Course content

The course contains a selection of topics from the following main areas:

• Anatomy
  • Joint architecture (skeletal joints, skeletal muscles, supporting structures)
  • Basic physiology
• Biomechanics
  • Basic concepts, e.g., force, moment and torque vectors, kinematics and kinetics
  • Application of statics and dynamics to biomechanics
  • Mechanical properties of biological tissues, e.g., stress, strain and deformation, failure of structures
  • Understanding the complexity of motion
• Medical imaging and image processing
  • Introduction to Medical Imaging modalities
  • Image segmentation methods
  • 2D/3D/4D processing and visualization
• Biomechatronics
  • Introduction to biomechatronic systems
  • Use of sensors (e.g., EEG, EMG)
  • Principles of active biomechatronic systems (e.g., smart orthosis, prostheses, and others)

More details on the curriculum will provided during the start of semester.

Learning outcome

Knowledge

• The candidate is able to explain and elaborate on fundamental theory and methods related to anatomy and biomechanics, e.g.,
  • joint architecture (skeletal joints and muscles, supporting structures),
  • basic physiology, and
  • basic biomechanical concepts to understand the complexity of motion.
• The candidate is able to explain and elaborate on fundamental theory and methods related to medical imaging and and image processing, e.g.,
  • the basic physics of the individual medical imaging modalities (RG, UL, CT, MR, PET),
  • the various image segmentation methods including intensity thresholding, edge detection, region-growing and AI based methods like the use of convolutional neural network (CNN) algorithms, and
  • 2D/3D/4D visualization methods (e.g., 3D printing and holographic VR and AR).
• The candidate is able to explain and elaborate on fundamental theory and methods related to biomechatronics, e.g.,
  • general properties and usage of biomechatronic systems
  • sensor technology
  • principles for active biomechatronic systems, e.g., smart orthosis, prostheses, and others

Skills

• The candidate is able to demonstrate application of theory and methods presented in the course, e.g., by
  • perfoming experiments that demonstrate anatomy and biomechanics
  • analysing, processing or visualising medical image data
  • design and implement simple prototypes of biomechatronic systems

General competence

• The candidate is able to adopt a cybernetics systems approach and model complex systems as being composed of multiple subsystems.
• The candidate is able to discuss and communicate opportunities and challenges related the field of biomedical engineering with respect to digitalization, innovation, ethics, and sustainability.

Learning methods and activities

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.

Further on evaluation

The final grade is based on an overall evaluation of the portfolio, which consists of a number of works delivered through the semester. The portfolio contains assignments that are carried out, digitally documented and submitted during the term. Both individual and team assignments may be given. Assignments are designed to help students achieve specific course learning outcomes, and formative feedback is given during the period of the portfolio. The re-sit exam is an oral exam.

Specific conditions

Recommended previous knowledge

• IMAA1001 Matematiske metoder 1
• IMAA2011 Matematiske metoder 2
• IFYKJA1001 Fysikk og kjemi
• ISTA1002 Statistikk

Required previous knowledge

The course has no prerequisites.

It is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester and may also include English material.