Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Have knowledge about different data formats and processing methods for geometrical information. 
• Have knowledge about software packages for handling biomechanical data. 
• Have knowledge on the different data storage and manipulation schemes. 
• Have knowledge on the basic processing methods to appropriately represent a time series, including data filtering and scaling.
• Have knowledge on basic correlation and curve fitting techniques.
• Have knowledge on performing multi-subject data processing steps. 

Skills

• Be able to transfer, read and store data of different sources and formats using a general programming language. 
• Be able to apply appropriate data processing steps (filtering, curve fitting) to handle biomechanical time series. 
• Be able to perform typical processing tasks for geometrical data.
• Be able to create processing codes to consistently analyze data from multiple experimental trials. 

Competences

• Be able to reflect upon the appropriate processing methods for specific data types and tasks. 
• Be able to identify limitations on the use of specific processing methods.  
• Be able assess the computational requirements for prospective studies.
• Be able to reflect upon the quality and consistency of results extracted from multi-subject processing. 

Type of instruction

The teaching is organized in accordance with the general form of teaching. Please see the programme cirruculum §17.

Extent and expected workload

Since it is a 5 ECTS course module the expected workload is 150 hours for the student.

Exam

Exams