course-details-portlet

BEV3201 - Introduction to Signal Processing in Matlab

About

Examination arrangement

Examination arrangement: Practical examination
Grade: Passed/Failed

Evaluation Weighting Duration Grade deviation Examination aids
Practical examination 100/100 30 minutes HJELPEMIDD

Course content

The course will provide an introduction to signal analysis in Matlab. The course will include selected topics within signal processing like digital data sampling, signal-to-noise ratio, data filtering, selection of time periods, and calculation of relevant signal characteristics. The course will include introduction to basic operations in Matlab such as importing and exporting data, data visualization, and programing of simple logical structures, use of functions, indexing of data vectors and matrices, and batch processing of larger data sets. The course will use exercises and examples to show the use and interpretation of signal analysis in movement and neuroscience

Learning outcome

After completing the course BEV3201, the student is able to: 

  • Explain important aspects of signal processing like data sampling, signal-to-noise ratio, data filtering and selection of time periods, and how these factors affect calculation of relevant signal characteristics.
  • Apply basic operations in Matlab such as importing and exporting data, data visualization, programming simple logical structures, indexing data vectors and matrices, and batch processing large data sets.
  • Create a Matlab script that can read the data, improve data quality, visualize results and compute relevant signal characteristics of various signals relevant in movement and neuroscience
  • Perform signal analysis using basic operations in Matlab.
  • Explain central concepts of signal processing - Understand the importance of various aspects in signal analysis for data quality and further statistical analysis

Learning methods and activities

The course contains eight meetings of up to 5 hours which includes some lectures, but most practical exercises in Matlab. Students are expected to work on assigned tasks between the meetings and participate in all activities. The course is taught in English when required and all communications must be in English if international students are enrolled.

Compulsory assignments

  • 70% attendance meetings

Further on evaluation

Students should bring their own laptop to show what they have programmed. Otherwise no aids during the examination.

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Admission to a programme of study is required:
Human Movement Sciences (MBEV)
Medical studies (CMED)
Neuroscience (MSNEUR)
Physical Activity and Health (MSPAHE)

Required previous knowledge

As for admission to the master programmes in medicine, health and social sciences. The course is reserved for students enrolled at master programmes in medicine, health and social sciences.

Credit reductions

Course code Reduction From To
BEV8003 5.0 AUTUMN 2016
More on the course

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Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2022

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Health Science
  • Sport Science
  • Human Movement Science
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Neuromedicine and Movement Science

Timetable

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Examination

Examination arrangement: Practical examination

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Practical examination 100/100 HJELPEMIDD INSPERA
Room Building Number of candidates
Spring ORD Practical examination 100/100 HJELPEMIDD INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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