Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course BMEN01F valid from Spring 2017

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  • The course provides an overview of methods suitable for solving problems in biomedical signal processing. The student should obtain sufficient insights on the origin on biomedical signals and analysis methods to independently determine suitable methods.
  • Bioelectrical signals:
    Their origin, especially concerning signals reflecting the activity of the brain, the muscles, and the heart.
    Information-carrying components in bioelectrical signals.
    Common clinical applications of bioelectrical signals.

    Brain signals:
    Analysis of both spontaneous activity and evoked potentials
    Spectral analysis (nonparametric and parametric) and characterization of power spectra.
    Time-frequency analysis
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • have knowledge about biomedical signals and methods which are particularly useful for their processing.
    to apply the most common methods on clinical problems (Matlab level)
    to define simple mathematical models and to determine related, optimal methods for estimation of relevant information.
Competences and Skills
  • For a passing grade the doctoral student must
  • to understand the origin of bioelectrical signals and their manifestation on the body surface.
    to describe the most common clinical applications where such signals are used.
    to describe the most common methods for analysis of both periodic and aperiodic biomedical signals. The description is to be done in catchall terms, i.e., block diagrams and text, as well as with the help of equations.
    to formulate and describe statistical signal models being suitable for modelling of specific signal properties.
    to implement a method and evaluate its performance in clinically relevant terms.
    analyze and solve a specific signal processing problem in the framework of a project.
Judgement and Approach
  • For a passing grade the doctoral student must
  • be able to analyze, assess, and implement algorithms, and also to interpret and to describe their inherent principles.
    have insight on the fact that seemingly different technical problems can be dealt with using the same methods.
Types of Instruction
  • Lectures
  • Exercises
  • Project
Examination Formats
  • Written exam
  • 1-2 comprehensive, mandatory projects which are pursued from a problem-oriented perspective where the student has to take considerable responsability in formulating and solving the assigned task.
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • ESS040 Systems and Signals, ETI265 Signal Processing in Multimedia or ETT080 Signals and Communications or EITF15 Signal Processing - Theory and Applications.
Selection Criteria
  • L, S. & P, L.: Biomedical Signal Processing in Cardiac and Neurological Applications. Elsevier, 2005. ISBN 0124375529.
Further Information
  • With less than 16 participants, the course may be given with reduced teaching and more self studies. The course will be given in English on demand.
Course code
  • BMEN01F
Administrative Information
  •  -05-23
  • Professor Thomas Johansson

All Published Course Occasions for the Course Syllabus

4 course occasions.

Course code ▽ Course Name ▽ Division ▽ Established ▽ Course syllabus valid from ▽ Start Date ▽ End Date ▽ Published ▽
BMEN01F Biomedical Signal Processing Biomedical Engineering 2018‑02‑05 Spring 2017 2018‑03‑19 2018‑05‑30 2018‑02‑05
BMEN01F Biomedical Signal Processing Biomedical Engineering 2019‑02‑07 Spring 2017 2019‑03‑25 2019‑06‑09 2019‑02‑07
BMEN01F Biomedical Signal Processing Biomedical Engineering 2020‑02‑17 Spring 2017 2020‑03‑24 2020‑06‑07 2020‑02‑17
BMEN01F Biomedical Signal Processing Biomedical Engineering 2023‑02‑10 Spring 2017 2023‑03‑20 2023‑06‑04 2023‑02‑10

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