspects below will be marked to determine the grade for the project.
- 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 5.1 exemptions)
DATE
For group presentations will be 6th March.
5. Course management
* 5.1 Exemptions for course deadlines/exams
Exemptions from deadlines and exams are not 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. Meeting minutes
Course summary:
| Date | Details | Due |
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