3 ECTS credits
90 h study time

Offer 1 with catalog number 4021660FNR for all students in the 2nd semester at a (F) Master - specialised level.

2nd semester
Enrollment based on exam contract
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Taught in
Partnership Agreement
Under interuniversity agreement for degree program
Faculty of Engineering
Electronics and Informatics
External partners
Universiteit Gent
Educational team
Decaan IR (course titular)
Activities and contact hours
18 contact hours Lecture
18 contact hours Seminar, Exercises or Practicals
6 contact hours Independent or External Form of Study
Course Content
This course covers neuro-engineering approaches to auditory signal processing and neuroscience, which is a core area in biomedical engineering applications that focus on sound perception and assistive hearing technology such as cochlear implants and hearing aids. The course teaches how the brain processes sound and how these processes can be modelled. Skills to analyse and design signal processing tools for auditory applications are developed. The topics range from basic auditory neuroscience to modelling these processes and developing signal processing tools that make use of this information to develop new technology (e.g., MP3, smart-phone apps, hearing-aid algorithms). The course offers hands on experience with the above concepts and combines lectures with lab exercises on auditory experiments to offer a comprehensive view of auditory neuro-engineering. With this background, students become acquainted with signal processing techniques and analysis methods for the fields of auditory signal processing, hearing technology, auditory brain-computer interfacing and the development of auditory EEG based techniques for hearing diagnostics. 
1. Physical basis:

General background of auditory neuroscience, sound perception and auditory computation
Auditory models of perception and computational models of the auditory system
Signal processing in assistive devices (hearing-aids, cochlear implants)
Auditory EEG: Hearing Diagnostics, brain-computer interface, links between EEG and sound perception
2. Application Oriented:
Basics of quantifying sound perception and quality using alternative forced choice procedures in Matlab.
Biomedical signal processing techniques and statistics to analyse auditory evoked brain potentials.
Modelling auditory neuroscience processes and computer hearing (e.g., pre-processing of speech recognition systems).
Signal processing and sound encoding in assistive devices such as hearing-aids and cochlear implants.
Hands-on experience with auditory EEG and sound perception experiments.
Additional info

Teaching staff: Sarah Verhulst, UGent, Faculteit Ingenieurswetenschappen en Architectuur, Vakgroep Informatietechnologie, +32 9 264 33 16.

Hearing, Auditory Signal Processing, Auditory Neuroscience, Auditory modelling, Assistive Device Algorithms (Hearing aids and cochlear implants) 
Initial competences 
Signal processing and filtering, basic knowledge of the EEG technique
Teaching methods 
lecture, practical sessions, self-reliant study activities 
Extra information on the teaching methods 
The lectures will provide the necessary theoretical background to understand the topic, after which a practicum will be conducted on the same topic. This lab exercise comprises either a lab-experiment (e.g., EEG recording, psychophysics sound perception experiment) or computer simulations of auditory models, assistive hearing device technology. The students can work in group to complete the exercises and need to hand in a written report for each of the 4 practical sessions. 
Learning materials and price 
Slides, (e-)book chapters, publications 


Learning Outcomes

Final Competences

1. Understand the basics of auditory neuroscience and signal processing. In particular: cochlear transformation, auditory nerve and brainstem encoding principles. 
2. Model key auditory features of the auditory system: auditory filter-bank models, and functional auditory neuronal models.
3. Be able to identify and apply the signal processing techniques and statistics to analyse auditory biomedical signals (e.g., auditory EEG).
4. A thorough understanding of how signal processing in assistive listening devices is applied.
5. Skills to further develop biomedical technology related to auditory neuroscience and sound perception.


The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

  • exam+reports+tasks with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation
Evaluation methods 
end-of-term evaluation and continuous assessment 
Examination methods in case of periodic evaluation during the first examination period 
Written examination, open book examination, oral examination 
Examination methods in case of periodic evaluation during the second examination period 
Written examination, open book examination, oral examination 
Examination methods in case of permanent evaluation 
Possibilities of retake in case of permanent evaluation 
examination during the second examination period is possible in modified form 
Extra information on the examination methods 
During examination period: oral open-book exam, graded project reports, contribution to tasks. 
Calculation of the examination mark 
Activities during the semester count for 30 % 
Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master of Biomedical Engineering: Standaard traject (only offered in Dutch)
Master of Biomedical Engineering: Startplan
Master of Biomedical Engineering: Profile Radiation Physics
Master of Biomedical Engineering: Profile Biomechanics and Biomaterials
Master of Biomedical Engineering: Profile Sensors and Medical Devices
Master of Biomedical Engineering: Profile Neuro-Engineering
Master of Biomedical Engineering: Standaard traject (NIEUW)
Master of Biomedical Engineering: Profile Artificial intelligence and Digital Health